mechanical engineering - ingegneria meccanica

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The aim of the course is to enable students to master advanced engineering methods for investigating the dynamics of mechanical systems, with a special focus on vibration of continuous structures and stability analysis of systems subjected to non-linear force fields. An introduction to three-dimensional rigid body dynamics and multibody techniques is also provided. The course covers theoretical models, discretisation techniques and numerical solutions based on the finite element method. Particular attention is given to practical examples and engineering applications, especially in the field of structural dynamics and rotordynamics. Each topic is treated both theoretically and practically, through traditional lectures, class exercises, experimental labs and computer room sessions.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will develop a knowledge of the modelling approaches to vibration analysis of continuous systems (DD1) and the ability to handle vibration problems for arbitrary combinations of geometrical configurations, structural properties and boundary conditions (DD2); in addition, students will understand the basic physical principles and the mathematical approach to the stability analysis of systems subjected to non-linear force fields (DD1); finally, they will get familiar with the phenomena involved in two of the most significant issues of rotordynamics (i.e. bending critical speeds and oil film instability) as well as the fundamental engineering approaches to rotor balancing and dynamic modelling of fluid lubricated journal bearings (DD1).
Concerning the ability to apply the acquired knowledge and understanding, students will develop the ability to apply theoretical knowledge to the analysis of vibration problems in complex mechanical systems and to make judgements concerning the possible alternative choices for modelling a real structure/machinery (DD2, DD3).
Through the experimental lab activities, students will learn how to process experimental data from dynamic tests and how to extract the information regarding the modal parameters of a vibrating structure, i.e. natural frequencies, damping ratios, mode shapes (DD2).
Finally, students will improve their communication skills, being able to develop skills in summarizing and presenting the results obtained during the lab activities (DD4).

The course contents are delivered through lectures, class exercises and lab activities.
The course covers the following topics divided in modules as per the description below.
Module 1. Vibration analysis of discrete systems (a short summary)
Topic 1.1. Free and forced vibration of single-dof and multi-dof systems.
Topic 1.2. Modal superposition approach and principal coordinates formulation of the equations of motion.
Module 2. Non-linear force fields and stability analysis of mechanical systems
Topic 2.1. Single-dof systems. Preliminary definitions. Non-linear force fields. Computation of the equilibrium position and linearization of the equation of motion. Stability analysis. Static and dynamic instability.
Topic 2.2. Two-dof systems. Force field which is a non-linear function of the system position only. Computation of the equilibrium position and linearization of the equations of motion. Conservative and non-conservative force fields. Stability analysis. Static and flutter instability. Non-linear field of position and velocity dependent forces. Example: 2-dof airfoil under incompressible flow.
Topic 2.3. Overview of stability analysis for multi-dof systems.
Module 3. Vibration analysis of one-dimensional continuous systems
Topic 3.1. Transverse vibration of strings. Axial vibration of bars. Torsional vibration of circular shafts. Bending vibration of slender beams (Euler-Bernoulli formulation). Wave propagation and standing wave solutions. Free vibration: natural frequencies and vibration modes for different boundary conditions, transient response to assigned initial conditions. Forced vibration: steady-state response to harmonic input.
Topic 3.2. Modal superposition approach and principal coordinates formulation of the equations of motion. Frequency Response Function formulation. Forced response to distributed and moving loads.
Module 4. Experimental modal analysis
Topic 4.1. Overview of the test procedures and estimation of the Frequency Response Function.
Topic 4.2. Algorithms for frequency-domain modal parameters identification (multi-mode curve fitting method and simplified single-mode identification procedure).
Module 5. The finite element method in structural dynamics
Topic 5.1. General introduction to the finite element discretization of continuous systems. Detailed formulation of the 6-dof beam element for in-plane analysis: shape functions for axial and bending deformation, mass and stiffness matrices.
Topic 5.2. Procedure for developing the finite element model of a structure: global and local reference systems, work-equivalent nodal forces, matrix assembling, structural damping model, boundary conditions and matrix partition. Classical dynamic analysis: natural frequencies and vibration modes, frequency response.
Module 6. Three-dimensional rigid body dynamics
Topic 6.1. Kinetic energy and inertia tensor. 3D kinematics: rotation matrix and body angular speed formulation based on Cardano angles.
Topic 6.2. Practical examples.
Module 7. Introduction to Rotordynamics
Topic 7.1. Overview of the dynamic problems in rotating machinery. Balancing conditions and balancing procedures for a rigid rotor. Bending critical speeds, balancing conditions and balancing procedures for a flexible rotor.
Topic 7.2. Fluid lubricated journal bearings and oil film instability.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The exam consists of:
a written test;
an oral examination (which includes a discussion on the lab reports).
Students are requested to deliver short reports on the two assignments given during the experimental and computer labs. Delivering the lab reports and passing the written test is mandatory for being admitted to the final oral examination. Once that these access requirements are satisfied, the final grading will be based on the outcome of the oral examination.
With reference to expected learning outcomes:
the written test is intended to verify module 3;
the discussion on lab reports is intended to verify modules 4 and 5;
the oral examination will cover all the topics illustrated in the course, with a specific focus on modules 2, 6 and 7.

F. Cheli, G. Diana, Advanced Dynamics of Mechanical Systems, Editore: Springer, Anno edizione: 2015, ISBN: 978-3319181998
L. Meirovitch, Fundamentals of Vibrations, Editore: Waveland, Anno edizione: 2010, ISBN: 978-1577666912
M. Petyt, Introduction to Finite Element Vibration Analysis, Editore: Cambridge University Press, Anno edizione: 2010, ISBN: 978-0521191609
Course handouts available on WeBeep

The aim of the course is to enable students to master advanced engineering methods for investigating the dynamics of mechanical systems, with a special focus on vibration of continuous structures and stability analysis of systems subjected to non-linear force fields. An introduction to three-dimensional rigid body dynamics and multibody techniques is also provided. The course covers theoretical models, discretisation techniques and numerical solutions based on the finite element method. Particular attention is given to practical examples and engineering applications, especially in the field of structural dynamics and rotordynamics. Each topic is treated both theoretically and practically, through traditional lectures, class exercises, experimental labs and computer room sessions.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will develop a knowledge of the modelling approaches to vibration analysis of continuous systems (DD1) and the ability to handle vibration problems for arbitrary combinations of geometrical configurations, structural properties and boundary conditions (DD2); in addition, students will understand the basic physical principles and the mathematical approach to the stability analysis of systems subjected to non-linear force fields (DD1); finally, they will get familiar with the phenomena involved in two of the most significant issues of rotordynamics (i.e. bending critical speeds and oil film instability) as well as the fundamental engineering approaches to rotor balancing and dynamic modelling of fluid lubricated journal bearings (DD1).
Concerning the ability to apply the acquired knowledge and understanding, students will develop the ability to apply theoretical knowledge to the analysis of vibration problems in complex mechanical systems and to make judgements concerning the possible alternative choices for modelling a real structure/machinery (DD2, DD3).
Through the experimental lab activities, students will learn how to process experimental data from dynamic tests and how to extract the information regarding the modal parameters of a vibrating structure, i.e. natural frequencies, damping ratios, mode shapes (DD2).
Finally, students will improve their communication skills, being able to develop skills in summarizing and presenting the results achieved during the lab activities (DD4).

The course contents are delivered through lectures, class exercises and lab activities.
The course covers the following topics divided into modules as per the description below.
Module 1. Vibration analysis of discrete systems (a short summary)
Topic 1.1. Free and forced vibration of single-dof and multi-dof systems.
Topic 1.2. Modal superposition approach and principal coordinates formulation of the equations of motion.
Module 2. Non-linear force fields and stability analysis of mechanical systems
Topic 2.1. Single-dof systems. Preliminary definitions. Non-linear force fields. Computation of the equilibrium position and linearization of the equation of motion. Stability analysis. Static and dynamic instability.
Topic 2.2. Two-dof systems. Force field which is a non-linear function of the system position only. Computation of the equilibrium position and linearization of the equations of motion. Conservative and non-conservative force fields. Stability analysis. Static and flutter instability. Non-linear field of position and velocity-dependent forces. Example: 2-dof airfoil under incompressible flow.
Topic 2.3. Overview of stability analysis for multi-dof systems.
Module 3. Vibration analysis of one-dimensional continuous systems
Topic 3.1. Transverse vibration of strings. Axial vibration of bars. Torsional vibration of circular shafts. Bending vibration of slender beams (Euler-Bernoulli formulation). Wave propagation and standing wave solutions. Free vibration: natural frequencies and vibration modes for different boundary conditions, transient response to assigned initial conditions. Forced vibration: steady-state response to harmonic input.
Topic 3.2. Modal superposition approach and principal coordinates formulation of the equations of motion. Frequency Response Function formulation. Forced response to distributed and moving loads.
Module 4. Experimental modal analysis
Topic 4.1. Overview of the test procedures and estimation of the Frequency Response Function.
Topic 4.2. Algorithms for frequency-domain modal parameters identification (multi-mode curve fitting method and simplified single-mode identification procedure).
Module 5. The finite element method in structural dynamics
Topic 5.1. General introduction to the finite element discretization of continuous systems. Detailed formulation of the 6-dof beam element for in-plane analysis: shape functions for axial and bending deformation, mass and stiffness matrices.
Topic 5.2. Procedure for developing the finite element model of a structure: global and local reference systems, work-equivalent nodal forces, matrix assembling, structural damping model, boundary conditions and matrix partition. Classical dynamic analysis: natural frequencies and vibration modes, frequency response.
Module 6. Three-dimensional rigid body dynamics
Topic 6.1. Kinetic energy and inertia tensor. 3D kinematics: rotation matrix and body angular speed formulation based on Cardano angles.
Topic 6.2. Practical examples.
Module 7. Introduction to Rotordynamics
Topic 7.1. Overview of the dynamic problems in rotating machinery. Balancing conditions and balancing procedures for a rigid rotor. Bending critical speeds, balancing conditions and balancing procedures for a flexible rotor.
Topic 7.2. Fluid-lubricated journal bearings and oil film instability.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists of:
a written test;
an oral examination (which includes a discussion of lab reports).
Students are requested to deliver short reports on the two assignments given during the experimental and computer labs. Delivering the lab reports and passing the written test is mandatory for being admitted to the final oral examination. Once these access requirements are satisfied, the final grading will be based on the outcome of the oral examination.
With reference to expected learning outcomes:
the written test is intended to verify module 3;
the discussion on lab reports is intended to verify modules 4 and 5;
the oral examination will cover all the topics illustrated in the course, with a specific focus on modules 2, 6 and 7.

F. Cheli, G. Diana, Advanced Dynamics of Mechanical Systems, Editore: Springer, Anno edizione: 2015, ISBN: 978-3319181998
L. Meirovitch, Fundamentals of Vibrations, Editore: Waveland, Anno edizione: 2010, ISBN: 978-1577666912
M. Petyt, Introduction to Finite Element Vibration Analysis, Editore: Cambridge University Press, Anno edizione: 2010, ISBN: 978-0521191609
Course handouts available on BeeP https://beep.metid.polimi.it/

The aim of the course is to enable students to master advanced engineering methods for investigating the dynamics of mechanical systems, with particular emphasis on the vibration of continuous structures and the stability analysis of systems subjected to nonlinear force fields. The course also provides an introduction to three-dimensional rigid-body dynamics and multibody system techniques. It covers theoretical models, discretisation techniques, and numerical solution methods based on the finite element method. Particular attention is given to practical examples and engineering applications, especially in the fields of structural dynamics and rotordynamics. Each topic is addressed from both theoretical and practical perspectives through lectures, classroom exercises, experimental laboratory sessions, and computer-based practical classes.

By the end of the course, students will have acquired the knowledge and skills defined in the learning objectives.
In terms of knowledge and understanding, students will develop an understanding of the modelling approaches used in the vibration analysis of continuous systems (DD1) and the ability to analyse vibration problems involving arbitrary combinations of geometrical configurations, structural properties, and boundary conditions (DD2). They will also understand the fundamental physical principles and mathematical methods underlying the stability analysis of systems subjected to nonlinear force fields (DD1). In addition, students will become familiar with the phenomena associated with two of the most significant issues in rotordynamics—namely bending critical speeds and oil-film instability—as well as the fundamental engineering approaches to rotor balancing and the dynamic modelling of fluid-lubricated journal bearings (DD1).
With regard to the application of knowledge and understanding, students will develop the ability to apply theoretical concepts to the analysis of vibration problems in complex mechanical systems and to evaluate alternative modelling approaches for real structures and machinery (DD2, DD3).
Through the experimental laboratory activities, students will learn how to process data obtained from dynamic tests and extract the modal parameters of vibrating structures, including natural frequencies, damping ratios, and mode shapes (DD2).
Finally, students will strengthen their communication skills by learning to summarise and present the results obtained during the laboratory activities effectively (DD4).

The course covers the following topics divided in modules as per the description below.
Module 1. Vibration analysis of discrete systems (a short summary)
Topic 1.1. Free and forced vibration of single-dof and multi-dof systems.
Topic 1.2. Modal superposition approach and principal coordinates formulation of the equations of motion.
Module 2. Non-linear force fields and stability analysis of mechanical systems
Topic 2.1. Single-dof systems. Preliminary definitions. Non-linear force fields. Computation of the equilibrium position and linearization of the equation of motion. Stability analysis. Static and dynamic instability.
Topic 2.2. Two-dof systems. Force field which is a non-linear function of the system position only. Computation of the equilibrium position and linearization of the equations of motion. Conservative and non-conservative force fields. Stability analysis. Static and flutter instability. Non-linear field of position and velocity dependent forces. Example: 2-dof airfoil under incompressible flow.
Topic 2.3. Overview of stability analysis for multi-dof systems.
Module 3. Vibration analysis of one-dimensional continuous systems
Topic 3.1. Transverse vibration of strings. Axial vibration of bars. Torsional vibration of circular shafts. Bending vibration of slender beams (Euler-Bernoulli formulation). Wave propagation and standing wave solutions. Free vibration: natural frequencies and vibration modes for different boundary conditions, transient response to assigned initial conditions. Forced vibration: steady-state response to harmonic input.
Topic 3.2. Modal superposition approach and principal coordinates formulation of the equations of motion. Frequency Response Function formulation. Forced response to distributed and moving loads.
Module 4. Experimental modal analysis
Topic 4.1. Overview of the test procedures and estimation of the Frequency Response Function.
Topic 4.2. Algorithms for frequency-domain modal parameters identification (multi-mode curve fitting method and simplified single-mode identification procedure).
Module 5. The finite element method in structural dynamics
Topic 5.1. General introduction to the finite element discretization of continuous systems. Detailed formulation of the 6-dof beam element for in-plane analysis: shape functions for axial and bending deformation, mass and stiffness matrices.
Topic 5.2. Procedure for developing the finite element model of a structure: global and local reference systems, work-equivalent nodal forces, matrix assembling, structural damping model, boundary conditions and matrix partition. Classical dynamic analysis: natural frequencies and vibration modes, frequency response.
Module 6. Three-dimensional rigid body dynamics
Topic 6.1. Kinetic energy and inertia tensor. 3D kinematics: rotation matrix and body angular speed formulation based on Cardano angles.
Topic 6.2. Practical examples.
Module 7. Introduction to Rotordynamics
Topic 7.1. Overview of the dynamic problems in rotating machinery. Balancing conditions and balancing procedures for a rigid rotor. Bending critical speeds, balancing conditions and balancing procedures for a flexible rotor.
Topic 7.2. Fluid lubricated journal bearings and oil film instability.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The exam consists of:
a written test;
an oral examination, including a discussion of the laboratory reports.
Students are required to submit short reports on the assignments completed during the experimental and computer laboratory sessions. Submission of the laboratory reports and successful completion of the written test are mandatory requirements for admission to the oral examination. Once these requirements have been met, the final grade is determined on the basis of the oral examination.
With reference to the expected learning outcomes:
the written test is intended to assess Module 3;
the discussion of the laboratory reports is intended to assess Modules 4 and 5;
the oral examination covers all the topics addressed during the course, with particular emphasis on Modules 2, 6, and 7.

G. Diana, F. Cheli, Advanced dynamics of mechanical systems, Editore: Springer, ISBN: 978-3319181998
L. Meirovitch, Fundamentals of Vibration, Editore: Waveland, Anno edizione: 2010, ISBN: 978-1577666912
S. S. Rao, Vibration of Continuous Systems, Editore: John Wiley & Sons Inc, Anno edizione: 2019, ISBN: 978-1119424147
M. Petyt, Introduction to Finite Element Vibration Analysis, Editore: Cambridge University Press, Anno edizione: 2010, ISBN: 978-0521191609

The course covers the analysis and design of control systems for dynamical systems, spanning both continuous and discrete time. The curriculum moves from foundational theory: stability, LTI systems, reachability/observability, transfer functions, frequency-domain methods (Bode, Nyquist), through classical controller design: PID, feedforward, cascade, sensitivity analysis, into more advanced topics: state-space control with pole placement and state observers, digital control (ZOH, sampling, discretization), motion control for servomechanisms, and finally discrete-event systems via Petri Nets and SFC/PLC programming.

Upon completing the course, students will have acquired the following knowledge and understanding:
They will be able to effectively represent the behavior of a linear and time-invariant dynamical system in both the time and frequency domains.
They will possess the skills to analyze the properties of dynamical systems and evaluate the potential for modification through the implementation of feedback.
They will be proficient in utilizing numerical tools to verify and validate the properties of a dynamical system, ensuring accurate analysis and assessment.
In terms of applying the acquired knowledge and understanding, students will be able to:
Derive a simple dynamical system that accurately represents the behavior of a real, albeit straightforward, dynamical system.
Propose an appropriate feedback control law for a given dynamical system, while satisfying given requirements in terms of performance and robustness.
Lastly, students will enhance their written communication skills by effectively linking the acquired theoretical knowledge to elaborate and articulate solutions to complex questions that may not have immediate application or known results.

Systems theory overview (continuous time systems): Fundamentals of continuous time dynamical systems. Solutions and equilibrium points. Lyapunov stability. LinearTime Invariant (LTI) systems: solutions and equilibrium points, stability analysis. Stability of equilibria of nonlinear systems. Structural properties of LTI systems: observability and controllability.
Frequency domain and design: LTI systems in the frequency domain. Frequency response, Nyquist and Bode diagrams. Introduction to control systems. Loop stability analysis. Loop transient and steady-state performance analysis. Control system design. Feedforward compensation. Cascaded control. Root locus for analysis and synthesis. Contour locus. PID regulators: standard form and anti-windup techniques.
Time domain design: Introduction to state space design. Full-state feedback. Observer design. Combining observer and control law. Introduction of a reference input. Adding a feedforward action.
Systems theory overview (discrete time systems): Introduction to discrete time systems. Linear Time Invariant (LTI) systems: solutions and equilibrium points, stability analysis. Stability of equilibria of nonlinear systems. LTI systems in the frequency domain.
Digital control systems: Introduction to digital control systems. Effects of sampling on the closed loop system. Indirect digital controller design: selecting the sampling rate and determining the transfer function of the digital regulator.
Motion control: Introduction to motion control problems. Models of an electric motor and of rigid and elastic transmissions. P/PI (position/velocity) control: tuning for rigid transmissions, using motor feedback.
Feedback DES and Petri Nets. lndirect and direct approach. Design of the supervisor. Transition refinement (Valette method). PLC: Programmable Logie Controller. SFC: fundamental elements.

Prova scritta obbligatoria, senza prove in itinere
Students will pass the course after having successfully taken a written examination of 2 hours (120 minutes) with open-books. The exam consists of 5/6 exercises. Final Grading to pass the course: students must successfully score as at least 18 points out of 32.

A.M. Zanchettin, Feedback Control Systems: Methods and Technologies for Mechatronic Engineers, ISBN: 9791221085259 https://re.public.polimi.it/handle/11311/1282765
Katsuhiko Ogata, Modern Control Engineering, Editore: Prentice Hall, ISBN: 978-0-13-615673-4
Karl Johan Astrom and Richard M. Murray, Feedback systems - An Introduction for Scientists and Engineers http://www.cds.caltech.edu/~murray/amwiki/index.php/Second_Edition

The course aims to provide the students with the necessary tools for the design and assessment of machine components for transportation systems, both under static and fatigue loading. The basics of mechanical design are upgraded in order to include advanced theory of elasticity applications (axisymmetrical bodies), stress analysis in plastic field, finite element analysis, design methods for static and fatigue loads (multiaxial and variable amplitude loading) and tools for assessing the influence of cracks/defects on static and fatigue strength. Theory of elasticity is extended in order to make it possible to evaluate stresses in typical mechanical components like pressure vessels, bolted joints, power transmission shafts, and validate finite element analyses.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to:
examine and perform the design and assessment of machine components for transportation systems subjected to static and fatigue loading.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
solve practical design applications by using different tools (analytical, numerical and experimental) and critically analyze the results.
Through activities of laboratory tests and of Finite Element Method applications, students will also acquire the skills to formulate a judgment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss the results.
Furthermore, through the assigned case studies, students will gain the ability to autonomously design and assess mechanical components subjected to static and fatigue loadings.

The course contents are delivered through lectures, practices, lab activities.
The course covers the following topics divided in modules as per the description below:
Module 1:
Structural analysis:
Statically undetermined systems: Force Method.
Axisymmetric problems: thin and thick cylinders loaded by internal and external pressure and centrifugal loads.
Stress analysis in plastic field: notched members, bending application over elastic limit.
Finite element modelling: basic formulation, definition of stiffness matrix, main shape functions, selection of element types, load and boundary conditions, evaluation of results, type of analysis (static, dynamic, etc.).
Module 2:
Strength of materials and assessment criteria:
Methods for fatigue design: Safe Life, Fail Safe, Damage Tolerance
Cyclic response of materials: high cycle fatigue, endurance limit, fatigue strength, modifying factors, stress concentration and notch sensitivity, multiaxial fatigue, variable amplitude loading, cumulative fatigue damage.
Linear Elastic Fracture Mechanics: energy approach (Griffith), stress intensity factor, K IC, fatigue crack propagation, plastic zone, overload effect.
Module 3:
Design of machine elements
Mechanical transmissions and Shaft. Materials, layout, design for stress, deflections, critical components, bearings.
Bolted joints. Stresses in bolted joints, design and assessment according with Standard.
Module 4:
Case studies:
Railway axle application
Pressure vessel
Hydraulic cylinder
Strcutural Health Monitoring theory and applications

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Students will pass the course after successfully take Written Test 1 composed by exercises and Written Test 2 with theoretical questions. Both the Tests are mandatory.
Written Test 1 with exercises
Via this exam, it will be possible to test students’ capability of application of the design tools to practical cases regarding machine components and systems.
Written Test 2 with theoretical questions
Via this exam, it will be possible to test students’ knowledge and understanding of the theoretical topics included in the program.
Final Grading
To pass the course, students must successfully pass the tests with a minimum mark for both.

N. E. Dowling, Mechanical Behavior of Materials, Editore: Prentice Hall, Anno edizione: 2013
J.E. Shigley et Al, Mechanical Engineering Design, Editore: McGraw-Hill, 9th Edition, Anno edizione: 2011
Lecture notes of the teacher available on Polimi WeBeep

The course aims to provide the students with the necessary tools for the design and assessment of machine element, both under static and fatigue loading. The basics of mechanical design are upgraded in order to include advanced theory of elasticity, design methods for static and fatigue loads (multiaxial and variable amplitude loading) and tools for assessing the influence of defects on static and fatigue strength. Theory of elasticity is extended to make it possible to assess the stress state in typical mechanical components like pressure vessels, welded joints, and shafts.
By means of finite element simulations, the students will acquire the skills for mechanical by means of a "design by analysis" approach.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
examine and perform the design and assessment of machine components subjected to static and fatigue loading by a "design by analysis approach".
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
solve practical design applications by using different tools (analytical, numerical and experimental) and critically assess the results.
Through activities of laboratory tests and of Finite Element Method applications, students will also acquire the skills to formulate an assessment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss the results.
Furthermore, through the assigned case studies, students will gain the ability to autonomously design and assess mechanical components subjected to static and fatigue loadings.
Finally, students will improve their communication skills, being able to write final technical reports.

The course contents are delivered through lectures, exercise courses, lab activities.
The course covers the following topics divided in modules as per the description below:
Module 1:
Structural analysis:
Statically undetermined systems: Force Method.
Euler's column and instability of compressed components;
Finite element modelling: basic formulation, definition of stiffness matrix, main shape functions, selection of element types, load and boundary conditions, evaluation of results;
Axisymmetric problems: disks, thin and thick cylinders loaded by internal and external pressure and centrifugal loads, elastic and elasto-plastic materials;
Structural behaviour of materials and components loaded beyond the elastic limit.
Module 2:
Strength of materials and assessment criteria:
Cyclic response of materials: high cycle fatigue, endurance limit, fatigue strength, multiaxial fatigue, variable amplitude loading, cumulative fatigue damage.
Linear Elastic Fracture Mechanics: energy approach (Griffith), stress intensity factor, K IC, strength assessment of crakced elements under static and cyclic loads;
Concepts of durability and life assessment in presence of flaws/defects.
Module 3:
Design of machine elements
Shaft and Shaft Components. Materials, layout, design for stress, deflections, components, fits;
Welding and the Design of Welded Structures. Stresses in Welded Joints, Strength of Welded Joints; fatigue;
Pressure vessels: design, assessment, acceptable defects.
Module 4:
Case studies:
Crane structure
Railway axle design and assessment;
Pressure vessel design and assessment;
Mechanical elements

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Students will pass the course after successfully take written test with exercises and written/oral test with theoretical questions. Both the tests are mandatory.
Written test with exercises
Via this exam, it will be possible to test students’ capability of application of the design tools to practical cases regarding machine components and systems.
Written/oral test with theoretical questions
Via this exam, it will be possible to test students’ knowledge and understanding of the theoretical topics included in the program.
Final Grading
To pass the course, students must successfully pass the tests with a minimum mark for both.

N. E. Dowling, Mechanical Behavior of Materials, Editore: Prentice Hall, Anno edizione: 2013
J.E. Shigley et al., Mechanical Engineering Design, Editore: Editore: McGraw-Hill, Anno edizione: 2011
A.C. Ugural and S. K. Fenster, Advanced Mechanics of Materials and Applied Elasticity https://webeep.polimi.it/
Lecture notes of the teacher available on Polimi WeBeep https://webeep.polimi.it/

The course aims to provide the students with the necessary tools for the design and assessment of machine components, both under static and fatigue loading. The basics of mechanical design are upgraded in order to include advanced theory of elasticity, finite element analysis, design methods for static and fatigue loads (multiaxial and variable amplitude loading) and tools for assessing the influence of defects on static and fatigue resistance. Theory of elasticity is extended in order to make it possible to evaluate stresses in typical mechanical components like pressure vessels, welded junctions, power transmission shafts and components containing cracks. The students will also apply finite element analyses to validate preliminary structural analyses and carry out a detailed structural assessment of some components.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to:
select the methods able to solve a statically indeterminate structure;
acquite the concept of instability of compressed structural members
understand the limitations of a given FE numerical model of structure component;
choose correctly the criteria for fatigue assessment of a mechanical component;
understand the concepts of flaw criticality and the material behaviour in presence of a singularity;
understand the main parameters that control the structural behaviour a component in presence of a flaw.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
sketch the structural scheme of a structure/component and how it should be modelled;
examine and perform assessment of machine components subjected to static and fatigue loading;
solve practical design applications by using different tools (analytical, numerical and experimental) and critically analyze the results;
determine the critical flaw size for a component subjected to static or fatigue loads;
fatigue assessment of a welded structure with the concepts of nominal stress.
Through activities of laboratory tests and of Finite Element Method applications, students will also acquire the skills to formulate a judgment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss the results.
Furthermore, through the assigned case studies, students will gain the ability to autonomously make appropriate choices for the design of mechanical components and assess their fitness when subjected to static and fatigue loadings.

The course contents are delivered through lectures, exercise courses, lab activities.
The course covers the following topics divided in modules as per the description below:
Module 1:
Structural analysis:
Statically undetermined systems: Force Method.
Euler's column and instability of compressed members;
Finite element modelling: basic formulation, definition of stiffness matrix, main shape functions, selection of element types, load and boundary conditions, evaluation of results;
Axisymmetric problems: thin and thick cylinders loaded by internal and external pressure and centrifugal loads;
Elastic solutions for notches and cracks.
Module 2:
Strength of materials and assessment criteria:
Cyclic response of materials: high cycle fatigue, endurance limit, fatigue strength, multiaxial fatigue, variable amplitude loading, cumulative fatigue damage.
Linear Elastic Fracture Mechanics: energy approach (Griffith), stress intensity factor, K IC, assessment under static loads;
Concepts of durability and life assessment in presence of flaws/defects.
Module 3:
Design of machine elements
Shaft and Shaft Components. Materials, layout, design for stress, deflections, components, fits;
Welding and the Design of Welded Structures. Stresses in Welded Joints, Strength of Welded Joints; fatigue;
Pressure vessels: design verification, assessment, acceptable defects.
Module 4:
Case studies:
Crane structure
Railway axle design and assessment;
Pressure vessel design and assessment;
Articulated welded boom.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Students will pass the course after successfully take written test with exercises and written/oral test with theoretical questions. Both the tests are mandatory.
Written test with exercises
Via this exam, it will be possible to test students’ capability of application of the design tools to practical cases regarding machine components and systems.
Written/oral test with theoretical questions
Via this exam, it will be possible to test students’ knowledge and understanding of the theoretical topics included in the program.
Final Grading
To pass the course, students must successfully pass the tests with a minimum mark for both.

Lecture Notes on WeBeep webeep.polimi.it
A.C. Ugural and S.K. Fenster, Advanced Mechanics of Materials and Applied Elasticity, Editore: Prentice Hall, Anno edizione: 2003
N.E. Dowling, Mechanical Behavior of Materials, Editore: Prentice Hall, Anno edizione: 2013 https://resolver.vitalsource.com/9781292279374
Note: Available as an e-book
J.E. Shigley et al., Mechanical Engineering Design, Editore: McGraw Hill, Anno edizione: 2011
G.R. Liu, S.S. Quek, The finite Element Method - A practical course, Editore: Buttherworth Heinemann, Anno edizione: 2003
Note: Available as an e-book

The objective of this course is to lead the students to master the most relevant advanced manufacturing processes, with special reference to processes with growing industrial importance and applied in different sectors, including automotive, aerospace, biomedical and energy. Shaping, joining, additive and subtractive manufacturing processes will be addressed, with a focus on the most innovative issues and applications. Industry 4.0 digitalization tools and specific approaches to green and sustainable manufacturing and production data management will be explained through relevant examples. The course starts from the classification of advanced manufacturing processes, based on their main physical mechanisms and for each process presents the basic principles, the most relevant industrial solutions, the machines, and the main applications.
Exercises, Lab Works, visits to laboratories, companies and trade fairs integrate the program. Lab Works represent an innovative approach to understand and solve typical manufacturing issues with a hands-on approach.
Some of the course topics involve innovative didactic tools as flipped classrooms. Some didactic materials are made available for an asynchronous use and then a dedicated discussion session takes place during the lectures.

By the end of the course, students learn contents and practices according to what defined in the leaning objectives. In terms of acquired knowledge and understanding, by the end of the course students are able, for each manufacturing process, to:
define and describe (by using graphs and drawings) the process basics, its main capabilities, processable materials, achievable geometries and tolerances, productivity performances, typical systems, and machines.
identify the appropriate manufacturing processes for a given product, considering technical, economic and environmental issues.
Concerning the ability to apply the acquired knowledge and understanding, by the end of the course students can:
examine the sensitivity of the processes to the main process variables, by applying analytical and empirical models (numerical exercises are helpful to this purpose).
select the manufacturing strategy and process parameters to solve a specific industrial need.
calculate the representative quantities of the selected process applied to a specific manufacturing case (e.g. force, power, material removal rate, surface finish, etc.)
Through the mandatory Lab Work, the students divided in groups acquire the skills concerning activity planning, problem setting, problem solving, and analytical thinking. The lab activities allow the students to apply the acquired theoretical knowledge to autonomously assess and solve manufacturing tasks. In this way, they acquire applied knowledge of advanced manufacturing processes and how to communicate the results of a manufacturing activity.

The course contents are delivered through lectures, exercise classes and lab activities. The course covers the following topics as per the description below:
Topic 1. Advanced machining. Evolution of traditional machining in terms of advanced work (e.g. aerospace applications) and tool (e.g. diamond coated or ceramic tools) materials, cutting fluids (e.g. cryogenic machining), simulation and control (digital twin), accuracy (e.g. ultra-precision machining).
Topic 2. Thermal modelling. Review of fundamentals of heat transfer. The heat equation and its practical applications in thermal machining and heat treatments.
Topic 3. Laser beam processing. Fundamentals of the physics of lasers: stimulated emission, properties of the laser beam. The technology of laser generation and transmission. Interaction mechanisms between the laser beam and the engineering materials. Laser beam machining by fusion, melt and blow, vaporization and ablation. Laser beam (conduction and keyhole) welding. Other applications of lasers. Empirical and numerical modeling.
Topic 4. Waterjet processing. Introduction to pure and abrasive waterjet machining. The technology of WJ/AWJ systems: pumps and pressure intensifiers, the cutting head and its components. Modelling the jet formation and the interaction mechanisms between the jet and the engineering materials. Process parameters influence in AWJ machining and cutting quality. Empirical modelling and cost optimization of waterjet machining.
Topic 5. Flexible forming processes. Hydroforming of tubes: systems, loading curves, forming mechanisms and main applications. Fluid and flexible forming of sheets and tubes: systems and applications.
Topic 6. Ultrasonic processing. The technology of vibrations generation: magnetostrictive and piezoelectric transducers, the sonotrode. Interaction mechanisms between the tool, the abrasive slurry and fragile materials. Main applications of the process. The process of ultrasonic welding: process parameters and applications.
Topic 7. Electro discharge machining (EDM). The technology of EDM (plunge and wire). The mechanism of material removal by spark erosion. Process parameters influence and cutting quality. Applications.
Topic 8. Plasma arc processing. Properties of plasmas. The technology of plasma beam generation: historical evolutions of plasma torches. Process parameters influence and cutting quality. Other applications of plasmas.
Topic 9. Introduction to additive manufacturing processes. Overview of the main processes/systems for metals (SLM, EBM, etc.). Technological and economical comparison to conventional manufacturing. Complementary role of AM as a rapid tooling technique.
As said for the course goals, Industry 4.0 digitalization tools and specific approaches to green and sustainable manufacturing and production data management will be explained through relevant examples in relation to the different studied processes. Examples will clearly point out how processes and models explained in the course allow professionals to solve challenging manufacturing cases in view of a more efficient, digital and sustainable production.
Some of the topics involve innovative didactic tools as flipped classrooms. Some didactic materials are made available for an asynchronous use and then a dedicated discussion session will take place during the lectures.
The Lab Work will ask the student to use and apply the knowledge acquired through lectures and exercises on one or two processes to solve a simple manufacturing case on a real machine. Students will be divided in groups to this purpose.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Students pass the course after successfully taking a mandatory written test, where they must solve some numerical problems and answer some theoretical questions. The written test is carried out on paper in a closed-book fashion: students can only use a cheat sheet provided by the professor. The only allowed electronic device is a standard calculator (no scientific calculators allowed). Both the written test and the oral exam are attended in presence.
Via this written test, it is possible to test students’ acquired knowledge and understanding of the course basics and its application based on analytical models. The test is composed of some problems that must be solved by giving numerical answers and by multiple-choice theoretical questions to verify the basics. The written test is successful if its grade Gw > 17/30.
If Gw > 17/30, the written test is followed by a mandatory oral discussion, otherwise the student fails the exam and goes to the next call.
Via the oral exam, it is possible to test students’ ability to autonomously form judgements and the ability to communicate learnt contents. Students have to answer two main questions formulated by the teacher on two manufacturing processes. The oral exam gives a grade Go ≥ 18/30. If Go < 18/30, the student fails the exam and goes to the next call. The written test grade is canceled in this case and the students has to retake the written test.
The final grade Gf is calculated as a weighted average of Gw and Go. The mandatory Lab Work can yield up to 2 additional points (Lw). Since the Lab Work is mandatory, every student is required to do it to pass the exam. The Lab Work must be submitted at the end of the course and before the first exam call according to the date declared by the professor during the course. If the Lab Work is not sufficient, the group cannot attend the first exam call and receives indications by the professor on how to fix it.
In case of absence from certain laboratory sessions, the student can retrieve the related material through the other group colleagues and/or via WeBeep. The professor considers the number of absences from the laboratories and, after consulting all group members, will decide whether to consider the requirement for the repeatedly absent student to complete the Lab Work satisfied. Once assessed that the requirement is satisfied, the Lab Work grade of the student with some absences is scaled according to the percentage of attended lab activities.
The final grading formula is: Gf = 0.25Gw + 0.75Go + Lw.

Lecture notes https://webeep.polimi.it/login/index.php
Note: WeBeep course website
Steen, Laser Material Processing, Editore: Springer, Anno edizione: 2003
Elman C. Jameson, Electrical Discharge Machining, Editore: SME
Carl Sommer, Non-Traditional Machining Handbook, Editore: Advance Publishing (TX)
Ian Gibson, David Rosen, Brent Stucker, Additive Manufacturing Technologies, Editore: Springer
Michele Monno, Barbara Previtali, Matteo Strano, Tecnologia meccanica. Le lavorazioni non convenzionali, Editore: CittàStudi

The objective of the course Advanced Manufacturing Processes B (AMP B) is to enable students to understand, analyse and select advanced processing technologies of growing industrial importance across sectors such as automotive, aerospace, energy and advanced mechanical engineering.
The course presents key enabling technologies that are transforming the contemporary manufacturing landscape by introducing innovative approaches to subtractive processing, joining, surface modification and material shaping.
Starting from a general classification of Advanced Manufacturing Processes, the course examines the fundamental physical mechanisms and operating principles of the selected technologies. Particular attention is devoted to:
process capabilities and limitations;
processable materials and achievable product characteristics;
main operating parameters and their influence on process performance;
industrial equipment, machine tools and production-system configurations;
monitoring, control and quality-assurance approaches;
representative industrial applications.
The course combines theoretical lectures with numerical and practical exercises. Students will apply analytical, empirical and numerical methods to investigate process behaviour, estimate manufacturing performance and compare alternative technological solutions.
Laboratory and project activities will allow students to address industrially relevant manufacturing challenges. These activities may include the use of artificial intelligence tools, data-analysis methods and other advanced engineering techniques to support process analysis, optimisation and decision-making.
The course may also be complemented by industrial case studies, guest lectures and contributions from experts working in advanced manufacturing sectors.

By the end of the course, students will understand the fundamental principles, technological characteristics and industrial relevance of advanced manufacturing processes, as well as the relationships between process mechanisms, operating conditions, material behaviour and product quality (Knowledge and Understanding Dd1)
Students will be able to apply engineering methods, analytical models and experimental evidence to analyse manufacturing processes, estimate their performance and propose suitable technological solutions for a given product or industrial application (Applying Knowledge and Understanding DdD2))
Students will be able to compare alternative manufacturing technologies and make technically justified decisions by considering process capabilities, quality, productivity, economic feasibility, resource efficiency and environmental implications (Making Judgements DdD3).
Students will be able to describe manufacturing technologies and discuss process-selection and process-analysis problems using appropriate engineering terminology, quantitative information and logically structured technical arguments (Communication Skills DdD4).
Students will be able to independently approach unfamiliar and emerging manufacturing technologies, identify the knowledge and information required for their analysis and transfer the methodologies acquired during the course to new industrial problems (Learning Skills DdD5).
The course provides students with a broad and transferable methodology for analysing Advanced Manufacturing Processes beyond the specific technologies covered in the syllabus.
Through the lab or project works, where students will work in groups, they will acquire the skills concerning problem setting, problem solving, and analytical thinking. These activities will allow to apply the theoretical knowledge to solve issues acquiring applied knowledge of advanced manufacturing processes. Furthermore, through the assigned group activities, students will gain the ability to autonomously plan their group work and select the most suitable strategies and approaches of their work.
Finally, students will improve their communication skills, because they will have to practice for the oral exam.

The course contents are delivered through lectures, exercise classes and laboratory or project activities.
The course covers the following topics:
laser-based manufacturing processes;
electrical discharge machining;
arc- and plasma-based processing;
waterjet cutting;
analytical modelling of advanced manufacturing processes
For each technology, the course will address the underlying process mechanisms, the influence of the main operating parameters, process capabilities and limitations, relevant production equipment, achievable product characteristics and representative industrial applications.
The laboratory or project activities will require students to address a state-of-the-art challenge related to the manufacturing sector. Students will analyse the assigned problem and develop a suitable solution with the support of engineering models, experimental methods, artificial intelligence tools, data-analysis techniques or other advanced approaches.
The course contents may be complemented by emerging technological topics, industrial case studies and guest lectures delivered by experts from manufacturing companies.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course assessment consists of a mandatory oral examination.
The oral examination mark, (Mo), is expressed on a scale of 30 points.
The oral examination consists of a technical discussion covering both the theoretical contents and the practical exercises presented during the course. Before the oral discussion, students may be required to complete a written assessment that will then be discussed during the oral exam.
The assessment will consider the student’s ability to demonstrate:
Knowledge and understanding of the fundamental mechanisms, technological characteristics and industrial relevance of advanced manufacturing processes;
Application of knowledge and understanding through the use of analytical, numerical and empirical methods to solve process-analysis problems and evaluate manufacturing performance;
Making judgements by comparing alternative technologies and justifying process-selection decisions based on technical, economic, environmental and operational criteria;
Communication skills in presenting technical concepts and engineering arguments with clarity, precision and appropriate terminology;
Learning skills through the ability to transfer acquired methodologies to unfamiliar manufacturing problems and emerging technologies.
Students may also participate in an optional laboratory project, which can provide an additional mark, (Ml), of up to 3 points.
The laboratory-project assessment will consider the ability to formulate and analyse an industrially relevant problem, select appropriate investigative methods, interpret the obtained results, work effectively within a group and communicate the project outcomes through a structured technical presentation.
The final mark, (Mf), is calculated as follows:
Mf = Mo + Ml

The objective of the ADVANCED MANUFACTURING PROCESSES (AMP) class is to lead the students to master the most relevant advanced processing technologies, with special reference to processes with growing industrial importance and applied in different sectors, including automotive, aerospace, energy, etc. Additive, joining, shaping and subtractive manufacturing processes will be addressed, with a focus on the most innovative issues and at the key enabling technologies.
The course starts from the classification of advanced machining processes, based on the elementary mechanisms and for each process presents the basic principles, the most relevant industrial solutions, the machines and the main applications. Numerical and PC-based exercises, semester projects, visits to laboratories, companies and trade fairs integrate the program.

By the end of the course, students will learn theoretical contents and industrial practices.
In terms of acquired knowledge and understanding, for each manufacturing process students will be able to:
define and describe their basics, the main process capabilities, processable materials, the achievable geometries and tolerances, the productivity performances, the typical systems and machines.
identify the appropriate technological processes for a given product, considering technical, economic and environmental issues.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
examine the sensitivity of the processes to the main process variables, by applying numerical, analytical, and empirical models.
Through reading and writing the semester project, they will familiarize with the scientific research, they will have a clear understanding of the state of the art and they will learn how to communicate the results of research activities
Through the lab or project works, where students will work in groups, they will acquire the skills concerning problem setting, problem solving, and analytical thinking. These activities will allow to apply the theoretical knowledge to solve issues acquiring applied knowledge of advanced manufacturing processes. Furthermore, through the assigned group activities, students will gain the ability to autonomously plan their group work and select the most suitable strategies and approaches of their work.
Finally, students will improve their communication skills, because they will have to practice for the oral exam.

The course contents are delivered through lectures, exercise classes and lab/project activities.
The course covers the following topics divided in modules as per the description below. The number of hours and credits for each topic will be modulated according to the Track the course is offered to.
Mechanical processes
Processes involve water jetting, flexible forming, ultrasonic, and advanced milling techniques.
Thermal processes
Processes involve laser based manufacturing, plasma, electric discharge machining.
Additive manufacturing
An introduction to some of the most widely used additive manufacturing techniques.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully take a mandatory written test, where they will have to solve some numerical problems and to answer some theoretical questions.
After the written test, a mandatory oral discussion will follow, allowing to assign the final grades.
[ Written test ]
Via this test, it will be possible to test students’ acquired knowledge and understanding of the course basics and its application based on numerical models. The test will be composed of some problems that must be solved by giving numerical answers and by multiple-choice questions to verify the basics.
[ Oral exam ]
Via this exam, it will be possible to test students’ ability to independently form judgements and the ability to communicate learnt contents. The students will have to thoroughly describe one manufacturing technology, answering specific questions formulated by the teacher.
Final Grading
To pass the course, students must successfully pass the written test, with a grade Gw≥17/30. Then, they will receive a grade Go≥18/30 of the oral exam. The final grade will be calculated as a weighted average of Gw and Go. The lab/project work can yield up to 3 additional points.

Lecture notes Beep course website
Steen, Laser Material Processing, Editore: springer, Anno edizione: 2003
Elman, C. Jameson, Electrical Discharge Machining
Carl Sommer, Non-Traditional Machining Handbook, Editore: Advance Publishing(TX).
Gibson, Ian, Rosen, David W., Additive Manufacturing Technologies, Editore: Springer
Michele Monno, Barbara Previtali, Matteo Strano, Tecnologia meccanica. Le lavorazioni non convenzionali, Editore: CittàStudi, ISBN: 978-8825173772

The goal of the course is to enable students to apply the metallurgical knowledge in all those engineering fields that require full knowledge on materials and damage phenomena.
During the course the main metallic alloys for engineering applications will be covered, referring to their microstructure, heat treatments and manufacturing processes. In particular, the properties of the main steel grades, special alloy steels, stainless and tool steels are described. Non-ferrous alloys are also covered, considering Aluminium, Magnesium, Nickel and Titanium alloys. Basic principles of composite materials will be presented.
The teaching activity is also aimed at facing damage phenomena occurring during service of mechanical parts such as fatigue, creep, brittleness, wear, corrosion, linking them to the metallurgical features and to specific manufacturing processes.
Sessions of lab activities will be organized with the aim of practically testing the theoretical knowledge about the behavior of materials. By working in groups, students will acquire the skills of problem setting, problem solving, analytical thinking. By flipped class students will acquire the skills of public speaking, summarizing and focusing.

After attending the course, the student will:
have a wide knowledge about the scenario of structural alloys that can be used for the design of mechanical components;
know how the properties of these alloys can be modified and influenced by the manufacturing processes;
know how the service condition may change the performance of the different classes of alloys;
be able to critically select the proper material for any specific design application;
have basic understanding about the cause of failure and about possible solutions.

Recall about the principles of physical and basic metallurgy (crystal structure, dislocations, strenthening mechanism, textures).
Damage phenomena and service conditions. Corrosion, wear, creep, fatigue, brittleness and embrittlement phenomena. Combination of such phenomena. Short introduction to failure analysis.
Production processes. Fundamental aspects of the production and transformation process of metals.
Steels for structural applications. Fundamentals about the steel microstructure, the effects of detrimental chemical elements and of the main alloying elements. Low carbon steels for structural application, high strength engineering steels (quenched and tempered steel, steel for carburizing, steels for nitriding, steel for surface quenching).
Steels for special applications. Stainless steels (austenitic, ferritic, martensitic, duplex, precipitation hardened), tool steels, bearing steels, advanced high strength steels (DP, CP, TRIP/TWIP), high temperature steels, steels for cryogenic applications.
Cast irons and non-ferrous alloys. Metallurgy and applications of cast irons, Aluminium, Magnesium, Nickel and Titanium alloys; properties, microstructure and related heat treatments.

Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
Students will pass the course after successfully submit technical reports about the labs experiences (Hall-Petch, Charpy, corrosion, hardening) and oral presentations (wear damages, engine steels, composite material substitution). The technical papers and the presentations are done in working groups.
Via these tasks, it will be possible to test students’ acquired knowledge and understanding and its application the ability to independently judgements, the ability to communicate learnt contents and the ability to use the acquired knowledge for problem solving.
Final Grading: o pass the course, students must successfully complete the tasks. The tasks will be marked according to: relevance to the assignment, subject completeness, team organization, personal organization and argumentation and lexicon precision. To modify the evaluation an oral examination is possible.

Reza Abbaschian, Robert E. Reed-Hill, Physical Metallurgy Principles, Editore: Cengage Learning Publisher, Anno edizione: 2009
D.R. Askeland,, The Science and Engineering of Materials, Editore: Chapman and Hall
William D. Callister,Jr, Materials Science and Engineering, Editore: Wiley
Metals Hanbook Collection, Editore: ASM

The course aims at providing a knowledge aware about the behaviour of advanced materials for the design and construction of mechanical and structural systems as a function of physical, mechanical and electrochemical properties featuring such materials. The topics covered in the course deepen the features and the performances of advanced materials in relation to operating conditions and related damage phenomena (brittleness, fatigue, corrosion, high temperature oxidation, creep, wear). These aims will be achieved also by learning the use of digital tools to perform computational trials that simulate the behaviour of advanced materials in the mechanical and structural systems in different working conditions.

Upon successful completion of the exam, the student will be able to:
DdD 1 & 2 – Knowledge and understanding / Applying knowledge and understanding
design mechanical and structural components and systems consciously, applying acquired knowledge to solve assigned problems;
improve the design of a mechanical or structural system as a function of varying operating conditions, taking into account mechanical and environmental constraints;
DdD 3 & 5 – Making judgements / Learning skills
critically analyze different design solutions for mechanical and structural components or systems, proposing modifications to optimize performance under multiple scenarios;
after guided activities, autonomously reorganize, plan, and design reliable and safe mechanical components or systems;
DdD 4 – Communication skills
compose a systematic technical report that includes context description, project goals, discussion, conclusions, and recommendations;
present the results of the analysis clearly and synthetically to an audience, demonstrating mastery of technical communication.

1st topic: strength, toughness, fatigue resiatnce and anisotropy featuring the materials and the design of crisytallographic textures (mild steels, deep drawing steels, Advanced High Strength Steels (AHSS), aluminium alloys, advanced ceramics);
2nd topic: corrosion phenomena and protection of advanced materials (weathering steels, zinc and tin plating, steels for pipelines, stainless steels -austenitic, ferritic, duplex and maraging grades-, metallic glasses)
3rd topic: ligth weight design by advanced materials (Advanced High Strength Steels, ductile cast iron, austempered pig iron, aluminium alloys belonging to 2xxx, 4xxx, 5xxx, 6xxx, 7xxx, Magnesium Alloys, graphene, graphite and fiber carbon composite, beta and alpha-beta titanium grades, composite reinforce by carbon fibers)
4rd topic: creep resistance and corrosion by high temperature oxidation (Nickel and Cobalt superalloys, high carbon stainless steels, advanced cast irons, tool steels, alpha titanium alloys, high entropy alloys, metallic glasses);
5th topic: management of the wear phenomenon.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
Valutazione continua obbligatoria
Periodic oral examination and final technical discussion about the computational trials performed during the course.

Ajit Behera, Advanced Materials An Introduction to Modern Materials Science, Editore: Springer, Anno edizione: 2022, ISBN: 978-3-030-80358-2

Il corso fornisce competenze avanzate sulle tecniche di misura per applicazioni in propulsione e generazione di potenza, con focus su elaborazione segnali e misure di flusso. Gli studenti apprenderanno metodi di analisi nel dominio del tempo e della frequenza, diagnostica di sistemi meccanici e gestione di sensori per misure di portata e velocità. Il corso prevede lezioni, attività di laboratorio e progetti pratici con utilizzo di MATLAB e LabVIEW. La valutazione avviene tramite test scritto e, opzionalmente, un progetto o una prova orale.

The course aims at developing the competences necessary to apply the basic Project Management techniques and tools to a complex project. In increasingly volatile markets, project management needs special attention including change-enabling methodologies into traditional processes. Consequently, the course deals with the traditional (or plan driven) processes of project planning and control (scope, time, resource, cost, quality, risk, cash flow, stakeholder, communication...) and with Agile (or change-driven) project management processes that facilitate the management of project scope changes. The waterfall and agile tools and techniques seen in class will be practiced with two approach:

• the analysis of case studies of projects carried out in traditional sectors (Oil & Gas, plant engineering, nuclear, energy).
• the participation to an hackathon where each groups’ project work will be presented to an external commission
  The course fits into the overall program curriculum pursuing some of the defined general goals. In particular, the course contributes to the development of the following capabilities:
  Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
  Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
  Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members
  The course is organized developing both the traditional PM approach and the Agile one. In particolar the agile approach is a stand alone course named Agile Project Management.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
Use properly Plan Driven & Change Driven Project Management language, understanding management processes involved in a project, understanding interdependencies between operational and managerial processes, capability to correctly apply techniques and tools available in project management.
In terms of acquired knowledge and understanding, students will be able to d evelope with both traditional and agile methodologies plan for managing different types of complex project involving the main knowledge areas of project management (scope of work, time, progress, cost, resources, cash flow, risk, etc.) and to e stimate project performance and evaluate recovery plan during project execution.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to select the methodology (plan driven or agile) that best suit different types of projects.
Through the project work developement students will also acquire the skills to formulate a judgment, on implementing an effective two-way communication: with colleagues for the development of the project work, with the managers of the companies involved in the competition for the participation to the hackathon.
Finally, students will improve their communication skills, being able to communicate both with other students during the project work development and with professionals during the final hackathon.

Traditional Project Management
Project and Project Management: Repetitive and non-repetitive processes. Project: features, types, success factors, performance indicators, stakeholders. Project life cycle. Operational, managerial and organizational processes. Project, program and portfolio management. International Standards. Project Management Body of Knowledge. Project Management System.
Project Governance: Projects, programs, and portfolios; types of governance structures; roles of governance in project management.
Engineering & Contracting: Extended project life cycle: marketing, competitive bidding, contract and contract management, operation. Project start up. Project execution: basic engineering, detailed engineering, procurement, construction, commissioning and testing. Interdependeces between operational processes. Project organization.
Stakeholder management: identification, classification and management.
Scope management: Scope of work planning and control. Work Breakdown Structure. Rules and criteria for building the project WBS. Work package. Standardization of WP.
Time management: Network analysis, early and late schedule, total float. Activity duration and resource allocation. Resource scheduling. Scheduling under uncertainty. PERT approach. Critical chain approach. Schedule control.
Cost management: cost classification, cost estimating, cost baselining, cost control. Project cash flow. Project balance.
Earned Value Management: integrated control of project time and cost. Project performance indicators. Earned Value. Estimate to complete. Control process. Final performance of the project.
Risk management: Risk definition and classification. Risk management processes: identification of threats and opportunities, risk assessment and identification of response actions. Quantitative analysis of project residual risk. Simulation. Size of the contingency reserve. Project robustness and flexibility.
Agile Project Management:
Managing projects with Agile methods: Project anticipation and adaptability to change; traditional, iterative, incremental and agile project’s lifecycles. Differences between agile and waterfall methods, need to develop new process to cope with change and instability, the context of application of Agile tools & Techniques.
The Agile Manifesto: History, origins and field of application.
Individuals and interactions over processes and tools: principles of effective communication and iteration.
Working software over comprehensive documentation: the key roles of iteration and prototyping activities.
Customer collaboration over contract negotiation: structuring an effective collaboration with client.
Responding to change over following a plan: Including change in the project planning phase.
The 12 principles of managing project in an Agile field: Definition and analysis of the 12 main values that are the basis of agile.
Working with Agile: The Agile Project management lifecycle, the triple constraints triangle.
Reviewing the main Agile Frameworks: Lean software development: The seven principles of software development
Extreme Programming: Values, principles and practices
Working in Scrum: Vision; Product Roadmap; Release planning; Sprint Planning; Daily Scrum; Sprint Review; Sprint Retrospective.
Agile Earned Value: measuring project progress in an agile context
Tool & techniques of Agile Project Management: communication area, Planning monitoring and control area, agile estimation, interpersonal skills, risk management, value based prioritization.
The role of the scrum master: principle of servant leadership in action.
TIMETABLE: all the educational activities for Agile Project Management (5 CFU) are held on FRIDAY from 14:15 to 18:15

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Besides lectures and practical exercises, the course is based on the development by student teams of a plan of a simple project (including scope, time, resource, progress, and cost management). The completion of the team assignment is a prerequisite (just for 10 etc participans, for all the others is volunteer) for accessing the final test and will it be presented in a final Hackathon where companies’ managers are involved. Participation in class is strongly recommended and positively evaluated.
The final test includes both a written and an oral part, having the same weight for the final mark. The written test concerns the solution of some quantitative exercises seen during exercise sessions. Oral exam is about the subjects introduced during the lectures.

Mauro Mancini, Costanza Mariani, Quantitative tools for a smart project management, Editore: Esculapio, Anno edizione: 2021, ISBN: 9788893852548
Rory Burke, Fundamentals of Project Management, Editore: Burke Publishing, Anno edizione: 2017, ISBN: 9780994149213

The course educates students to become professional data scientits by reviewing several statistical models, methods and algortihms aimed at the statistical analysis of mutivariate data. The aim is twofold: first, to provide future data scientists with the mathematical knowledge and understanding necessary for making proper judgments when selecting appropriate methods and algorithms, producing sensible interpretations of the results generated by their application and grasping their strenghts and weaknesses and, second, to enhace the students ability in applying the knowledge and understanding of the statistical approach to data analysis by emphasizing real life and engineering applications where statistical methods and modern computer packages permit to elicit information from multivariate data through complex statistical analyses.
The course is offered in two versions, for 8 CFU and 10 CFU respectively. Both versions are named Applied Statistics and are described in the present document. In the 8 CFU version, the course will cover classical topics of Multivariate Data Analysis (e.g.: dimension reduction, inference for regression, supervised and unsupervised classification) with overtures to the modern treatment of multiple inference (FDR) or to novel statistical learning methods and algorithms (e.g. support vector machines, ensemble leraning methods). To these contents, the 10 CFU version of the course adds three modules of Advances in Statistical Learning, leveraging on seminars offered by experts of the fields (e.g.: Linear Mixed Models, Functional Data Analysis, Spatial Statistics).
Through an extensive recourse to blendend learning and flipped classroom innovative teaching, both during the lectures and the lab sessions, the course will enahace the students ability in autonomous learning; this will also be accomplished by perusing new teaching media like the MOOC on Statistical Learning by Hastie and Tibshirani referenced in the Bibliography.
Particular emphasis is given to the devolopment of a responsible and efficient attitude toward work in a multidisciplinary environment where the data scientist collaborates on a peer-to-peer basis with other engineers and scientists for the modeling and understanding of complex phenomena of scientific or industrial interest. Hence, the course requires team work on real data statistical analyses, either in interaction with industrial partners of the statistical research group of the Department of Mathematics or in collaboration with scientists and engineers demanding a data-driven approach to the solution of their research problem. Work-in-progress of the teams will be periodically discussed in class, drawing attention not only on the appropriatness of the statistical methods and algorithms, but also on the communication skills of the teams when informing an audience of peers.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Design models and utilize information from experimental data for inferential estimation, verification and adaptation of the models and for their heuristic developments;
Provide the statistical interpretation and simulation of scenarios for the treatment of data in situations of high complexity;
Use R for the analysis and treatment of complex data.

Both versions of the course have the following common learning goals:

• At the end of the course students are expected to be able to design - and run with R - data analyses aimed at: reducing the dimensionality of a dataset, solving a classification problem, both supervised or unsupervised, making multiple inference on multiple mean vectors or their components, choosing the most appropriate regression model and fitting it while making inference on its components, handling classical (OLS) or more modern approaches to model building and selection (ridge regression and lasso). Leveraging on their engineering forma mentis and on the skills in data analysis acquired in the course, students are expected to be able to evaluate the practical and statistical significance of the final result of their data analysis, to quantify its uncertainty analytically or through simulation, e.g. by cross-validation, and to diagnose its potential shortcomings, either when used to provide an empirical explanation of the industrial or scientific problem under study or when the main goal of the analysis is to formulate predictions.
• To prepare for responsible and efficient interactions in a working environment, every student is required to take part in a real data analysis project developed by an independently formed team of 3-5 members. The work in progress of the projects will be collectively discussed during general meetings scheduled along the course; final analyses and results will be presented in a workshop which will take place at the end of the course.
• Students are expected to be able to communicate and transfer the results and interpretations of their data analysis to a wider audience of experts, using effective graphical or analytical means, suitable for the problem under study, the findings of the analysis and, finally, the audience.
  Moreover, the students of the 10 CFU version of the course are expected to have a basic understanding of the more complex issues - and the methods and algorithms developed to solve them - characterizing the statistical analysis of data when heterogeneity and temporal or spatial dependence is of importance or when data do not belong to the finite dimensional Euclidean setting considered in the classical Multivariate Data Analysis framework, like in the case of functional data.

The topics covered by the 8 CFU version of the course are the following:
1) The essence of statistical learning. The regression function: local methods and the curse of dimensionality. Structured models. Test error, training error and expected test error. The bias variance tradeoff. Generalization error and Expected generalization error. Bias-variance tradeoff.
2) Exploring a multivariate dataset: descriptive statistics and graphical displays. The geometry of a multivariate sample. Generalized Variance. The metric induced by the covariance matrix.
3) Data representation and dimensional reduction: the analysis of the covariance structure, principal component analysis. Independent component analysis.
4) Inferences about a mean vector: Hotelling T^2 test. Confidence regions and simultaneous comparisons of component means. The Bonferroni method for multiple comparisons. Familywise Error Rate and False Discovery Rate. Comparisons of several multivariate means. ANOVA and MANOVA. Inference for Linear Models. Beyond Ordinary Least Squares: ridge regression, lasso, regularized least Squares. Cross-validation and model selection. Ensemble learning methods: random forests for regression and classification.
5) Discrimination, classification, clustering. Statistical classification: model, misclassification costs and prior probability. Bayesian supervised classification and the Fisher approach to discriminant analysis. Alternative approaches to classification: support vector machines and CARTs. Similarity measures. Unsupervised classification; hierarchical and nonhierarchical methods. Multidimensional scaling.
In the 10 CFU version of the course, the above topics are complemented with the following three modules of Advances in Statistical Learning:
6) Linear Mixed Models. Enriching the covariance structure of a linear model to take into account heteroschedasticity and dependence, random effects, hierarchical grouping structures, longitudinal data.
7) Functional Data Analysis. Data smoothing, dimensional reduction and representation. Functional principal component analysis. Data registration: phase and amplitude variability. Classification of functional data.
8) Spatial Statistics. Random fields, variogram models and variogram fitting. Spatial prediction and Kriging, Functional data with spatial dependence.
In both versions of the course, methods and algorithms will be illustrated in the lab sessions through applications to real data sets; analyses will be performed in R, an opensource package for the statistical analysis downloadable at www.r-project.org.
Through the course, students are required to work in team on a real data analysis project whose progress will be shown periodically to the class.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists of two parts:
(a) A written exam. The written exam consists of questions (theory and practice) and of a few data analysis problems to be individually solved with R; two problems for the students following the 8 CFU versions of the course, three problems - with extra time - for those registered in the 10 CFU version. For the students taking the course for 10 CFU, the extra problem will be related to the three advanced topics treated in the modules characterizing their additional 2 CFU; working on this problem is mandatory to pass the exam of the 10 CFU version of the course. For all students, the use of a personal computer is allowed as well as that of books, personal notes etc.
In the written exam the student must show the ability to conduct a stylized data analysis, by selecting the appropriate methods and algorithms - among those introduced in the course - for solving the problems, by running the algorithms with R, by identifying the significant results and by reporting them with the precision and property of language which characterize the technical and scientific communication.
(b) Team project evaluation. Projects will be collectively evaluated by the teachers of the course and by the students participating to a final workshop at the end of the course.
During the presentation of their projects, teams must prove their ability to conduct and report a real life statistical data analysis, showing knowledge and understanding of the problem at hand and the nature of the data, proper judgment for the selection of the appropriate methods and algorithms, sensible interpretations of the generated results - grasping not only their strenghts but also their weaknesses - and, finally, communication skills when informing an audience of peers.
To pass the exam the student must pass each part of the exam with a score greater than or equal to 18/30; the final score is then obtained as the weighted average of the two scores, with weights respectively equal to 0.6 for the written exam and 0.4 for the project evaluation.

Galecki A., Burzykowski T., Linear Mixed-Effects Models using R, Editore: Springer, Anno edizione: 2013
Jhonson R.A., Wichern D.W., Applied Multivariate Statistical Analysis, Editore: Prentice Hall, Anno edizione: 2007
Ramsay, J.O. e Silverman, B.W., Functional Data Analysis (second edition), Editore: Springer, Anno edizione: 2005
Cressie, N., Statistics for Spatial Data (Revised Edition), Editore: Wiley, Anno edizione: 1993

This course explores advanced topics in Computational Fluid Dynamics (CFD), focusing on the practical application of simulation techniques to the complex flow phenomena encountered across engineering. Students will learn to develop and implement CFD models for a broad range of flow processes, including compressible flows, chemically reacting flows, multiphase flows, moving boundaries and grids, and heat transfer. Building on the introductory course Computational Fluid Dynamics: Fundamentals, it emphasizes advanced simulation strategies rather than the detailed mathematical formulation of numerical methods. Throughout, students will work through real-world examples drawn from mechanical engineering and related fields, and dedicated sessions will address the development and integration of custom models for simulating complex physical phenomena.

Learning Outcomes
By the end of the course, students will be able to translate complex multiphysics fluid dynamics problems—typically described by partial differential equations (PDEs)—into discretized systems of equations and solve them using appropriate numerical techniques. This includes a solid understanding of numerical stability, convergence, and consistency, applied to a wide range of scenarios from single-phase to multiphase flows, incorporating heat transfer and moving grids.
Lectures and exercise sessions will enable students to:
Identify the most suitable modeling approach for complex, multiphysics problems.
Select the optimal simulation strategy and level of approximation for solving advanced flow scenarios.
Evaluate the impact of setup choices on CFD simulation results and effectively conduct post-processing.
Implement custom models within a CFD framework to extend the software’s capabilities.
The project laboratory will provide students with practical experience to:
Set up a well-posed compressible flow problem, selecting appropriate numerical schemes and solvers.
Generate computational grids for multi-region and multi-domain configurations.
Configure CFD simulations, including boundary and initial conditions, and define grid motion strategies.
Choose and apply the most appropriate multiphase modeling approach (e.g., Lagrangian, Eulerian, Eulerian dispersed, Eulerian VOF).
Post-process and analyze simulation results to extract meaningful insights.

Course Topics
CFD Simulation of Compressible Flows: Extension of pressure-based solution methods to compressible flow regimes. Density-based approach. Treatment of boundary conditions for subsonic and supersonic flows. Overview of available solvers for compressible flow simulations and techniques for effective post-processing.
Moving Grid Strategies: Approaches for handling small deformations, including mesh-to-mesh interpolation. Techniques for managing large deformations through mesh topology adaptation. Advanced methods for dynamic mesh handling, such as sliding interfaces, overset meshes, and immersed boundary techniques.
Multiphase Flow Simulations: Fundamentals of Eulerian–Eulerian approaches, diffused interface (pseudo fluid) and interface capturing (VoF) approaches. Simulation of dispersed phases using Lagrangian particle tracking. Introduction to liquid film modeling: tracking of wall film formation and phase change process.
Conjugate Heat Transfer: Multi-region modeling strategies for heat transfer problems involving multiple materials and fluid systems. Integration with structural analysis to assess mechanical stress and thermal effects.
Reacting Flows: Simulation methodologies for chemical reactions within fluid flows, including both homogeneous and heterogeneous processes. Introduction to combustion and catalytic reaction modeling in CFD environments.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam will consist of a project assessment which will be carried out in groups of three students. The project is the same for all the students and is valid for a single academic year. All the groups are required to submit the report about the project by two days before the official date of the exam. The development of the project will prove that the student has learned how to discretize a system of partial differential equations into a set of discretized equations and how to solve them checking consistency, stability and convergence.
All the students will be required to discuss the project in the frame of an oral group presentation, during which the teacher will ask questions related to modeling aspects learned during the course. Students will show that they can discuss the results obtained at the light of the approximations and choices they have done during the development of the project. The final mark will be the summation the two parts of the exam: project and oral presentation.

J. H. Ferziger, M. Peric, Computational Methods for Fluid Dynamics, Editore: Springer, Anno edizione: 2002
H. K. Versteeg, W. Malalasekera, An introduction to computational fluid dynamics: the finite volume method, Editore: Longman, Anno edizione: 1995
A. Onorati, G. Montenegro, 1D and Multi-D Modeling Techniques for IC Engine Simulation, Editore: SAE International, Anno edizione: 2020

The course aims to introduce the fundamental principles of Computational Fluid Dynamics (CFD) and to provide students with the knowledge and skills required to properly apply CFD techniques to the simulation of simple flow problems encountered in various fields relevant of mechanical engineering. The course covers the basic mathematical models for inviscid, viscous, and turbulent flows, as well as computational mesh generation and quality assessment, the main numerical discretization schemes, and the most widely used solution strategies for the incompressible Navier–Stokes equations. Upon successful completion of the course, students will have acquired the theoretical background and practical skills needed to use an open-source CFD software package to simulate incompressible internal and external flows relevant to mechanical engineering applications.

By the end of the course, students will be able to apply a general-purpose CFD tool to solve fluid flow problems relevant to mechanical engineering by selecting the appropriate flow model, numerical setup, and computational mesh. They will have acquired a comprehensive understanding of the key aspects of the numerical modeling of incompressible viscous and turbulent flows, including both internal and external flow applications.
Lectures and exercise sessions will allow students to:

• identify the most appropriate level of physical and mathematical approximation for the flow phenomena to be simulated;
• generate the most appropriate space discretization based on the selected approximation level and choose a proper set of boundary conditions;
• evaluate the impact of modeling and numerical choices made during the simulation setup on the accuracy and reliability of the results, and perform appropriate post-processing and interpretation of the outcomes.
  The project laboratory will enable students to:
• a computational mesh suitable for the problem under investigation;
• set up a CFD simulation by selecting the fluid and turbulence models and defining the appropriate initial and boundary conditions;
• select an appropriate set of schemes for the numerical approximation for the problem being solved;
• monitor and assess the convergence of the simulation;
• post-process, verify, and validate the simulation results.

The course introduces the fundamental principles of Computational Fluid Dynamics (CFD), with particular emphasis on the physical models, numerical methods, and solution algorithms used for the simulation of incompressible internal and external flows under both steady and transient conditions. The topics covered by the course are as follows:
1. Basic concepts of computational fluid dynamics: Introduction to CFD and description of the main modeling approaches: one-, two-, and three-dimensional flow models. Mathematical classification of the flow regimes: compressible and incompressible, viscous and inviscid flows.
2. Space discretization: Computational mesh for finite difference methods and for finite volume methods. Structured and unstructured meshes. Tetrahedral, hexahedral, and hybrid meshes. Advanced meshing strategies. Mesh quality assessment, boundary-layer meshing, and mesh independence analysis.
3. Turbulence and turbulence modeling: Physical characteristics of turbulent flows. Levels of approximation for turbulence modeling. Reynolds-averaged Navier–Stokes (RANS) equations. Algebraic, one-equation, and two-equation turbulence models. Near-wall treatment and wall functions.
4. Finite difference methods: Discretization of first-order and second-order derivatives in space for convection/diffusion problems. First-order and second-order discretization schemes.
5. Finite volume methods: Integral formulation of the governing equations. Numerical approximation of surface and volume integrals. Interpolation techniques. First- and second-order discretization schemes and their accuracy. Implicit and explicit time integration.
6. Solution of systems of linear equations: direct and iterative methods, Gaussian elimination, LU decomposition, the conjugate gradient method, and multigrid techniques.
7. Solution algorithms for the Navier-Stokes equations: Pressure-based and density-based approaches. Pressure–velocity coupling algorithms for incompressible flows, including SIMPLE and PISO solution strategies. Numerical solution of steady and transient flow problems.
The tutorials will include guided examples and hands-on activities covering the complete CFD workflow, including mesh generation, simulation setup, solver run, and post-processing of representative engineering applications.
1. Internal flows: Steady and transient flows in ducts and channels. Mesh generation, specification of initial and boundary conditions, solver selection. Comparison between inviscid and viscous flow models.
2. External flows: Flows around airfoils, turbomachinery cascades, and wind turbines. Computational domain definition, mesh topology, boundary conditions, application of turbulence models, and assessment of their effects on aerodynamic performance.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The exam will consist of two parts:
The first part consists of a written examination including questions on the theoretical aspects covered during the course.
The second part consists of the preparation, submission, and oral discussion of a report documenting two computational exercises: one involving an internal flow and one involving an external flow.
The final grade will be determined by combining the results of the written examination and the report/oral discussion.

J. H. Ferziger, M. Peric, Computational Methods for Fluid Dynamics, Editore: Springer, Anno edizione: 2002
H. K. Versteeg, W. Malalasekera, An introduction to computational fluid dynamics: the finite volume method, Editore: Longman, Anno edizione: 1995
A. Onorati, G. Montenegro, 1D and Multi-D Modeling Techniques for IC Engine Simulation, Editore: SAE International, Anno edizione: 2020

The course aims to provide students with the fundamental knowledge and methodological tools required to model, analyse, and evaluate mechanical systems equipped with actuators and active control.
By the end of the course, students will be able to understand the interaction between mechanical systems, actuators, and control logic, and to assess how active control can improve performance, efficiency, stability, and disturbance rejection.

D1. Knowledge and understanding
After completing the course, students will:
understand the interaction between mechanical systems, electric motors, and control logic;
know how to represent controlled mechanical systems using mathematical models, including transfer functions and state-space representations;
understand the basic principles of classical control in the time and frequency domains;
know the main methods for stability and performance analysis, including Bode diagrams, Nyquist diagrams, and root locus;
understand the basic principles of PID control and its practical tuning;
know the modelling principles of electric motors used in controlled mechanical systems;
understand the effects of feedback control on stability, dynamic performance, robustness, reference tracking, and disturbance rejection;
understand how laboratory activities support the design and assessment of control systems.
D2. Applying knowledge and understanding
After completing the course, students will be able to:
build dynamic models of mechanical systems coupled with electric motors;
design and tune basic control systems, with particular reference to PID controllers;
compare different control strategies and evaluate their effects on system performance;
analyse controlled mechanical systems in both the time and frequency domains;
use basic simulation tools, such as MATLAB/Simulink, to support control-system design;
interpret simulation results and relate them to the physical behaviour of controlled mechanical systems.
D3. Making judgements
After completing the course, students will be able to:
select the most appropriate controller for a given mechanical system, taking into account stability, performance, robustness, reference tracking, and disturbance rejection requirements;
critically compare different modelling and control choices on the basis of simulation results and frequency- and time-domain analyses;
evaluate the stability and performance of a controlled mechanical system and justify the adopted design choices.
D4. Communication skills
After completing the course, students will be able to:
present and discuss the results of modelling, simulation, performance analysis, and controller design in a clear and effective way;
use graphical representations, such as time responses, Bode diagrams, Nyquist diagrams, and root locus plots, to support the explanation of control-system behaviour;
prepare laboratory reports that clearly describe modelling assumptions, control design procedures, simulation results, and final conclusions.
D5. Learning skills
After completing the course, students will be able to:
use the methodological tools acquired during the course to analyse new controlled mechanical systems with a sufficient degree of autonomy;
deepen their understanding of control-system design through technical documentation, simulation tools, and further individual study;
extend the acquired modelling and control techniques to related applications involving mechanical systems, electric motors, and feedback control.

The course covers the following topics, divided into modules as described below.
Module 1: Introduction to the control of mechanical systems
Basic concepts of a dynamic system, input and output variables. Control variables and observed variables. Control of a mechanical system: feedback and feedforward. Effects of control action on dynamic performance, stability, and disturbance rejection.
Module 2: Classical control theory
Simulation models. State variables. Routh-Hurwitz stability criterion. Laplace transform. Transfer functions. Block diagram representation. Root locus. Harmonic transfer function. Fourier transform. Frequency response function. Bode and Nyquist diagrams. Nyquist criterion. Requirements of a controlled dynamic LTI SISO system: synthesis of the control logic, definition of performance and robustness indexes.
Module 3: P, PD and PI controllers
Application to one-degree-of-freedom and two-degree-of-freedom vibrating systems. Performance assessment of the controlled system in the time and frequency domains. Input and output disturbance rejection.
Module 4: Electric actuators
Basic components, performances, and characteristic curves. DC drives and their control. Control of electric drives: basic principles, criteria for torque and speed control, and performance assessment.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
The exam consists of:
a written test;
a discussion of three assignments;
an oral examination.
Students are required to submit three short assignments based on the activities carried out during the computer labs. Submission of the assignments and successful completion of the written test are mandatory requirements for admission to the final oral examination.
With reference to the expected learning outcomes:
the written test is mainly intended to assess the topics covered in Modules 1 and 2;
the discussion of the assignments is intended to assess the topics covered in Modules 2, 3 and 4;
the oral examination covers all topics addressed in the course.

Andrea Maria Zanchettin, Feedback Control Systems, ISBN: 9791221085259 https://re.public.polimi.it/retrieve/3fc18d40-8910-4813-9a15-b6c7eef53981/Feedback_control_systems_mech_eng_compressed.pdf
Note: Available online
Gene Franklin, David Powell, Abbas Emami-Naeini, Feedback Control of Dynamic Systems, Editore: Pearson Education Limited, Anno edizione: 2019, ISBN: 9781292274522

The great majority of mechanical systems is nowadays fitted with active control aimed at improving performance, efficiency and stability. Main objective of the course is to provide students with the fundamental knowledge and methodological tools required to model, analyse, and evaluate mechanical systems equipped with actuators and active control. By the end of the course, students will be able to understand the interaction between mechanical systems, actuators, and control logic, and to assess how active control can improve performance, efficiency, stability, and disturbance rejection.

D1. Knowledge and understanding.
After completing the course, students will:
understand the interaction between mechanical systems, electric motors, and control logic;
know how to represent controlled mechanical systems using mathematical models, including transfer functions and state-space representations;
understand the basic principles of classical control in the time and frequency domains;
know the main methods for stability and performance analysis, including Bode diagrams, Nyquist diagrams, and root locus;
understand the basic principles of PID control and its practical tuning;
know the modelling principles of electric motors used in controlled mechanical systems;
understand the effects of feedback control on stability, dynamic performance, robustness, reference tracking, and disturbance rejection;
understand how laboratory activities support the design and assessment of control systems.
D 2. Applying knowledge and understanding
After completing the course, students will be able to:
build dynamic models of mechanical systems coupled with electric motors;
design and tune basic control systems, with particular reference to PID controllers;
compare different control strategies and evaluate their effects on system performance;
analyse controlled mechanical systems in both the time and frequency domains;
use basic simulation tools, such as Matlab/Simulink, to support control-system design;
interpret simulation results and relate them to the physical behaviour of controlled mechanical systems;
D 3,4,5 Making judments, Communications, Learning skills
After completing the course, students will be able to:
select the more appropriate controller for a given mechanical systems
apply PID control to a case study and evaluate stability and performance of the controlled system
present and discuss the results of modelling, simulation, performance analysis, and controller design in a clear and effective way, also through graphical representations and laboratory reports.

Introduction to the control of mechanical systems (short review). Basic concepts of a dynamic system, input and output variables. Control variable and observed variables. Control of a mechanical system: feed-back and feed-forward. Effects of the control action on dynamic performance and disturbance rejection.
Classic control. Simulation models. State variables. Harmonic transfer function. Laplace and Fourier transform. Frequency response function. Block diagram representation. Root Locus. Bode and Nyquist diagram. Nyquist criterion. Requirements of a controlled dynamic LTI (linear time invariant) SISO (single input single output) system: synthesis of the control logic, definition of performance and robustness indexes.
P, PD and PI controller. Application to 1 dof and 2 dofs vibrating systems. Performance assessment of the controlled system in time domain and frequency domain. Input and output disturbance rejection.
Electric actuators: basic components, performances, characteristic curves. DC drives: control. Control of electric drives: basic principles, criteria for torque and speed control, performances.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Altro
The exam consists of:
a written test;
a discussion on lab reports;
an oral examination.
Students are required to deliver a short report on the assignments given during the computer labs. Delivering lab reports and passing the written test is mandatory for having access to the final oral examination.
With reference to expected learning outcomes:
the written test is intended to verify mainly items D1 and D2;
the discussion on lab reports is intended to verify items D2, D3, D4, D5;
the oral examination will cover all topics illustrated in the course and it is intended to verify items D1, D2, D3, D4 and D5.

K. Ogata, Modern Control Engineering, Editore: Prentice Hall Ed
L. Meirovitch, Fundamentals of Vibrations, Editore: John Wiley & Sons Ed
L. Meirovitch, Dynamics and control of structures, Editore: John Wiley & Sons Ed
G. Diana, F. Cheli, Advanced dynamics of mechancial systems, Editore: Springer
D. Inman, Vibration with control measurement and stability, Editore: Prentice Hall
Mechanical systems control WeBeep
R. C. Dorf, R. H. Bishop, Modern Control Systems, Editore: Prentice Hall
A. Hughes, Electric Motors and Drives-Fundamentals, Types and Applications, Editore: Elsevier
Merrit, Hydraulic control systems, Editore: John Wiley & Sons

Questo corso fornisce una panoramica completa delle strategie di raccolta dati, elaborazione segnali e tecniche di analisi per la caratterizzazione di sistemi di trasporto. I principali argomenti trattati comprendono: concetti introduttivi (classificazione dei segnali e loro caratteristiche, basi di acquisizione segnali); analisi nel dominio del tempo (parametri statistici, funzioni di correlazione); sistemi lineari tempo-invarianti (convoluzione); analisi nel dominio della frequenza (analisi di Fourier, finestre, spettri, filtri); tecniche avanzate di analisi dei dati (trasformata tempo-frequenza, analisi degli ordini, introduzione agli approcci di machine learing e di intelligenza artificiale).
Ogni argomento viene esplorato sia dal punto di vista teorico, attraverso discussioni e casi studio, sia dal punto di vista pratico, attraverso sessioni dedicate di esercitazioni interattive.

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a circular business and industrial environment and the impact of those factors on business and technical performance measures.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a circular business case, focusing on demanufacturing and remanufacturing processes for recoverying and reuse functions and materials from high-value, post-use products in multiple sectors.
Develop new ideas and solutions in circular business cases, grounding on the knowledge of the available technological solutions supporting demanufacturing and remanufacturing and evolving in line with the general technological, business and regulatory framework.

Understand: The students will learn the key definitions of circular economy business cases, the underlying motivations, and the boundary conditions affecting the successful industrial transition to this sustainable production-consumption model. Moreover, they will learn the key role of advanced de-and remanufacturing systems in view of the development and implementation of circular economy business models at industrial scale. Several real-life examples will be discussed in order to support the in-depth understanding of business practices.
Design: The students will learn scientific and engineering methods in support of an efficient design and management of advanced demanufacturing and remanufacturing systems.
Develop: The students will learn the most relevant circular economy problems of the future and will be challenged with the analysis of future technology and business innovations to support these emerging needs.

The economical and environmentally sustainable treatment of end-of-life products and industrial waste by de-manufacturing processes is the core topic of this course. De-manufacturing includes the set of technologies, tools and knowledge-based methods to remanufacture and re-use functions and to recover materials from industrial waste and post-consumer high-tech products, under a circular economy perspective. This course provides competences related to mechanical de-manufacturing processes and systems, with the objective to design and operate these technologies in environmental and economical sustainable way, in different industrial settings.
The course will be structured to cover the following topics:

• De-manufacturing paradigm: definition of de-manufacturing systems and examples of industrial applications; De-manufacturing performance measures; Integrated process and system view of the problem; recent trends in de-manufacturing system and the role of the Digital Product Passport.
• De-manufacturing technologies: description of mechanical de-manufacturing processes, including disassembly, re-manufacturing and recycling technologies; mechanical size-reduction and separation processes; the role of hybrid data-driven and physics-based models in the design and operation of de-manufacturing and remanufacturing processes; advanced de-manufacturing technologies based on automated and semi-automated systems.
• De-manufacturing systems: features of de-manufacturing systems; material mixtures and granular flow models; multi-stage de-manufacturing systems modeling; performance evaluation and design of de-manufacturing systems; flexibility in de-manufacturing systems.
  The students will carry out laboratory activities to develop hands-on knowledge on specific processes and process-chains.
  Detailed Lectures Plan (32h)
  Introduction (6h)
  De-manufacturing paradigm: definitions and context.
  Integrated view of disassembly, remanufacturing, recycling, and recovery.
  Overview of de-manufacturing processes and systems.
  Examples:
  Remanufacturing of mechatronic components in the automotive industry: Electronic Control Units (ECUs), starters, alternators, engines.
  Recycling systems for End of Life Vehicles (ELVs): workflow and ASR (Automotive Shredding Residue) problem.
  Recycling systems for WEEE: focus on Printed Circuit Boards (PCBs).
  Recovery of key-metals from Lamps, hard drives, and PCBs.
  Performance Measures: grade/recovery trade-off.
  Integrated process and system view of the problem.
  De-manufacturing processes and technologies (13h)
  Mechanical disassembly and remanufacturing processes. Disassembly graphs and disassembly planning.
  Mechanical recycling processes: size-reduction and separation.
  Mechanical size-reduction processes:
  Overview of the cutting mechanisms and shredding machines;
  Population Based Models for size reduction processes;
  Experimental analysis;
  Application and analysis of the results.
  Mechanical Separation processes:
  Separation principles, physics and mechanisms;
  Overview of technologies: eddy current separation, electrostatic separation, magnetic separation, floatation, sieving, jigging, separation by air, optical sorting technologies (NIR, VIS, SWIR). Comparison of technologies and criteria for the selection of the most suitable process/technology.
  Modeling and simulation of separation processes;
  Analysis of the output and use of the models for process parameters optimization.
  Thermal and chemical processes: characteristics and requirements on the upstream processes (hints).
  De-manufacturing systems (13h):
  De-manufacturing systems architectures and material transportation technologies.
  Modeling material mixtures and granular flows.
  Performance Evaluation of de-manufacturing systems:
  Mass Balance Equations;
  Analytical modeling of de-manufacturing systems dynamics.
  Design of de-manufacturing systems;
  Flexibility and modularity in de-manufacturing systems.
  Detailed Classworks and Labs Plan (21h)
  De-manufacturing process planning (4h):
  Exercise: given a set of electronic and mechatronic products, the student will analyze their structure, their materials, their joints and will decide upon the best possible de-manufacturing process sequence, also through practical sessions.
  Exercises: calculation of performance measures.
  De-manufacturing processes and technologies (9h):
  Exercises: disassembly processes optimization.
  Exercises: disassembly line balancing (both deterministic and stochastic).
  Exercises: use of the size reduction simulation model for process parameters’ selection.
  Visit to the CIRC-eV lab.
  De-manufacturing systems (8h):
  Exercises: analytical modeling of de-manufacturing system.
  Exercise: use of the separation models for the analysis of the recovery and grade in different operating conditions.
  Exercises: reconfiguration of recycling systems; impact of different flow control logics.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course is based on lectures, integrated with exercise sessions, also using laptops, as well as laboratory sessions with hands-on and experimental activities at lab scale. Moreover, optional industrial visits will be organized. The exam includes a written part, focused on exercises, and an oral part, with questions dealing with the whole program. To access the oral part, the written part has to be approved with a sufficient mark. Both parts have to be approved during the same exam session. Optional seminars and small projects will also be offered to deeply analyze specific topics of the course in small teams along with the course development. The results of these optional project works have to be presented before the end of the semester. The quality of this integrative work will be reflected in the final mark.

L'insegnamento fornisce l'insieme di contenuti necessari a progettare gli esperimenti e ad analizzare i risultati utilizzando un sw a grande diffusione. Gli studenti del corso da dieci crediti, inoltre, avranno modo di applicare i concetti teorici ad un caso pratico in cui cercheranno di migliorare un processo di fabbricazione con uno o più esperimenti
I temi affrontati saranno: Analisi della varianza a un fattore e a molti fattori, Modelli a fattori fissati, casuali e misti. Tecniche DOE (Design Of Experiments) per la progettazione degli esperimenti: piani fattoriali completi e con blocco; piani 2k replicati, frazionati e con blocca; piani nested e split plot, piani alfabetici ottimi. Analisi di regressione lineare. Tecniche RSM (Response Surface Methodology) e di progettazione robusta.

The course describes the methodologies to plan, conduct and analyze controlled experiments to determine which factors influence key performance indicators (response) of the product, process or service. Once the relevant factors are selected, the course proposes methodologies for optimization; that is, selecting the levels of the important factors producing the best values of the response. The possibility to optimize through an evolutive experimentation is illustrated using RSM (Response Surface Methodology) Many physical processes are difficult or even impossible to study by usual experimental methods. As computing power has increased, it has become possible to model processes/products/services by sophisticated and time consuming computer codes which act as a proxy for the reality. Also in these cases it is necessary to design appropriately the experiment to save the computational effort. Space filling algorithms are used. The analysis of data has some differences compared to the analysis of physical experiment data as computer experiments have deterministic responses. To analyse this kind of data, Kriging or Gaussion process models must be used. A final look to combining different data sources of information ( multifidelity data, including experts’ opinions, computer simulations and experimental data) for process optimization is included. With the reduced lifetime of innovative technologies, the significant increase of data availability and the needs to speed up the time-to-market for new solutions, this course provides a must-have toolkit for engineers.

Lectures will provide the basis for originality in applying ideas, sometimes in a research context ( Knowledge and understanding ), in the Design and Analysis of Experiments field.
Classwork in computer room will develop the student problem solving abilities in a familiar environment ( Applying Knowledge and understanding ). Some problems will be proposed and the students will be required to solve them under a light guidance of a tutor. The student will use State of Art Softwares to make computations (SAS-JMP, MINITAB, MATHEMATICA or MATLAB).

Part 1 – Design and Analysis of Experiments (DOE)
Introduction to Designed Experiments
The ANalysis Of VAriance (ANOVA) for single factor and single response
Factorial experiments and Blocking for single response and multiple factors
Reducing the experimental effort via fractional factorial experiments
Fundamentals of Linear Models
Part 2 – Response Surface Methodology (RSM) and Design and Analysis of Computer Experiments (DACE)
Advanced Linear Models
Evolutive Experimentation: RSM (Response Surface Methodology)
Robust Design and Multiple Response Optimization
Design of Computer experiments: space filling solutions
Analysis of Computer Experiment Data: Gaussian Processes and Kriging models
Advanced topics for Statistical Optimization

Prova scritta obbligatoria, senza prove in itinere
Written Test
The written test will verify if the students have got the Knowledge and understanding and Applying Knowledge and understanding abilities.
In the Written test the students must solve, usually, 4 problems in computer room.
Usually:
in two problems the students are required to analyse one or more data set containing, sometimes, outliers or incomplete data;
in one problem the students are required to design an experiment and discuss its properties;
one problem is mainly theoretical and the students are required to prove some quite simple property not seen before.
Each problem will have a certain mark and the final test mark will be the sum of the four problem marks.
If the sum of grades is 33 the student will get a final test grade of 30 with "lode"
If the grade equal to or less than 10, the student must go to the next exam session.
The exam will be " Open Book ".

Douglas C. Montgomery, Design and analysis of Experiments, Editore: John Wiley & Sons, Inc., Anno edizione: 2013, ISBN: 978-1-118-09793-9
Professor's Notes
Note: on the WeBeep Course site
Thomas J. Santner, Brian J. Williams, William I. Notz, The Design and Analysis of Computer Experiments, Editore: Springer, Anno edizione: 2003, ISBN: 0-387-95420-1
Enrique del Castillo, Process Optimization. A Statistical Approach, Editore: Springer, Anno edizione: 2010, ISBN: 978-1-4419-4396-5
Note: it is possible to download the book for free

The main objective of the course is to deliver knowledge about the technical organisations, the methods and tools for the design and management of a production system.
Specifically, the course contributes to the development of the following skills:

• understanding the context, functions, processes, and key decision-making areas for managing a logistics and production system;
• designing solutions by applying the scientific and engineering approach (learning, reasoning, and modeling) to appropriately address problems related to a logistics and production system.

Regarding knowledge, after passing the exam, the student will be able to:

• know the terms and classification principles of logistics and production systems;
• apply fundamental principles, generalizations, theories, and concepts to structure the entire planning process (demand forecasting, inventory management, production planning, distribution planning, procurement planning) and measure its performance.
  Regarding understanding, after passing the exam, the student will be able to:
• understand the operation of the main models for demand forecasting, inventory management, production management, distribution management, and procurement management;
• apply this knowledge to specific management problems of a logistics and production system.

The course contents are delivered through lectures and exercises.
After a general overview, the course delves into the topics of basic performance and analyzes the basic aspects of the production and logistics planning and control process.
More specifically, the course covers the following topics:

• Introduction to Supply Chain Management: management of procurement, production, and distribution; types and classification of production and distribution systems.
• Performance measurement: performance of production systems. Performance effectiveness (quality and service) and efficiency (productivity and flexibility).
• Forecasting demand for finished products: basic demand forecasting techniques (moving average, exponential smoothing, etc.).
• Inventory management: types of stock; basic reordering techniques; inventory and stock-out costs.
• The integrated production management cycle: aggregate planning; materials requirements planning; scheduling; just-in-time systems.
• The main trends and innovations in logistics and production systems management.
  Lectures will be complemented by exercises and case study discussions, with the primary goal of providing greater concreteness to the topics covered in class and accustoming students to analyzing information, including quantitative data.

Prova scritta obbligatoria, senza prove in itinere
The exam consists of a written test covering the content of the lectures and exercises.
Specifically, the exam includes:

• open-ended and closed-ended questions on the content covered during the lectures and exercises;
• numerical exercises that require the application of acquired knowledge.
  There are no ongoing tests ("prove in itinere").

Slides,articles,and other classroom material
Production systems management, Editore: Mondadori Education, ISBN: 9788861848924
Design and Management of Production Systems - Practice Book, Editore: CUSL, ISBN: 9788881327775
La gestione del sistema di produzione, Editore: ETAS, ISBN: 9788817068062

The Digital and Advanced Manufacturing (D&AM) course intends to provide students with a concrete vision of the evolutionary challenges that characterize the machine tool and production systems industry today through the experience of some CNC manufacturing companies.
The course includes the intervention of direct testimonies of technical directors of well-known companies located in the Piacenza area, the Italian district specialized in the design and manufacturing of machines and production systems.

Expected learning outcomes are:
MECHATRONIC DESIGN
Design and Safety reference directives, Risk Analysis and Assessment; Security distance and Protections; CE Conformity Declaration; Green design in machine tools; Balance quality starting from the mechanical processing; Main components: Mechanical head; Types of spindle: Mechanical spindle-Electrospindle; Cooling and lubrication systems; Bearing dimensioning; Linear axis-polar axis dimensioning and motion systems; Ball screw dimensioning; Pinion/rack dimensioning; FEM analysis; Balancing dimensioning; Precision; Encoders; Testing - Chatter - Lobe Diagrams.
INFORMATION TECHNOLOGY IN MANUFACTURING
This course section, introduces students to the role of information technology in manufacturing, with emphasis on the following themes:

• Fundamental Abstractions in Manufacturing; The Role and Structure of a Shop Floor Operating System.
• Applications to Process Modeling and Execution, Applications to Production Planning and ExecutAppliion Control
• The Use of Simulation Models in Supporting the Life Cycle of Production Systems.
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  ​

The didactic learning methods include lectures and exercises classroom where will be developed topics such as:
mechanical/electrical/electronic design of processing cells (machine/robot/equipment) starting from the manufacturing problem,

• from specifications to production system configuration,
• selection of materials,
• modularity of the single machine and of the production system,
• components and sensors for automation,
• analysis of the construction costs of individual subassemblies and of the production system,
• numerical control and machining programming,
• a look ahead: the network part-program,
• the machines precision (measurement, repeatability, interconnection),
• digitization of production,
• digital twins and predictive maintenance,
• testing of the machines,
• machining process modeling and execution monitoring,
• production planning and control,
• production system configuration.
  Such activities will be accompanied by specialized laboratories, carried out mainly in the companies involved, in which the students, in groups of two/three, will develop an in-depth analysis of a topic among those addressed in the classroom and will be called to discuss it during the exams, in flipped/blended teaching mode, also highlighting independently acquired concepts.

Prova orale obbligatoria
During the first weeks of the course, a semester projet will assigned to groups of two/three students.
The discussion of the semester project will be at the focus of the evaluation achieved by each student within the exam.
===
D&AM 2024-'25 is supported by: JOBS, MCM, DEX Siemens, MUSP.

"L'obiettivo del corso è quello di presentare alcuni dei principali concetti e metodi di Ottimizzazione Discreta che consentono di affrontare un'ampia varietà di problemi decisionali che sorgono in scienza, ingegneria e management. L'attenzione si concentra sulla programmazione lineare mista intera (PLMI), cioè sui problemi di ottimizzazione con una funzione obiettivo lineare e vincoli lineari in cui alcune (o tutte) le variabili sono limitate a prendere valori discreti (interi). Vengono trattati anche aspetti modellistici e relativi alle applicazioni.
Argomenti: Fondamenti di analisi convessa. Problemi di PLMI e tecniche di modellazione. Formulazioni alternative, forti e ideali. Problemi di PLI ""facili"". Rilassamenti lagrangiani, surrogati e combinatori. Euristiche (greedy e ricerca locale). Strategie di branching per il metodo Branch-and-Bound. Metodi dei piani di taglio: tagli per problemi di PLI generici, disuguaglianze valide forti per problemi specifici di PLI, separazione e rafforzamento. Metodo Branch-and-Cut. Metodo di generazione delle colonne.
Durante le sessioni di laboratorio informatico, gli studenti impareranno a risolvere problemi di PLMI con il linguaggio di modellazione AMPL e un risolutore stato dell'arte. "

The aim of the course is to enable students to master advanced engineering methods for vibration analysis of mechanical systems, with a specific focus on continuous structures. It covers theoretical models, discretisation techniques and numerical solutions based on the finite element method. Particular attention is given to practical examples and engineering applications, especially in the field of structural dynamics and rotordynamics. Each topic is treated both theoretically and practically, through traditional lectures, class exercises, experimental labs and computer room sessions.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will develop a knowledge of the modelling approaches to vibration analysis of continuous systems (DD1) and the ability to handle vibration problems for arbitrary combinations of geometrical configurations, structural properties and boundary conditions (DD2); in addition, students will understand the basic physical phenomena involved in two of the most significant issues of rotordynamics (e.g. bending critical speeds) as well as the fundamental engineering approaches to rotor balancing (DD1).
Concerning the ability to apply the acquired knowledge and understanding, students will develop the ability to apply theoretical knowledge to the analysis of vibration problems in complex mechanical systems and make judgements concerning possible alternative choices for modelling a real structure/machinery (DD2, DD3).
Through lab activities will be able to process experimental data from dynamic tests and extract basic information regarding the modal parameters of a vibrating structure, i.e. natural frequencies, damping ratios, mode shapes (DD2);
Finally, students will improve their communication skills, being able to develop skills in summarizing and presenting the results achieved during lab activities (DD4);

The course contents are delivered through lectures, exercises courses and lab activities.
The course covers the following topics divided in modules as per the description below:
Module 1 Vibration analysis of discrete systems (a short summary)
Topic 1.1 Free and forced vibration of single-dof and multi-dof systems. Modal superposition approach and principal coordinates formulation of the equations of motion.
Module 2 Vibration analysis of one-dimensional continuous systems
Topic 2.1 Transverse vibration of strings. Axial vibration of bars. Torsional vibration of circular shafts. Bending vibration of slender beams (Euler-Bernoulli formulation).
Wave propagation and standing wave solutions. Free vibration: natural frequencies and vibration modes for different boundary conditions, transient response to assigned initial
conditions. Forced vibration: steady-state response to harmonic input.
Topic 2.2 Modal superposition approach and principal coordinates formulation of the equations of motion.
Module 3 Experimental modal analysis
Topic 3.1 Overview of test procedures and Frequency Response Function (FRF) estimation. Mathematical formulation of the FRF based on modal superposition.
Topic 3.2 Algorithms for frequency-domain modal parameters identification (multi-mode curve fitting method and simplified single-mode identification procedure).
Module 4 The finite element method in structural dynamics
Topic 4.1 General introduction to the finite element discretization of continuous systems. Detailed formulation of the 6-dof beam element for in-plane analysis: shape functions for
axial and bending deformation, mass and stiffness matrices.
Topic 4.2 Procedure for developing the finite element model of a structure: global and local reference systems, work-equivalent nodal forces, matrix assembling, structural damping
model, boundary conditions and matrix partition. Classical dynamic analysis: natural frequencies and vibration modes, frequency response.
Module 5 Rotordynamics
Topic 5.1 Overview of the dynamic problems in rotating machinery. Balancing conditions and balancing procedures for a rigid rotor.
Topic 5.2 Bending critical speeds and balancing procedures for a flexible rotor

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
The exam consists of:
a written test;
a discussion on lab reports;
an oral examination.
Students are requested to deliver short reports on the two assignments given during the experimental and computer labs. Delivering lab reports and passing the written test is mandatory for having access to the final oral examination.
With reference to expected learning outcomes:
the written test is intended to verify module 2;
the discussion on lab reports is intended to verify items 3 and 4;
the oral examination will cover all topics illustrated in the course, with a specific focus on items 5 and 6.
Final Grading
To pass the course, students must successfully pass the written test, complete the project and being able to discuss it, pass the oral examination.

F. Cheli, G. Diana, Advanced Dynamics of Mechanical Systems, Editore: Springer, Anno edizione: 2015, ISBN: 978-3319181998
L. Meirovitch, Fundamentals of Vibrations, Editore: Waveland, Anno edizione: 2010, ISBN: 978-1577666912
M. Petyt, Introduction to Finite Element Vibration Analysis, Editore: Cambridge University Press, Anno edizione: 2010, ISBN: 978-0521191609
Course handouts available on BeeP https://beep.metid.polimi.it/

This course is aimed to introduce aspects and issues related to the design and operation of the electric systems for railway transportation both considering the infrastructures (and their interactions with other technological plants nearby) and the apparatus/devices on board of the trains.

The course will allow the Students to know (DdD1):
the electric systems to supply the railway infrastructure;
the size, design and protection of the electric system infrastructure;
the interference with other technological systems present in the vicinity and underground;
thedifferent electric drives typologies on board of the trains;
the auxiliary systems for train operation;
the systems on board of trains not powered by contact lines.
The laboratory project will allow the Students to (DdD2 and DdD3)
present and discuss about the design of a regional train service.
Technical visits to a railway train maintenance structure will show to the Students the practical application of the theoretical aspects (DdD2).

1.: The Electric Substations and Lines: this section is related to the electricity supply of the railway infrastructure: convenience of electrically powering the infrastructure; DC supply with power electronic converters, protections; AC supply at railway frequency; AC supply at industrial frequency for High Speed lines: sizing criteria and criticalities are presented and discussed.
2.: Interference and electromagnetic compatibility: this topic is focused on interference of railway electric infrastructures with other technological systems in the vicinity and underground both for DC supplied lines and AC supplied ones; the safety of the people and the security of the plants.
3.: DC electric machines: these machines were used in the past for train drives and their characteristics are underlined for undertanding the need of torque/speed optimal curve regulation that modern systems have to adopt with technologies that can reduce weight, size, costs.
4.: AC electric machines: these machines installed on board of the recent trains are described in their electrical and mechanical characteristics e the need of regulation for transportation goals are highlighted.
5.: Power electronic Drives: this section is focused on the presentation of the different power electronic inverters for motors drive: type and size of components, schematic design, control strategies, for the supply regulation of AC motors.
6.: Auxiliary services: in this section the auxiliary devices for the train safety and operation are described.
7.: Interoperability: in this section the multi-voltage supply train are analyzed; they can operate under different supply voltage and frequency for national and international services.
8.: Trains not powered by contact lines: in some cases it is not convenient to build an electric infrastructure for railways and the electric energy is generated on board by means of diesel machines or hydrogen fuel cells. This systems are presented with reference to different type of trains.
Room exercise lessons are dedicated to the sizing of DC supply lines.
Technical visits on real power systems complete the course.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, con revisioni periodiche, senza presentazione/discussione finale
Final exam at the end of the course will be in oral form.
Some questions on specific subjects will be asked to assess the knowledge of the theoretical aspects of the course (DdD1).
Moreover, other questions will assess the ability of the Student to link the theoretical subjects to the practical aspects (DdD2).
A design project possibly carried out during the laboratory will contribute to the final evaluation (DdD2).

M. Brenna, F. Foiadelli, D. Zaninelli, Electric Railway Transportation Systems, Editore: IEEE Press - Wiley, Anno edizione: 2018, ISBN: 978-1-119-38680-3

In the domain of micro and nanosystems, classical mechanical models no longer suffice to predict material behavior. This course provides students with the fundamental principles of quantum mechanics and solid-state physics, which are essential for a rigorous microscopic description of matter. Acquiring these analytical tools enables future mechanical engineers to comprehend, predict, and exploit the novel physical phenomena that emerge exclusively at the micro- and nano-scale.
The course is organized into three progressive phases, bridgeing the gap between classical engineering backgrounds and advanced modern physics:
The Classical Crisis and the Quantum Transition: Initiating from classical electromagnetism (Maxwell’s equations and electromagnetic waves), the course examines the pivotal experiments of the early 1900s that exposed the limitations of classical physics—including black-body radiation, the photoelectric and Compton effects, electron diffraction, and atomic spectra.
Fundamentals of Quantum Mechanics: Students will master core quantum principles, such as wave-particle duality, operators and observables, the Schrödinger equation, and the Heisenberg uncertainty principle, applying them to decipher atomic and condensed matter phenomena.
Solid-State Physics and Material Properties: The course introduces the quantum theory of solids, focusing on crystal structures, symmetry, Bloch’s theorem, and electronic band structures. This framework is utilized to explain the underlying mechanisms governing the electrical and thermal properties of materials.
The course balances theoretical rigor with an engineering perspective by analyzing selected state-of-the-art applications within micro and nanotechnology.
Utilizing innovative pedagogical approaches, including the flipped classroom method, the course actively engages students in evaluating their comprehension of the material. This interactive framework is designed to foster critical thinking, training students to select and apply the appropriate analytical approach—whether classical, semiclassical, or quantum—to solve complex, real-world engineering problems.

DD1 (Knowledge and understanding): acquisition of the fundamental principles of quantum mechanics and condensed matter physics.
DD2 (Applying knowledge and understanding): application of quantum models to the description of microscopic systems and material properties.
DD3 (Making judgements): ability to critically interpret physical models and their domain of validity in modern physics contexts.
DD4 (Communication skills): use of appropriate scientific language and formalism in describing quantum and solid-state phenomena.
DD5 (Learning skills): development of autonomous learning abilities for advanced topics in theoretical and applied physics.

The curriculum is strategically structured into three interconnected modules, transitioning from established classical principles to advanced quantum engineering frameworks. This rigorous theoretical foundation is systematically paired with practical problem-solving sessions, analytical exercises, and specialized case studies to ensure a comprehensive, quantitative understanding of physical phenomena.
Module 1 | Classical Electromagnetism
This module establishes the classical baseline and field-theory fundamentals necessary to understand wave propagation and radiation-matter interaction.
Maxwell's Equations: A comprehensive review of electrostatics and magnetostatics, leading to Faraday-Neumann-Lenz's law, the Ampère-Maxwell law, and the unified framework of Maxwell's equations in vacuum and matter.
Wave Physics: Fundamental principles of the wave equation, complex representation, interference phenomena, and the behavior of traveling and standing waves.
Electromagnetic Waves: Propagation of plane waves, energy transport via Poynting's theorem, and the principles of interference and diffraction.
Engineering Applications: Structural characterization via X-ray diffraction.
Module 2 | Fundamentals of Quantum Mechanics
This module explores the foundational crisis of classical physics and introduces the mathematical and conceptual apparatus of quantum mechanics to explain atomic and molecular structures.
The Breakdown of Classical Physics: Empirical evidence from electron diffraction, the photoelectric effect, the Compton effect, black-body radiation, and discrete atomic spectra.
Wave-Particle Duality: Quantum nature of light (photons) and the De Broglie wavelength of matter.
The Schrödinger Equation: Wave functions, quantum operators, stationary states, expectation values, Born's statistical interpretation, and the continuity equation.
Operators and Observables: Properties of Hermitian operators, commutators, the Heisenberg uncertainty principle, and Ehrenfest’s theorem.
Canonical Case Studies: Energy quantization and dynamics in potential wells, particles in a box, harmonic oscillators, and quantum tunneling.
The Hydrogen Atom: The Bohr model legacy, angular momentum quantization, quantum numbers, ground/excited states, and atomic orbitals.
Multi-Electron Systems & Molecules: Electron spin, the Pauli exclusion principle, the periodic table architecture, the ionized hydrogen molecule, molecular orbital theory, and structural stability.
Engineering Applications: Diagnostic and analytical techniques in atomic spectroscopy.
Module 3 | Introduction to Solid-State Physics
The final module applies quantum mechanics to collective crystalline systems, establishing the microscopic origins of macroscopic material properties essential for micro- and nanosystems.
Quantum Theory of Crystals: Periodicity, Bloch’s theorem, the tight-binding approximation, the free-electron gas model, electronic band structures, and dispersion relations defining metallic, semiconducting, and insulating states.
Optical Properties: Microscopic mechanisms governing material reflectance and transparency.
Electrical Properties: Electron dynamics within crystal lattices, electrical conductivity mechanisms, effective mass concept, and hole transport.
Thermal Properties: Lattice and electronic contributions to the heat capacity of metals.
Engineering Applications: Modeling, analysis, and characterization of advanced crystal structures.

Prova orale obbligatoria
The final examination can be taken during any of the official sessions established by the School's academic calendar and consists of a comprehensive oral examination covering all course topics.
This discussion is designed to assess the student's depth of knowledge and understanding of the course, as well as his/her capacity to critically apply the theoretical concepts to the description of electromagnetic phenomena and quantum systems—including atoms, molecules, and simple crystal structures. To achieve a successful evaluation, the student must demonstrate the ability to present and discuss the course topics in a clear, concise, and logically organized manner, utilizing appropriate and scientifically rigorous language.

Lecture notes and slides
P. V. Landshoff, A. Metherell, W. G. Rees, Essential Quantum Physics, Editore: Cambridge University Press, Anno edizione: 1997, ISBN: 9780521629935
Classical Electromagnetism - theory and exercises
Note: One of the many existing books on classical electromagnetism (from electrostatics and magnetostatics to Maxwell equations, electromagnetic waves)
F. Ciccacci, Fondamenti di Fisica Atomica e Quantistica, Editore: Edises, Anno edizione: 2019, ISBN: 9788833190679

Il corso fornisce una panoramica delle tecnologie allo stato dell'arte per la produzione di energia elettrica e termica. Il corso tratta i metodi e gli strumenti per valutare le prestazioni energetiche, ambientali ed economiche dei sistemi di conversione dell'energia, quali caldaie, scambiatori di calore, cicli termodinamici, tecnologie di generazione di energia rinnovabile e tecnologie di accumulo di energia elettrica. Il corso fornisce inoltre i fondamenti per l'analisi quantitativa di sistemi energetici con alta penetrazione di energie rinnovabili intermittenti quali solare ed eolico.

The course aims at providing an overview of state-of-the-art and of novel technologies for the production of electricity, heating and cooling power and the fundamental knowledge on technologies and processes for efficient and low-emission energy supply and use in industry.
The course will provide the methods and analytical tools for the evaluation of the energy efficiency, environmental impact and economic performance of energy conversion systems and of energy supply and decarbonization technologies for industrial processes.

Students are expected to acquire knowledge and understanding on:
Main methods and tools to analyze and design energy conversion systems (i.e. mass and energy balances, emissions, economic analysis)
Working principles and main design criteria of conventional and novel energy conversion systems for the generation of electricity, heat and cooling power.
Technical and economic issues associated to the transition towards renewable energy sources (reliability, energy storage, flexible operation, etc)
Operating principles of available and emerging technologies for the increase of energy efficiency and the reduction of CO 2 emissions from different industrial processes
Analytical tools to quantify efficiency, emissions and costs of electricity and heat supply systems for industry
Analytical tools to evaluate and compare different technological approaches for the reduction of the environmental impact in industry, based on technical, environmental and economic indicators
Students are expected to develop the capability of applying the above described knowledge to:
Develop models of the main equipment units and conversion processes of energy systems
Perform energy/economic analysis of conventional energy conversion systems for the production of electricity, heat and refrigeration power (i.e. writing and solving mass and energy balance equations, evaluate the key performance indexes, discuss design and operational principles)
Make judgements on their techno-environmental-economic feasibility and performance.
Develop models to quantify the efficiency and the emissions associated to energy supply to industrial processes
Perform energy, environmental and economic analysis of technologies for the decarbonization of industry
Make judgements on the technical, environmental and economic feasibility of industry decarbonization with different technological approaches.

The course is divided into two parts:
PART 1: Energy conversion technologies (5 CFU):
Energy outlook: units for power and energy; primary energy sources; energy demand and supply evolution; climate change and CO 2 emissions; trajectories for energy transition; regulatory aspects.
Economic analysis: cost of electricity/energy production; impact of main parameters (plant scale, efficiency, fuel cost, carbon tax, capacity factor) on the cost of electricity; fundamentals of electricity markets and electricity price formation.
Heat exchangers: mass and energy balances; design and off-design calculation methods;
Combustion processes: basic properties of fuels and combustion processes; mass and energy balances; emission of pollutants from combustion processes; combustors and boilers; thermal efficiency of combustion processes;
Power generation with thermodynamic cycles: steam and Rankine cycles, gas cycles and gas turbines, combined cycles, reciprocating engines;
Renewable energy technologies: solar, wind, hydro, geothermal, biomass; management of intermittent renewable energies: electricity and heat storage, demand-response flexibility, energy storage, sectors coupling.
Energy storage: characterization of energy storage technologies; technology overview; levelized cost of storage.
PART 2: Industry decarbonization (5 CFU):
Environmental impact of industrial processes: emissions of CO 2 and pollutants from industrial processes; definition and examples of direct (scope 1) and indirect (scope 2 and 3) CO 2 emissions from industrial processes; principles of life cycle assessment (LCA); indicators of energy, environmental and economic performance for energy supply and CO 2 avoidance in industry; European regulatory framework.
Energy efficiency: energy efficiency in industry; heat recovery techniques (air preheating, raw material preheating, heat recovery with thermodynamic cycles); cogeneration; energy efficiency in fluid compression (variable speed drives for air compression, heat rejection).
Decarbonization of heat supply: heat pumps, electric heating, hydrogen (from water electrolysis and from methane reforming), solar heat, biomass and biofuels, geothermal, CO 2 capture and storage.
Reversed cycles: reversed thermodynamic cycles for the production of heat (heat pumps) and cooling power (refrigeration cycles); performance indexes; working fluids for vapor compression cycles.
Technological options for the transition to a decarbonized industry: options for the decarbonization of relevant industrial sectors (cement, iron and steel, refining and chemical industry, glass, ceramics, paper).

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente) o condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully taking a written exam.
Written test on numerical problems – mandatory
This test aims at evaluating students’ ability of applying the acquired knowledge and understanding to simple problems, the ability to independently form judgements and the ability to use the acquired knowledge for further professional development.
The test consists of two numerical problems related to two different case studies. Consulting books or lecture notes is allowed. The topics covered in the exam span the whole course program (including the exercise lessons).
The grade will span the range from 0/30 to 30/30.
Written test on theory – mandatory
This test aims at evaluating students’ acquired knowledge and understanding, the ability to communicate learned contents, the ability to use the acquired knowledge for further professional development.
The test consists of two theory questions related to two different topics of the course. Consulting books or lecture notes is not allowed. The topics covered in the exam span the whole course program (including tutorials).
The grade will span the range from 0/30 to 30/30.
Final Grading
To pass the exam, students must successfully complete the two written tests with a minimum score of 16/30 on both parts.
The final grade is determined as the average of the grades obtained in the two parts, capped to a maximum of 29/30. To obtain a final grade of 30/30 or 30 cum laude, an additional oral test is required. If the final grade in the problem test is lower than 8/30, the student is not admitted to the subsequent exam session.
Optional oral test
If the average grade is above 16 and below 18, it is possible to ask for an oral test to reach sufficiency. In any case, all students with sufficient score can ask for an optional additional oral test, provided that the maximum possible score increase is 3 points while the score decrease is unbounded.
Optional group works
Optional group works are assigned along the course. Participating in the group works activities will allow to obtain a bonus of up to +3 points on the final grade.

Il corso fornisce una panoramica delle tecnologie per la fornitura di elettricità e calore ai processi industriali. Il corso tratta i metodi e gli strumenti per valutare le prestazioni energetiche, ambientali ed economiche della cogenerazione, dei cicli inversi e delle pompe di calore, dei sistemi di riscaldamento elettrico, della produzione e dell'uso dell'idrogeno, della cattura e dello stoccaggio della CO₂ e dell'accumulo di energia termica. Infine, il corso offre una panoramica sulle tecnologie a basse emissioni applicabili in futuro per la riduzione delle emissioni in settori industriali ad alta intensità energetica.

The course aims at:
(i) reviewing relevant basic principles and tools for the analysis of energy conversion systems;
(ii) developing the capability to analyze, model and assess the performance of conventional as well as novel systems for the production of electricity, heat, refrigeration power and propulsion power;
(iii) analyzing and discussing the distinctive features and the potential of the energy conversion technologies playing (or expected to play) a major role in current and future energy scenarios.
Given the emerging trends of the expected “energy transition”, comparative evaluations will consider either conventional technologies like steam cycles, gas turbines and combined cycles, as well as established and emerging renewable energy technologies.
To account for the growing sensibility to sustainability, the analysis of thermodynamic, technological and economic features will be complemented with environmental considerations.

Students are expected to acquire knowledge and understanding in:
Physical principles underlying the conceptual design and the operation of the energy conversion systems most relevant in the current energy scenario
Main tools to analyze and design energy conversion systems: mass and energy balances, performance estimates, emissions, economic analysis
Technical and economic aspects associated to the transition to low-carbon energy systems: available technologies, production / demand match, off-design operation, flexibility, energy storage.
Operating principles and main design criteria of conventional and emerging technologies for the generation of electricity, heat and cooling power.
Students are expected to develop the capability of applying the above described knowledge to:
Develop models of the main equipment units and of the processes carried out in energy conversion systems.
Perform energy/economic analysis of conventional energy conversion systems for the production of electricity, heat and refrigeration power: write and solve mass and energy balance equations, explain operation by referring to basic physical principles, develop simple models to assess performances, evaluate key performance indicators, discuss design and operational principles.
Make judgements on technical, environmental, economic feasibility of energy systems, as well as on their performance

Energy scenario: Overview of world energy demand, production, expected evolution, environmental constraints.
Overview of technologies for electricity production: power generation from fossil fuels (steam power plants, gas turbines, combined cycles) and nuclear; power generation from renewables (solar, wind, hydro, geothermal, biomass); energy storage (pumped hydro, batteries, water electrolysis, power-to-X).
Heat exchangers: Classification, a rchitecture and basic features of the heat exchangers utilized in energy conversion systems. Review of constitutive equations and issues typically encountered in energy conversion systems. Design and off-design approach.
Fuels and combustions: Basic properties of fossil fuels, stoichiometry and energy balance of combustion reactions, evaluation of parameters relevant for the assessment of the performance of fossil fuel-fired energy systems.
Steam Cycles: Basic thermodynamic features and configuration. Regeneration and reheat. De-aeration. Optimization of operating parameters. Interaction between cycle parameters, scale and turbo-machine performance. Modern Ultra-Super-Critical plants.
Steam generators and heat rejection: Architecture, basic features and issues of fired large scale steam generators. Material issues. Heat rejection by large power plants.
1st and 2nd Law analysis: Energy balances of energy conversion systems. Fundamentals of 2nd Law analysis. Applications to the basic processes encountered in energy conversion systems.
Gas turbines and combined cycles: Basic thermodynamic features and configuration of Joule cycles. Choice of cycle parameters vs type of duty and application. Material issues and blade cooling. Regeneration, intercooling and reheat. Motivation and basic features of combined cycle configuration. Heat Recovery Steam Generators. Supplementary firing. Architecture of gas turbine combustors.
Cogeneration: Meaning and motivation of cogeneration. Applications to steam cycles, gas turbine and combined cycles, internal combustion engines. District heating applications. Performance indexes.
Hints on pollutant formation and abatement: P ollutant formation in combustion processes (CO, NOx, HC, PM). Basic principles of primary and secondary abatement technologies for steam cycles and gas turbines. Greenhouse gas emissions.
Economic analysis: Basic approach and tools to evaluate the cost of electricity. Impact of main parameters (plant scale, efficiency, fuel cost, carbon tax, capacity factor) on the cost of electricity. Comparative analysis of most relevant fossil fuel-based and renewable-source-based power plants.
Refrigeration cycles and heat pumps: Inverse thermodynamic cycles. Choice of working fluids and configuration. Multi-level arrangement.
Review of renewable energy and nuclear technologies: basic features of geothermal, solar, wind, biomass and hydro plants. B asic physical processes and technologies for the production of power by nuclear fission reactors: Boiling Water Reactors (BWR) vs. Pressurized Water Reactors (PWR).
Technical visits: one or two exercises sessions will be devoted to the visit of industrial plants for the production of eletricity and/or heat, where students can develop a feeling of the configuration and the operation of commercial Energy Systems.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Written exam: 1) Numerical problems – mandatory
This part of the exam is meant to test students’ ability of applying the acquired knowledge and understanding to simple problems, the ability to independently form judgements and the ability to use the acquired knowledge for further professional development.
The exam consists of two numerical problems related to two different case studies that may be encountered in practical circumstances. The is open book. The topics cover the whole course program, including exercise sessions.
The grade spans the range from 0/30 to 30/30.
Written exam: 2) Theory questions – mandatory
This part of the exam is meant to test students’ acquired knowledge and understanding, the ability to communicate learnt contents, the ability to use the acquired knowledge for further professional development.
The exam consists of two theory questions related to two different topics covered in the course, including exercise sessions. Consulting books or lecture notes is NOT allowed.
The grade spans the range from 0/30 to 30/30.
Final Grade
The final grade is the average of the grades obtained in numerical problems and theory questions. Solutions where either part one (numerical problems) or part two (theory questions) is completely missing, will not be graded. Should a student get a final grade of 8/30 or lower, he/she will not be admitted to the subsequent exam session. The grade obtained in the written exam can be increased up to 3 points based on the quality and the promptness of the execution of group activities, exercise sessions and the individual focus report to be submitted at the end of the course.
Oral exam – optional
Students can also give an oral test. Depending on the grade obtained in the written test, the following rules apply:
Students who have obtained a grade in the written test of at least 18/30 can decide whether or not giving the oral test - i.e. the oral is optional.
Students who have obtained a grade in the written test between 15.5 and 17.5/30 can take the oral test to reach the minimum (18/30) required to pass the exam; otherwise the exam is failed.
The final grade will account for the outcome of both the written and the oral test, and can be either higher or lower than the grade obtained in the written test. By taking the oral, the grade obtained in the written test can be increased at most by 5 points or decreased, possibly down to fail.
The oral test is given in English.

H. Struchtrup, Thermodynamics and Energy Conversion, Editore: Springer, Anno edizione: 2014
S.L. Dixon and C.A. Hall, Fluid Mechanics and Thermodynamics of Turbomachinery (Seventh Edition), Editore: Elsevier, Anno edizione: 2014
K. K. Kuo, Principles of Combustion, 2nd edition, Editore: Wiley-Interscience, Anno edizione: 2005
A. Bejan, Advanced Engineering Thermodynamics, Editore: John Wiley, Anno edizione: 2006
L. Borel, D. Favrat, Thermodynamics and Energy Systems Analysis, Editore: EPFL Press, Anno edizione: 2010, ISBN: 978-2-940222-45-2
J.P. Holman, Heat Transfer, 10th ed., Editore: McGraw-Hill Education, Anno edizione: 2010
F. P. Incropera, Fundamentals of Heat and Mass Transfer, 6th ed., Editore: John Wiley & Sons, Anno edizione: 2006
R. Kehlhofer, F. Hannemann, F. Stirnimann, B. Rukes, Combined Cycle Gas & Steam Turbine Power Plants, 3rd ed., Editore: PennWell, Anno edizione: 2009
H. Spliethoff, Power Generation from Solid Fuels, Editore: Springer, Anno edizione: 2010
Michael J. Moran, Howard N. Shapiro, Fundamentals of Engineering Thermodynamics, Editore: John Wiley & Sons, Anno edizione: 2010, ISBN: 978-0-470-54019-0
Yunus A. Cengel, Michael A. Boles, Thermodynamics: an engineering approach, Editore: McGraw-Hill, Anno edizione: 2011, ISBN: 978-007-131111-3

The course treats the main techniques for data and signal processing, as well as the main approaches for characterising mechanical and mechatronic systems. The main objective of the course is to give students the capability of autonomously:

• experimentally testing mechanical and mechatronic systems;
• analysing and processing data related to mechanical and mechatronic systems;
• using the achieved information to the aim of identifying significant system parameters.

The student will learn how to:

• use algorithms and techniques for data/signal processing in the time and frequency domains (base and advanced frequency analysis, frequency response functions, multichannel analysis, basic and advanced statistics), with special focus on smart/mechatronic systems. Great attention is paid to the use of the information extracted from the signals for system diagnostics through discussions of case studies and explaining how data indexes can be used in the context of artificial intelligence.
• carry out experiemental tests, design tests, and process data to the aim of system identification (e.g., modal analysis for mechanical/mechantronic systems).
  More in detail, at the end of the course, the student is expected to reach the following learning outcomes:
  In terms of acquired knowledge and understanding, students will be able to:
  interpret data and signals (for, e.g., system diagnostics, data cleansing)
  examine system identification tools
  design experimental tests
  Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
  perform data and signal analysis
  process data and signals
  perform experimental tests
  check data after acquisition
  identify the correct data acquisition and data analysis techniques for signal processing
  estimate parameters in mechanical and mechatronic systems
  Through project activity, students will also acquire the skills to formulate a judgment, meaning to
  select actuators/sensors for carrying out experimental tests
  select methods for checking data reliability
  select the best signal processing technique for evidencing system characteristics
  select the best identification algorithm for given problems
  Furthermore, through the assigned project, students will gain the ability to autonomously plan activities and design experiments, and work in team.
  Finally, students will improve their communication skills, being able to prepare and present a technical report/presentation on the basis of data acquired during the semester.

Module 1: Introductory concepts
Topic 1.1: Classification of signals and their features: stationary and non-stationary signals, random and deterministic signals.
Topic 1.2: Basics of signal acquisition. Synchronous and Asynchronous sampling
Module 2: Analysis in the time domain: statistical parameters and correlation
Topic 2.1: Statistical parameters and indexes from time-signals
Topic 2.2: Correlation functions.
Module 3: Signal analysis in the frequency domain
Topic 3.1: Band analysis, Fourier-direct and inverse transform, frequency resolution, Welch’s approach
Topic 3.2 Leakage and Aliasing
Topic 3.3: Windowing techniques, Thomson's approach
Topic 3.4: Relevant quantities in frequency domain: spectra, power-spectra, cross-spectra
Topic 4.4: Time-frequency transform
Module 4: Analysis of Linear Time Invariant Systems
Topic 4.1: Dirac function, impulse response, the convolution integral and the theorem of convolution
Topic 4.2: Frequency response function of mechanical systems and its estimation
Topic 4.3: Coherence function
Topic 4.4: Multiple-input systems
Module 5: Advanced data analysis techniques
Topic 5.1: Orthogonalization of signals, principal component analysis, data reduction
Topic 5.2: Singular Value Decomposition (SVD)
Topic 5.3: Autoregressive moving average models (AR,MA,ARMA,ARX,ARMAX), filtering
Module 6: Techniques for system identification
Topic 6.1: Methods for testing a mechatronic system: choice of sensors, actuators, excitation profiles
Topic 6.2: AutoMAC index
Topic 6.3: Data check
Topic 6.4: Data comparison, MAC and Co-MAC indexes
Topic 6.5: Single- (e.g., least squares) and multi-degree of freedom modal analysis (e.g., Prony method, SVD method, Multi-reference Ibrahim Time Domain method, Maximum likelihood method)
Topic 6.6: Output-only modal identification (operational modal analysis) and main algorithms (e.g., Ibrahim method, frequency domain decomposition method)
Topic 6.7: Feature identification in mechatronic systems
Topic 6.8: Examples of use of modal parameters: introduction to artificial intelligence for system diagnostics, data fitting and regression, multi-variate statistics
Topic 6.9: Recursive identification methods (e.g., LMS, RLS)
Module 7: Identification of fast transient phenomena
Topic 7.1: Wavelet transform

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Attendance to lectures and labs is not mandatory, but warmly suggested.
The exam is composed by two parts: a discussion/presentation about an experimental project (in team) on system identification in mechatronic context carried out by the student during the labs + written test about theory.
The two parts can be given in any order, according to the student's preferences.
Project
Via this project, it will be possible to test students in terms of their capability to apply the knowledge gained in the course, during the theoretical lectures, as well as in terms of their capability to make independent judgements about the achieved results. Furthermore, the discussion of the project will allow evaluating their capability to work in team and their ability to properly present technical activities.
Written test
Via this exam, it will be possible to test students’ comprehension of the theoretical topics discussed during lectures and labs.
Final Grading
To pass the course, students must successfully complete both the previous exam tasks. The final grade will be the sum of the grade of the written exam (maximum of 21 points out of 30) and of the presentation (maximum of 9 points out of 30). Nevertheless, the teacher will have the chance to slightly change the mark with respect to the previous sum in case of very positive/negative answers to specific points during either the presentation or the written test.

Slides on WeBeep https://webeep.polimi.it/my/
A. Brandt, Noise and Vibration Analysis, Signal Analysis and Experimental Procedures, 2nd edition, Editore: Wiley
J. Bendat and A.G. Piersol, Engineering applications of correlation and spectral analysis, Editore: Wiley
J. Bendat and A.G. Piersol, Random data, Editore: Wiley
G. D'Antona, A. Ferrero, Digital signal processing for measurement systems,, Editore: Springer
D.J. Ewins, Modal testing - theory, practice and application - 2nd edition, Editore: Research studies press Ltd,, Anno edizione: 2000
R. Brincker and C. Ventura, Introduction to operational modal analysis, Editore: Wiley
S. Elliott, Signal processing for active control, Editore: Academic Press

The course aims at developing Finite Element analysis skills in the framework of machine design, including non-linear analyses.

By the end of the course, students will acquire theoretical and practical skills according to the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
Define a finite element model of a mechanical structure
Identify the correct solution techniques
Interpret and discuss the results
Concerning the ability to apply the acquired knowledge and understanding, students will be able to critically, independently, and creatively solve structural analysis problems by the finite element method
Through guided exercises, students will also acquire the skills to formulate a judgment, meaning to analyse the structure and select the correct analysis settings and boundary conditions, based on a limited set of input information.

The course contents are delivered through lectures, exercise courses, and design lab activities.
The course covers the following topics divided into modules as per the description below:
Module 1 Linear analyses
Topic 1.1 The finite element method: introduction, review of truss element formulation, shape functions, assembly of the stiffness matrix, and handling of boundary conditions.
Topic 1.2 Solution techniques for FE problems. FE formulation of the Rayleigh-Ritz method.
Topic 1.3 2D elements: element types and shape functions; iso-parametric formulation. Integration of the stiffness matrix: Gauss points, full integration, reduced integration, shear locking; Zero energy modes. Stress evaluation and convergence analysis
Topic 1.4 3D elements and axisymmetric elements
Topic 1.5 Shell elements: formulation of Kirchhoff and Mindlin elements (shear flexible); solid to shell transformation (mid-surface extraction).
Module 2 Non-linear analyses
Topic 2.1 Non-linearities related to large displacements
Topic 2.2 Contact problems: formulation and solution techniques
Topic 2.3 Non-linear behaviour of materials: basic formulation of metal plasticity
Module 3 Other analyses
Topic 3.1 Dynamic analyses: eigenfrequencies and eigenmodes of a FE model
Topic 3.2 Buckling analyses: critical loads and modes.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully taking a written exam, submitting and presenting a homework assignment report, and taking a conditional oral exam.
At the written exam, they will be asked to answer questions about the exercises and the theoretical topics of all the modules.
Only if the written exam is satisfactory can they access the presentation and discussion of the homework assignment.
If deemed necessary, at the end of the discussion of the homework assignment, they could be asked more theoretical questions.
Via this exam, it will be possible to test students’:

• acquired knowledge of the principles of structural analysis by the finite element method
• ability to make decisions about the most appropriate modeling techniques.
  Final Grading
  To pass the course, students must first satisfactorily answer the practical and theoretical questions of the written exam.
  Then, they must satisfactorily present and discuss the homework assignment report.
  Finally, they must satisfactorily answer questions, if any (conditional oral exam).
  The final mark will be the sum of the marks of the written exam, of the presentation and discussion of the homework assignment and of the conditional oral exam.

Robert D. Cook, David S. Malkus, Michael E. Plesha, Robert J. Witt,, Concepts and Applications of Finite Element Analysis, Editore: Wiley, Anno edizione: 2001
Singiresu S. Rao, The Finite Element Method in Engineering https://www.sciencedirect.com/book/9781856176613/the-finite-element-method-in-engineering
Introduction to Finite Element Analysis Using MATLAB and Abaqus https://www.taylorfrancis.com/books/9780429166433
The Finite Element Method: Fundamentals and Applications in Civil, Hydraulic, Mechanical and Aeronautical Engineering https://onlinelibrary.wiley.com/doi/book/10.1002/9781119107323

L’insegnamento ha l’obiettivo di avvicinare gli studenti alle problematiche tecnico-scientifiche delle armi, delle munizioni e degli esplosivi con riferimento alle loro tipologie, caratteristiche, modalità di progettazione, fabbricazione ed impiego, nonché alle possibilità di prevederne il comportamento e gli effetti.
Grande attenzione sarà dedicata alle principali munizioni, armi, sistemi d’arma e strumenti di supporto alla pratica del tiro, specialmente in relazione alle loro caratteristiche balistiche ed esplosivistiche.

Al termine del corso agli studenti avranno fatto propri i contenuti e le pratiche d’esercizio secondo quanto stabilito negli obiettivi formativi di seguito indicati.
In termini di conoscenza e capacità di comprensione, gli studenti saranno in grado di:
conoscere le tipologie, le caratteristiche tecniche, le modalità di progettazione, fabbricazione ed impiego delle principali munizioni, armi e sistemi d’arma;
conoscere e comprendere le tipologie, le caratteristiche tecniche, le modalità di progettazione, fabbricazione ed impiego dei principali esplosivi;
conoscere, prevedere e modellare i principali fenomeni di balistica interna, esterna e terminale;
conoscere e comprendere le caratteristiche e le modalità di applicazione al tiro a bersaglio delle armi leggere e dei principali strumenti di supporto, per l’individuazione, la stima della distanza e la collimazione;
conoscere, comprendere e prevedere i fenomeni lesionali che si sviluppano nei tessuti e nelle strutture biologiche come conseguenza di fenomeni balistici ed esplosivistici;
conoscere e comprendere le tipologie, le caratteristiche e le modalità di progettazione, fabbricazione ed impiego delle principali protezioni balistiche per persone e veicoli.
In merito all’ applicazione delle conoscenze e della capacità di comprensione acquisite, gli studenti saranno in grado di classificare le armi ed i sistemi d’arma in base alle loro proprietà e caratteristiche.
Attraverso le lezioni, le esercitazioni e la didattica laboratoriale gli studenti inoltre acquisiranno la capacità di formulare giudizi in autonomia e di analizzare problemi di base dell’ingegneria, legati alle armi, ai sistemi d’arma ed al loro impiego, nonché alle protezioni balistiche.
Inoltre gli studenti saranno in grado in maniera autonoma di riconoscere le principali tipologie di armi e sistemi d’arma, interpretando per ciascuna le specifiche caratteristiche balistiche ed esplosivistiche.
A valle di questo insegnamento, infine, gli studenti avranno accresciuto le loro capacità comunicative nell’ambito delle armi portatili, dei sistemi d’arma e delle protezioni balistiche, nonché delle relative questioni balistiche ed esplosivistiche, ovvero saranno in grado di riorganizzare i concetti appresi, potendo approfondire in autonomia nuove tematiche in questo specifico ambito.

Le attività didattiche sono realizzate a mezzo di lezioni frontali, esercitazioni ed attività di laboratorio.
L’insegnamento si basa su argomenti divisi in moduli come descritto in seguito:
Modulo 1 - Munizioni e Armi (1,5 CFU)
Cos’è una munizione: innesco, carica di lancio, bossolo, proiettile. Funzionamento, caratteristiche e calibri, materiali e tecnologie, nomenclatura, cenni storici. Le parti fondamentali di un’arma e il suo funzionamento. CIP e SAAMI e gli standard NATO. Canna, otturatore, sistema di mira, sistemi di operazione e sistemi di chiusura. Armi ad avancarica e armi a retrocarica. Armi a colpo singolo, armi a ripetizione (a ricarica manuale), armi semi-automatiche, armi automatiche. Sistemi di mira e ottiche. Visori notturni e termocamere. Telemetri. Accuratezza e precisione. Tipi di armi e relative munizioni. Armi portatili, armi pesanti, armi dei blindati e dei mezzi corazzati, armi anticarro: classificazione, tipologie, impieghi.
Modulo 2 – Esplosivistica (2 CFU)
La combustione e i suoi effetti: i fenomeni esplosivi, combustibile-comburente-innesco, esplosioni deflagranti ed esplosioni detonanti. Esplosioni da gas, da liquidi, da solidi, limiti di infiammabilità. Il metodo del TNT equivalente per la valutazione dei danni di un’esplosione; il fenomeno del BLEVE; la polvere nera e la polvere infume, gli esplosivi da mina, gli esplosivi convenzionali e non convenzionali, i fuochi d’artificio.
Modulo 3 - Balistica interna (1,5 CFU)
Movimento del proiettile nella canna ed andamento delle pressioni. La pressione media e il rapporto d’espansione. Calcoli semplificati di balistica interna e programmi di calcolo per la previsione delle prestazioni della munizione La rotazione del proiettile e le forze agenti sul proiettile. L’espansione dei gas alla volata. Il rinculo e i suoi effetti. Vibrazione della canna.
Modulo 4 - Balistica esterna (2 CFU)
La traiettoria del proiettile: definizioni, terminologia, sistemi di coordinate. Traiettorie balistiche nel vuoto. Forze reali agenti sui proiettili. La resistenza aerodinamica dell’aria e il coefficiente balistico. Traiettorie balistiche in aria. Effetti sulla traiettoria della temperatura, dell’umidità, della pressione atmosferica e della quota. La stabilità e la stabilizzazione dei proiettili. L’effetto del vento. Tiri verso l’alto e verso il basso. Il tiro in verticale. Ottimizzazione aerodinamica dei proiettili. Misura della velocità dei proiettili. I pallini e le loro traiettorie. Programmi di calcolo delle traiettorie balistiche. Programmi di calcolo di balistica esterna ed applicazioni al tiro
Modulo 5 - Balistica terminale (2 CFU)
Energia, densità d’energia e densità sezionale. Bersagli duri: Teoria e modelli di penetrazione balistica, il limite balistico (V 50% ), penetrazione di lamiere spesse e sottili. Il rimbalzo. Protezioni balistiche. Corazze spaziate e composite, corazze reattive. Bersagli morbidi: balistica lesionale, efficacia di un proiettile e potere lesivo, l’impatto di un proiettile contro un bersaglio morbido e la perforazione, la cavità temporanea e la cavità permanente, le lesioni balistiche e potere d’arresto.
Modulo 6 - Armi ed aspetti legislativi (1 CFU)
Classificazione delle armi dal punto di vista legislativo. Acquisto e detenzione di armi da fuoco. Formalità e licenze. Armi inefficienti: disattivazione e rottamazione. Munizioni. Artifizi pirotecnici. Commercio e riparazione di armi. Principali reati e relative sanzioni in materia di armi.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
La valutazione finale mira a definire per ogni studente i risultati di apprendimento attesi. Nello specifico la valutazione finale consta di un esame scritto e di una parte orale facoltativa. Non sono previste prove in itinere.
La prova scritta ha l'obiettivo di valutare la conoscenza di base della materia e riguarderà tutti gli argomenti trattati a lezione/esercitazione durante lo svolgimento dell'insegnamento. A discrezione del docente (se cioè non risultasse evidente l’effettiva preparazione dello studente oppure se si evidenziassero specifiche lacune), oppure qualora ne faccia esplicita richiesta lo studente (se cioè lo studente ritenesse la sua preparazione migliore di quanto il voto proposto in fase di valutazione finale non rappresenti), è prevista anche una parte della valutazione finale da svolgersi oralmente con domande aperte sugli argomenti del programma

Boniardi M., Gorla C., Dispense dell'insegnamento, Editore: edito in proprio, Anno edizione: 2023
Bettin C., I proiettili - tecnologia e balistica, Editore: edito in proprio, Anno edizione: 2015
Bettin C., Balistica lesionale, Editore: edito in proprio, Anno edizione: 2022
Bettin C., Balistica esterna, Editore: edito in proprio, Anno edizione: 2022
Carlucci D.E., Jacobson S.S., Ballistics - Theory and Design of Guns and Ammunitions, Anno edizione: 2018
De Florentiis G., Tecnologia delle armi da fuoco portatili, Anno edizione: 1987
Dodd M.J., Terminal Ballistics, Anno edizione: 2006
Hazell P.J., Armour - Materials, Theory and Design, Anno edizione: 2016
Heard B., Handbook of Firearms and Ballistics, Anno edizione: 2008
Kneubuehl B.P., Wound Ballistics - Basics and Applications, Anno edizione: 2011
Mori E., Sintesi del diritto delle armi, Editore: edito in proprio, Anno edizione: 2021
Pignone G.A., Vercelli U.R., Appunti di balistica, Anno edizione: 1987
Rosenberg Z., Dekel E., Terminal Ballistics, Anno edizione: 2016

The course aims at introducing the students to the fundamental aspects characterizing the discipline of Electronics for microsystems. In particular, the course deals with the fundamental concepts of electronic processing of information, both analog and digital, focusing also on the examination of the physical behavior of analog and digital components and circuits, so that the student can evaluate their influence on real system performance (amplification, frequency response, speed, power dissipation…). For this reason, during the course the basic concepts on the working principles of elementary electronic devices (e.g., diodes, transistors) will be reviewed.
The course is divided into two modules ("Module 1: Fundamentals of Electronics - Analog" and "Module 2: Fundamentals of Electronics - Digital"), the first module is a prerequisite for the second one.

At the end of the course, the student:
Will have a solid understanding of the operating principles of basic analog and digital circuits using amplifying stages made of transistor, operational amplifiers and logic gates (DD1).
Will be capable to select the correct analysis techniques and to perform the useful approximation required to analyze the behavior of elementary analog and digital circuits. (DD1 and DD2).
Will be able to analyze an amplifier circuit, an elementary or complex CMOS logic gate, or simple acquisition chains using analog/digital converters (DD2).

Program of the theoretical and exercise lessons:
The main topics discussed during the course are:
1. Electronic Systems (Module 1)
1.1. Signals: real generators and sensors. Representation in the time domain and frequency components. Analog and digital systems.
1.2. Review of the first-order analysis of linear networks in the time and frequency domain.
2. Electronic Devices (Module 1)
2.1. Basics of semiconductors: dopants, carriers.
2.2. Diode: ideal characteristics in static conditions, use as a rectifier
2.3. MOS transistor: ideal characteristics in static conditions, use as switch and amplifier.
2.4. Amplifier stages based on single transistors
3. Analog Electronics (Module 1)
3.1. Operational amplifiers (OA): ideal characteristics, linear operation; comparator.
3.2. Negative reaction: concept of virtual ground, inverting and non-inverting configurations.
3.3. Circuits with real OA for addition, difference, integration, derivation and filtering of waveforms.
4. Positive Feedback Circuits (Module 2)
4.1. OA with positive reaction: Schmitt trigger and oscillators.
5. Analog/Digital Conversion (Module 2)
5.1. General concepts on sampling process: reconstruction criteria, spectrum and equivocation.
5.2. Sample&Hold: circuit made of discrete components, parameters and errors.
5.3. Analog to digital converters (ADCs): examples of internal structure, quantization, resolution, precision and accuracy.
5.4. Digital to analog converters (DACs): examples of internal structure, errors and non-linearities.
6. Digital Electronics (Module 2)
6.1. General concepts on CMOS logic: static and dynamic performance.
6.2. Combinatorial (decoder, multiplexer) and sequential (flip-flop) components.
7. Electronic noise (Module 2)
7.1. Stochastic VS deterministic quantities
7.2. Possible sources of electronic noise
Exercise classes on circuit simulation software (Modules 1 & 2)
The circuit simulaton activity aims to introduce students to the use of simulation software for circuit analysis (SPICE). During these classes, the basic functioning of the program will be explained, which will then be used to analyze simple circuits and compare the simulated results with the results obtainable with a "pen and paper" analysis. After these classes, the students will be able to self-assess the results obtained in all the other exercises of the course.

Prova scritta obbligatoria, senza prove in itinere
The exam consists of a written test on the entire program of the course. The written test verifies that the student:
understands the operating principles of basic amplifying circuits, CMOS logic gates and analog/digital conversion chains. (DD1)
is able to apply the acquired knowledge and to select the most useful techniques to analyze the behavior of the aforementioned circuits. (DD2)
is able to choose and apply simplified models for the solution of the proposed problem and to verify their reliability. (DD1 and DD2)

Franco Zappa, Elettronica, Editore: EdiSES, Anno edizione: 2016, ISBN: 978-8879598972
Note: Italiano
R. Jaeger, T. Blalock, B. Blalock, Microelettronic Circuit Design (VI edition), Editore: McGraw-Hill, Anno edizione: 2023, ISBN: 978-1260597851
Note: (English)

Durante il corso noi:
esamineremo i fondamenti della strategia e delle tattiche degli stati (I)
ci focalizzeremo sulla geopolitica delle potenze che stanno plasmando l'ordine mondiale (I)
identificheremo le determinanti chiave e gli schemi ciclici dell'ascesa e della caduta del potere politico ed economico-industriale delle potenze più rilevanti (II)
descriveremo l’evoluzione multipolare della globalizzazione, la competizione su IA, risorse strategiche e infrastrutture (III)
analizzeremo il posizionamento e le priorità strategiche dell’Italia e dell'Unione Europea nello scacchiere internazionale (IV)
ascolteremo testimonianze di militari e manager di aziende multinazionali, esperti di energia, difesa e sicurezza
impareremo utilizzando casi di studio in diverse situazioni reali

Al termine del corso lo studente sarà in grado di:
riconoscere le priorità che determinano il processo decisionale degli stati
valutare l'impatto dei conflitti di potere sulla resilienza multidimensionale dei paesi
riconoscere la dinamca della competizione globale e le sovrapposte crisi di questi anni 2020
verificare la solidità delle evidenze quantitative su cui si fondano le decisioni strategiche
valutare le priorità di intervento per l'autonomia strategica dell'Unione Europea e dell'Italia, a partire dalle dipendenze delle filiere industriali

Il corso sarà articolato in quattro moduli didattici, arricchiti da seminari tenuti da esperti su tematiche specialistiche di Defence & Security. I temi verranno affrontati attraverso principi causa/effetto e forniranno una visione trasversale ai contenuti ingegneristici degli studenti della LM in Ingegneria Meccanica ed Ingegneria Informatica.
Il corso è di natura multidisciplinare ed a livello metodologico integra:
l’ approccio analitico qualitativo, basato su casi specifici della geopolitica, come sviluppato da John J. Mearsheimer (docente alla University of Chicago, uno dei più famosi scienziati politici viventi);
l’ approccio statistico-quantitativo, basato sui cicli di sviluppo e declino della potenza delle nazioni, come sviluppato da Ray Dalio (fondatore di Bridgewater Associates e GMO, il più grande hedge fund Global Macro del pianeta);
l’approccio esperienziale attraverso esercitazioni su casi pratici e testimonianze di esperti di altissimo livello, provenienti dai settori industriali strategici, dalla Difesa e dalla ricerca scientifica.
Descrizione dei quattro moduli didattici
1) Come pensano gli Stati: elementi fondamentali di analisi geopolitica con focus sulle logiche di competizione tra grandi potenze
2) Come e volvono le potenze: relazioni causa/effetto, cicli di sviluppo/declino, indici anticipatori, con focus su USA e Cina in rapporto al resto del mondo
3) Come sta cambiando l’ordine mondiale: multipolarità, competizione su IA, su risorse strategiche e infrastrutture
4) Europa al bivio e il caso Italia: una piattaforma strategica e contesa, in mezzo a due oceani
Esempi degli argomenti oggetto delle testimonianze di esperti negli anni accademici precedenti ed il profilo indicativo dei relatori
Industria Aerospaziale e opportunità per l’Italia _ Responsabile per l'internazionalizzazione e la promozione dell'industria spaziale nazionale presso ASI, Agenzia Spaziale Italiana
Sicurezza Attività Spaziali _ Generale, Ingegnere, in forze al Comando delle Operazioni Spaziali, presso lo Stato Maggiore della Difesa
Sicurezza Europea ed Italiana _ Generale, Ingegnere, già Capo di Stato Maggiore dell’Aeronautica e della Difesa
Sicurezza Energetica _ Responsabile Sicurezza Risorse Naturali di ENI, ottavo gruppo petrolifero a livello mondiale e azienda di massima rilevanza strategica per l’Italia
Industria della Difesa e prosperità nazionale _ Vice Presidente Pianificazione Commerciale di LEONARDO, player globale high-tech nei settori dell'Aerospazio, della Difesa e della Sicurezza
Industria navale e sottomarina _ Chief Innovation Officer di FINCANTIERI, uno dei più importanti complessi cantieristici al mondo, attivo in tutti i segmenti della navalmeccanica ad alto valore aggiunto e dual-use.

Prova orale obbligatoria
L’esame è basato su una discussione orale degli argomenti trattati durante il corso e si terrà conto positivamente della partecipazione attiva a tutte le lezioni e testimonianze.

Prof. Alessandro Pozzi, Slide relative al corso, materiali aggiuntivi e selezione contributi audio-video webeep
Note: Le dispense sono il principale supporto obbligatorio, fornito prima di ogni lezione; nella pagina webeep trovi in via facoltativa: Risorse Didattiche (approfondimenti e documenti ufficiali), Registrazioni (laddove disponibili) ed infine Seminari geopolitica extra curricolari (analisi e podcast).
John J. Mearsheimer Sebastian Rosato, How States Think, Editore: Yale University Press, Anno edizione: 2023, ISBN: 978-0-300-26930-7
Note: Elementi fondamentali descritti nelle dispense del corso. Focus del testo su: capitoli 1, 2, 3, 5 (caso USA egemonia Liberale), 8.
Draghi, Mario, The future of European competitiveness Part A: A competitiveness strategy for Europe, Editore: European Commission, Anno edizione: 2024, ISBN: 978-92-68-22716-9 https://commission.europa.eu/topics/competitiveness/draghi-report_en
Note: Il report Draghi 2024 definisce una strategia UE per la competitività basata su innovazione digitale, decarbonizzazione industriale e sicurezza economica. Il documento evidenzia la necessità di colmare il divario con USA e Cina, riducendo i costi energetici e rafforzando la difesa comune
Ray Dalio, I principi per affrontare il nuovo ordine mondiale, Editore: HOEPLI, Anno edizione: 2022, ISBN: 978-88-360-0018-0 https://commission.europa.eu/topics/competitiveness/draghi-report_en
Note: Elementi fondamentali descritti nelle dispense del corso. Focus testo: capitoli 1, 2, 3, 5, 6, 13 + appendice statistica aggiornata nei materiali didattici webeep per pronto riferimento sui punteggi relativi a condizioni e prospettive dei 24 principali paesi.
Relazione Annuale dell'Intelligence 2026 https://www.sicurezzanazionale.gov.it/cosa-facciamo/relazione-annuale
Note: La Relazione 2026 sulla politica dell'informazione per la sicurezza, elaborato dalla comunità intelligence nazionale, presenta il quadro di riferimento per comprendere l'evoluzione delle minacce, individuare le vulnerabilità dei sistemi e rafforzare la capacità di prevenzione e governo rischi.
Draghi, Mario, Competere o sparire. Per un nuovo paesaggio europeo., Editore: Rizzoli, Anno edizione: 2026, ISBN: 9788817198752
Note: Il testo fotografa l'Europa schiacciata tra dinamismo tecnologico USA e massiccia scala industriale Cinese: amplia il Rapporto sulla competitività UE evidenziandone i ritardi: frammentazione normativa, scarsa innovazione digitale, dipendenza energetica e mancanza di investimenti coordinati.
M. Vellano, A. Miglio, Sicurezza e Difesa Comune dell'Unione Europea, Editore: CEDAM, ISBN: 9788813379834
Helen Thompson, Disorder, Hard Times in the 21th century, Editore: Oxford University Press, Anno edizione: 2022, ISBN: 978-0-19-886498-1
Note: Il testo analizza le crisi del XXI secolo collegando geopolitica, economia ed energia. Il saggio spiega come la dipendenza dal petrolio, l'instabilità finanziaria e le fratture democratiche abbiano generato l'attuale disordine globale, con l'Europa schiacciata tra le grandi potenze.
Nigel Inkster, The Great Decoupling China, America and the Struggle for Technological Supremacy, Editore: Hurst, Anno edizione: 2020, ISBN: 9781787383838

The course is conceived as an experiential based learning process, where students acquire frameworks, models and tools to develop their business mainly from the experience and advising of practitioners, i.e. entrepreneurs, venture capitalists, business angels, incubator/accelerator’s managers, with whom the course is designed. The faculty will provide a core of preliminary concepts through frontal lectures on high-tech start-ups’ creation and funding, after that the students will start to work in teams on their own business models, receiving inputs and feedbacks from practitioners, who participate as guest speakers, and throughout tutoring sessions.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand and design solutions, applying a scientific and engineering approach, in relation to the setting up of a new business, the design of its business model, and the identification of the proper funding channels
Interact in a professional, effective and constructive way in teams and with external practitioners

At the end of the course, the students will be able to:
Comprehend the functioning of the entrepreneurial ecosystem
Understand what is a business model and its building blocks
Identify the key challenges for the creation of high-tech start-ups and the funding mechanisms available, and understand when it is appropriate to use each of them, according to the specific start-up’s industry, funding requirements and stage of the life cycle.
Through the project work, the students will also be able to:
Test and validate the business model in the real world with potential customers
Write an effective business proposal to ask for funding (i.e., to business angels, venture capitalist, incubator programs..)
Effectively work in teams
Interact with practitioners of the financial sector
Summarize and present the results achieved in the business proposal in front of potential investors clearly and convincingly.

Introductory event: startup success stories and introduction to the course
Startups: the reference strategic framework - external and internal analysis
Startups: the reference strategic framework - value proposition canvas and business model canvas
Getting external resources: hiring, strategic alliances and financing (video clips)
Lean startup approaches

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students must identify a new business idea based on an innovative technology (e.g., the result of current scientific research) or an innovative way of doing business in an incumbent business (e.g., an innovative business model), form an entrepreneurial team, create a document describing the business model and prepare an "elevator pitch".
The grades will be assigned through:

• the evaluation by the faculty of the document describing the business model;
• the evaluation by a commission including faculty members and practitioners of an "elevator pitch" aimed at presenting the business model.
  In the exam, the students must show that:
  They have a good comprehension of the challenges in creating and funding a new start-up and how financial intermediaries and other actors of the financial ecosystem may support the start-up’s development
  They understand how the business model is articulated, and are able to properly build one, tailored to their business idea
  They have effectively validated the business model developed, in the real world, and they are able to select the appropriate funding channels
  They are able to summarize and communicate the key concepts of their business model in a public context.
  During the tutoring sessions, as well as in the exam, the students must also show that:
  They are able to effectively work in teams
  They are able to take advantage of the advise provided by practitioners and guest speakers.

The course aims at giving the students the necessary knowledge and technical competences to critically approach the design of industrial plants. In particular, the course is focused on the identification and the assessment of different planning solutions in the three phases of the planning process: industrial facilities design, realization and operation, with a particular focus on their interactions. Most of the topics will be integrated with the discussion of case studies and practical examples.
The course will delve deeper into problems and issues related to:
the planning of complex industrial projects, layout design, and feasibility study in the plant engineering area;
the management of production and logistics, the management of maintenance of industrial assets, and the automation of logistics-production systems.
The course targets the following goals, within the broader context of the programme and relating to industrial plants and facilities, so as to empower the student capabilities to:
understand context, functions, processes and performance;
design solutions applying a scientific and engineering approach.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
Define a problem and its issues
Identify appropriate methods, relevant parameters, key data and assessment criteria
Collect data and information
Interpret and discuss the outcomes.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
Apply theoretical methods to industrial cases
Demonstrate the ability to select relevant data and information for solving the problem and getting the required outcome.
Through in-class discussions about real cases and an elective project work, students will also acquire the skills to formulate a judgment, meaning to identify, select, analyse, classify and connect data in order to formulate possible solutions and rate them compliantly with the assessment criteria.

The course contents are delivered through lectures and exercise sessions, based on guided or autonomous development by the students.
The course covers the following topics divided in modules as per the following description.
Module 1 - Industrial plants
1.1 - introduction and general concepts
Module 2 - Feasibility study
2.1 - market analysis
2.2 - production systems design
2.3 - capability
2.4 - cost analysis
2.5 - investment appraisal
2.6 - risk and sensitivity analysis
Module 3 - Industrial layout
3.1 - product analysis
3.2 - material flows and relationship analysis (rel-charts)
3.3 - layout planning
3.4 - Muther model
Module 4 - Location problem
4.1 - contextual factors
4.2 - strategic directions
4.3 - methods and criteria
Module 5 - Strategy of operations
5.1 - strategic priorities
5.2 - how to set an operations strategy
5.3 - competitive goals of a production system
Module 6 - Quantitative methods for industrial plants design
6.1 - simulation as a tool for industrial plants design (from concept to detailed design)
6.2 - Discrete Events Simulation (DES)
Module 7 - Occupational Health and Safety
7.1 - principles
7.2 - risk assessment and management techniques
7.3 - OHS management
7.4 - principles and techniques for system safety
Module 8 - Industrial storage and material handling systems
8.1 - conveyors and loading systems
8.2 - trucks and Automated Guided Vehicles (AGV)
8.3 - traditional storing systems
8.4 - how to design a traditional (not automated) warehouse
Module 9 - Air conditioning and heating systems
9.1 - criteria for designing
9.2 - human body thermal balance
9.3 - thermal environment assessment
Module 10 – Project management
10.1 - introduction to project planning and control
10.2 - Engineering, Procurement, Construction companies (EPC contractors), their organization and business models
The contents of the Industrial Plants B course are those until Module 6 - Quantitative methods for industrial plants design (included ).

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will get a pass mark after successfully taking a combination of (eventually) three different tests: written exam (mandatory), oral exam and oral presentation. The exam is aimed to assess:
Knowledge and understanding
Ability to apply knowledge and understanding
Autonomy of judgement (in case of oral exam)
Communication skills
Learning ability (in case of oral presentation)
Written exam (mandatory)
Via this exam, it will be possible to test students’ acquired knowledge and understanding and the application of acquired knowledge and understanding.
The written exam consists of a set of questions to answer (in order to check knowledge and understanding) and quantitative problems to be solved (in order to check application abilities); their assessment equally takes into account the formal development and the quantitative/qualitative content, so as to appraise the capability of each student to:
identify the relevance of either contextual factors, or functions or processes with respect to the performance of a project, or of a plant as a whole, or of a single component;
set up and solve a problem related to a project, or to plant as a whole, or to a component.
The exam is an individual test developed through three sections:
multiple choice theoretical questions: the student must answer correctly at least 66% of them in order to go on with the exam (otherwise he/she gets a fail-mark),
open-ended theoretical question(s),
numerical problems (at least two exercises for Industrial Plants A and one for Industrial Plants).
Oral exam (based on the result of the written exam)
Via this exam, it will be possible to fine tune the mark taken in the written exam. The decision about the oral exam is up to the professor only, based on the result of the written exam.
Oral presentation
Via this elective activity, it will be possible to submit an individual or group (up to three students) elective project work about one of the topics of the course (given by the professor), so to contribute to the final grading.
Final Grading
To pass the course, students must get a pass mark given by the written exam, eventually integrated with an oral exam (based on a decision by the professor), and the additional points (up to 2/30) of the oral presentation (elective project work).

Industrial Plants - Compendium, Editore: Wiley&Sons, Anno edizione: 2021, ISBN: 9781119922568
W.Behrens, P.M.Hawranek, Manual for the Preparation of Industrial Feasibility Studies, Editore: UNIDO, Anno edizione: 1991, ISBN: 9211062691
Benjamin O. Alli, Fundamental Principles of Occupational Health and Safety (2nd edition), Editore: ILO, Anno edizione: 2008, ISBN: 9221204545

Il corso è volto a preparare lo studente a gestire la misurazione delle quantità meccaniche e, in generale, fisiche più comuni utilizzate per il monitoraggio e il controllo dei sistemi bioispirati e bionici. Sarà inoltre fornito un focus sulla misurazione dei principali parametri fisiologici. Una parte rilevante del corso consiste in attività sperimentali. Gli studenti avranno l'opportunità di lavorare praticamente con sensori e sistemi di misurazione tipicamente applicati al corpo umano e ai sistemi bionici, e di eseguire autonomamente l'acquisizione e l'analisi dei dati.

The course aims to prepare students with an extensive know-how about principles of operation of internal combustion engines and to provide the skills required to develop and manage engineering projects involving selection, operation, design and optimization of i.c. engines.
Particular attention is paid to the fluid dynamics, combustion, energy and environmental aspects of engines used in the transportation sector as well as in the off-highway, heavy-duty and marine sectors. The subject is offered in four configurations: the full 10-cfu course and three 5-cfu modules – Fundamentals, Advanced and Marine Propulsion – so that students can focus on the aspects most relevant to their curriculum.

By the end of the course, students will learn contents and practices according to what is defined in the learning objectives.
Lectures will provide the basis for basic knowledge to understand all the key aspects involved in the design of conventional and innovative i.c engines used in both transportation and off-road sectors.
In terms of acquired knowledge and understanding, students will be able to:
evaluate all relevant parameters of an i.c. engine which define its architecture and operation for automotive applications (all configurations) and for off-highway, heavy-duty and marine applications (10-cfu course and Marine Propulsion module);
master the fundamental concepts of the gas exchange process and charge motions in engines and apply them for design and optimization purposes;
know the fundamentals of fluid-dynamic engine modelling (10-cfu course only);
describe the combustion in spark ignition and compression ignition engines and assess the influences of the most important operating parameters on the engine performance;
know deeply the mechanisms of pollutant emission formation and in-cylinder and after-treatment solutions to reduce the environmental impact and comply with the vehicle exhaust emission testing procedures;
have a good background in the control of gas-dynamic noise and select and/or design the optimal silencers for a given engine (10-cfu course and Advanced module);
demonstrate an understanding of challenges related to future technological developments of i.c. engine for powertrain from the fluid-dynamic, chemical and thermal point of view and the potentialities of different levels of electrification.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
apply the fundamental concepts of the gas exchange process and charge motions in engines and for design and optimization purposes;
define the requirements and suggest the preferred layout for the fuel injection and combustion systems in SI and CI engines;
assess the advantages of turbocharged versus natural aspirated engines and propose the best configuration depending on the field of application;
classify, from the chemical and physical points of view, the conventional and alternative fuels for engines (10-cfu course, Advanced and Marine Propulsion modules);
evaluate the impact of different after-treatment systems (all configurations) and the emission performance of the vehicle over dynamic RDE cycles (10-cfu course only);
select and/or design the optimal silencers for a given engine (10-cfu course and Advanced module).
After completing the laboratories students will:
have a good practical familiarity with the main engine components
have knowledge about the potentialities and field of application of using a simulation tool for engine performance and emissions
have a good familiarity with the use of 1D fluid-dynamic tools for a preliminary engine design (10-cfu course only).
Furthermore, through an assigned group project to be delivered at the end of the course, students will gain the ability to work in team and make some preliminary experiences on a virtual engine by means of numerical tools for a deeper understanding of some aspects that were theoretically discussed in the lectures (10-cfu course only).
Finally, students will improve their communication skills, being able to integrate in their background a fundamental fluid-dynamic and thermal knowledge, which is mandatory for a mechanical engineer who has to work in the automotive sector in any possible field of operation.

The course contents are delivered through lectures.
The course is offered in four configurations – the full 10-cfu course and the 5-cfu Fundamentals, Advanced and Marine Propulsion modules. The topics are organised in the modules listed below; for each module the configurations in which it is taught are indicated.
Fundamentals of IC Engines
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion.
Classification and application areas of internal combustion engines. Geometric and kinematic parameters; effective torque and power; indicated cycle and organic efficiency; ideal thermodynamic cycles; air/fuel ratio; specific fuel consumption; cylinder volumetric efficiency and relations between the characteristic parameters. Engine operating characteristics: torque and power curves, engine matching and fuel-consumption maps. Exercise on SI-engine performance.
Gas Exchange in Four-Stroke Engines
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion.
Gas exchange processes in IC engines and determination of the cylinder volumetric efficiency. Flow through poppet valves: flow areas and discharge coefficients, maximum valve lift, valve diameter, influence of geometric details and valve-timing diagrams; variable valve timing (10-cfu course and Advanced). Exercise on valve design for a four-stroke engine.
Air Induction in Two-Stroke Engines
Configurations: 10-cfu course, Advanced, Marine Propulsion.
Scavenging process and port configurations. Global scavenging parameters and port flow coefficients. Analysis of actual scavenging processes; port and manifold design; optimum choice of the scavenging efficiency; scavenging pumps.
Intake and Exhaust Systems – Unsteady Flows
Configurations: 10-cfu course, Fundamentals (intake and exhaust manifolds also in Advanced).
Functions of the intake and exhaust systems. Unsteady flows in the pipes: inertial effects and wave actions, with examples of dynamic-effect exploitation. Intake and exhaust manifold design (10-cfu course and Advanced). Exercise on dynamic effects in a four-stroke engine.
Supercharging and Turbocharging
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion (automotive turbocharging in the 10-cfu course and Advanced).
Methods of supercharging. Energy of the exhaust gases; constant-pressure and pulse turbocharging; e-boosters and electric turbochargers. Turbocharger matching, engine transient response and automotive turbocharging – twin-scroll and variable-geometry turbines (10-cfu course and Advanced).
Fossil and Renewable Fuels
Configurations: 10-cfu course, Advanced, Marine Propulsion.
Requirements for fuels and fossil-based fuels. Technical properties: stoichiometric air/fuel ratio, heating value and knock rating. Biofuels: bio-alcohols, biodiesel, HVO and biogas. E-fuels: hydrogen, methanol, NH3, DME, e-gasoline and e-diesel. Exercise comparing the contributions of different fuels to CO2 emissions.
Fuel Metering and Injection in SI Engines
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion.
Mixture requirements for SI engines. Fuel-injection systems: classification criteria, GDI and PFI systems and the formation of the fuel-air mixture. Multi-point, single-point and direct-injection systems; dosing regulation by means of O2 sensors.
Fuel Injection in CI Engines
Configurations: 10-cfu course, Fundamentals, Marine Propulsion.
Requirements and functions of the CI injection system and the main injection systems. Common-rail systems and piezo-injectors; fuel injectors and fuel rail. Spray atomization and penetration.
In-Cylinder Charge Motion
Configurations: 10-cfu course, Advanced.
Characterization of the charge-motion fields in the engine cylinder. Organized rotary movements of the cylinder charge: swirl, tumble and squish.
Combustion in SI Engines
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion.
Combustion rate, auto-ignition, flame-front propagation, turbulent and diffusive combustion (10-cfu course, Fundamentals, Marine Propulsion). Spark-ignition combustion of homogeneous and stratified charges: in-cylinder pressure development, energy-release law, cycle-to-cycle variations, abnormal combustion (pre-ignition, knock, CAI and SACI) and combustion-chamber design (10-cfu course and Advanced).
Combustion in CI Engines
Configurations: 10-cfu course, Fundamentals, Marine Propulsion (combustion chambers and HCCI in the Advanced module).
Characteristics of the process and ignition delay: physical and chemical processes and correlations. Premixed and diffusive combustion and the heat-release rate. Direct-injection and pre-chamber combustion chambers and HCCI combustion (10-cfu course and Advanced).
Emission Formation and Control
Configurations: 10-cfu course, Fundamentals, Advanced, Marine Propulsion.
SI-engine exhaust emissions: carbon oxides, unburned hydrocarbons and nitrogen oxides; test cycles; catalytic converters. Diesel-engine emissions: formation and control of gaseous pollutants, exhaust-gas recirculation (EGR) and particulate matter (formation, characteristics and control). After-treatment: particulate filters and NOx reduction. Electric and hybrid vehicles (10-cfu course, Fundamentals and Advanced).
Noise Control
Configurations: 10-cfu course, Advanced.
Fundamentals and definitions. Combustion and mechanical noise; control of gas-dynamic noise. Types of silencers; transmission and insertion loss; TL curves of basic elements and practical silencer design. Exercise on gas-dynamic noise reduction.
Heavy-Duty Engines
Configurations: 10-cfu course only.
Application overview and general requirements: emissions, global markets, environmental conditions and duty cycles. Technical solutions and future developments.
Lubrication
Configurations: 10-cfu course only.
Purpose of lubrication; the oil; the lubrication circuit and its main components; lubrication regimes; experimental tests.
Marine and Naval Propulsion
Configurations: 10-cfu course, Marine Propulsion.
Introduction to maritime transport and propulsion and IC engines for boats. Engine classification for ship propulsion and boat engine types. Engine performance maps, engine matching for ship propulsion and overall propulsion performance. Low-speed two-stroke and medium-speed four-stroke ship engines: engine-propeller coupling, gas exchange, turbocharging, injection and combustion, alternative fuels and emission standards (SOx, NOx, GHG).
Hybrid and Electrified Powertrains
Configurations: 10-cfu course (selected topics also in Marine Propulsion).
Concept and architectures of hybrid electric drive trains: series and parallel configurations (torque-coupling, speed-coupling and combined). Design of series and parallel HEV drive trains: operation patterns and control strategies (Max. SOC-of-PPS, thermostat and engine on-off) and sizing of the major components – traction motor, engine/generator and peaking power source. IC engines for electrified powertrains.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully:
taking a written exam which must be integrated by a mandatory oral exam only in the case of an evaluation higher than 28/30 in the written exam;
The student during the examination must demonstrate:
to have the ability to organize the knowledge of the different topics of the course and the interrelations existing between them;
to have the capacity for critical reasoning on the theoretical concepts that led to the definition of the different technological solutions which have been studied;
to be able to quantitatively determine the main geometrical and operational parameters which are asked in the proposed numerical exercises;
to describe each topic with good technical language properties and adequate synthesis and linearity.
to design a new engine with specified target of performances, field of application and given constrains.
Final Grading
Evaluations at all exam dates will consist of:
a first part with 10 multiple-choice questions on fundamental theoretical topics
a second part with open theoretical and numerical questions
a mandatory oral to complete the exam only for the highest marks (>28)
optional: deliver of a year's project which awards 2 extra bonus points

FERRARI G., D'ERRICO G., ONORATI A., Internal Combustion Engines, Editore: Esculapio, Anno edizione: 2022, ISBN: 9788893853064

The course aims to provide the students with the necessary tools for the design and assessment of machine components, both under static and fatigue loading. The basics of mechanical design are upgraded in order to include advanced theory of elasticity, finite element analysis, design methods for static and fatigue loads and tools for assessing the influence of defects on static and fatigue strength.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
examine and perform the design and assessment of machine components subjected to static and fatigue loading.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
solve practical design applications by using different tools (analytical and numerical) and critically analyze the results.
Students will also acquire the skills to formulate a judgment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss the results.
Furthermore, through the assigned case studies, students will gain the ability to autonomously design and assess mechanical components subjected to static and fatigue loadings.

The course contents are delivered through lectures, exercise courses, lab activities. The course covers the following topics as per the description below:
Cyclic response of materials: high cycle fatigue, uniaxial low cycle fatigue (cyclic behaviour and strain based approach to fatigue)
Linear Elastic Fracture Mechanics: stress intensity factor, KIC, fatigue crack propagation.
Life assessment methods of components and products under a complex stress states, multiaxial high cycle fatigue (critical plane and stress invariants approaches), multiaxial low cycle fatigue (strain based criteria, energetic approach, critical plane approach).
Finite element modelling: basic formulation, definition of stiffness matrix, main shape functions, selection of element types, load and boundary conditions, evaluation of results.
Relevant example of Machine design applications.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Students will pass the course after successfully take written test with exercises and oral test with theoretical questions. Both the tests are mandatory.
Written test with exercises. Via this exam, it will be possible to test students’ capability of application of the design tools to practical cases regarding machine components and systems.
Oral test with theoretical questions. Via this exam, it will be possible to test students’ knowledge and understanding of the theoretical topics included in the program.
Final Grading. To pass the course, students must successfully pass the tests with a minimum mark for both.

N. E. Dowling, Mechanical Behavior of Materials, Editore: Person
D. Socie, G. Marquis, Multiaxial Fatigue, Editore: SAE International, ISBN: 978-0-7680-0453-3
J.E. Shigley et Al, Mechanical Engineering Design, Editore: McGraw-Hill

The course aims to provide the students with the necessary tools for the design and assessment of machine components, both under static and fatigue loading. The fundamentals of mechanical design are enhanced to encompass the theory of elasticity, finite element analysis, design techniques for static and fatigue loads (including multiaxial), and methodologies for evaluating the impact of notches on static and fatigue strength. These methodologies and techniques will be employed in practical instances, where numerical models play a pivotal role.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to:
examine and perform the design and assessment of machine components subjected to static and fatigue loading.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
solve practical design applications by using different tools: analytical, numerical, experimental (to be confirmed during the course), and critically analyze the results.
Through activities based on Finite Element Method applications, students will also acquire the skills to formulate a judgment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss the results.
Furthermore, through the assigned case studies, students will gain the ability to autonomously design and assess mechanical components subjected to static and fatigue loadings.
Finally, students will improve their communication skills, being able to write final technical reports for the case/s study.

The course contents are delivered through lectures, exercise courses, lab activities.
The course covers the following topics as per the description below:
Stress-strain analysis in plastic field - Notched members and plasticity in bending
Finite element modelling: basic formulation, definition of stiffness matrix, main shape functions, selection of element types, load and boundary conditions, evaluation of results.
Cyclic response of materials: high cycle fatigue, endurance limit, fatigue strength, modifying factors, stress concentration and notch sensitivity, multiaxial fatigue.
Linear Elastic Fracture Mechanics: energy approach (Griffith), stress intensity factor, KIC, fatigue crack propagation.
Basic principles of Welding and the Design of Permanent Joints.
Basic rules for writing a FEM report.
Relevant example of Machine design applications close to the fields of Micro-Nano, Defense and Security and Material design will be discussed during the course.
Laboratory activities: experimental activities on mechanical components
Laboratory activities: numerical modelling lab

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The student will pass the course after successfully take a mandatory written or oral test with theoretical and applicative questions covering all the topic of the course.
Via this exam, it will be possible to test students’ capability of application of the design tools to simple practical cases regarding machine components and systems and/or to test students’ knowledge and understanding of the theoretical topics included in the program.
The student will have to deliver a mandatory report of a "case/s study": this work consists in preparing a report that describe some activities carried out during the computer laboratory and/or new projects (details will be provided during the course); in both the cases the main topic of the report will be FE modelling. This report will make it possible to evaluate:
The ability to understand the most appropriate choice of the FEM model to be adopted;
The ability to build the finite element model;
The ability to interpret the load and constraint conditions and apply them appropriately;
The ability to formulate assessments independently through the choice of results to be reported because they are significant in demonstrating the structural behavior of the component;
The ability to communicate contents through the drafting of a technical report that include all the points previously indicated.
Final Grading
To pass the exam, students must pass the written exam and submit the report of the "case/s study” which will also be evaluated. The final assessment will be defined by evaluating a maximum of 10 points for the result of the written/oral test and a maximum of 20 points for the report. At the discretion of the teacher, an oral discussion of the presented report may be requested. The report has to be submitted prior the written or oral test; the possibility to prepare the report inside a small team will be discussed during the course. Once submitted, the report is understood to be valid for the entire academic year.

N. E. Dowling, Mechanical Behavior of Materials, Global Edition 5th Edition, Editore: Person, Anno edizione: 2019
J.E. Shigley et Al, Mechanical Engineering Design, Editore: McGraw-Hill, Anno edizione: 2011
A.C. Ugural and S. K. Fenster, Advanced Mechanics of Materials and Applied Elasticity
Lecture notes of the teacher available on Polimi Webeep

The course has the purpose to advance the bachelor class “Costruzioni di Macchine” and to provide the students with tools that will be used in a wide range of applications. The course addresses master students, and some of the theories presented during bachelor will be deepened and extended.
Theory of elasticity is extended to cover components of practical interests like e.g. pressure vessels and rotating disks and cylinders.
An introduction on composite materials will be delivered.
Finite elements and numerical computing softwares will also be used to provide the students with useful tools to tackle and solve complex engineering problems, of common use in the industry.
Mechanical design will be updated in order to cover the theory of fracture mechanics and to deliver the tools necessary to assess the influence of defects on static and fatigue strength. Introduction of Low-cycle fatigue will also be delivered.
Eventually if the possibility will arise, a company-joint project will be proposed to the studentes. The class will be split into groups, each one of them shall solve the same problem proposed by the company. In case the project will not be activated, two lectures on welding design will be activated instead.

Lectures and exercise sessions will allow students to learn the content defined in the learning objectives.
In terms of acquired knowledge and understanding, students will be able to (DdD1):

• examine and perform the design and assessment of machine components subjected to static and fatigue loads;
• approach simple design of components made with composite laminated material;
• perform simple numerical statical analysis.
  In terms of ability to apply the acquired knowledge and understanding, students will be able to (DdD2):
• solve practical design problems by using analytical and numerical tools, and critically analyse the results;
• set up a numerical simulation of mechanical components loaded with static loads.
  In terms of DdD3 to DdD5, the student will be able to:
• acquire the skills to formulate a judgment of the stress state of a component possessing analytical and numerical tools to make accurate evaluations (DdD3);
• autonomously present results in front of technical personnel, colleagues, and the professor (DdD4)

The course contents are delivered through lectures and exercise sessions.
The course covers the following topics divided in modules as per the description below:
Module 1: Structural analysis:
Axisymmetric problems: thin and thick cylinders loaded by internal and external pressure and centrifugal loads.
Module 2: Strength of materials and assessment criteria:
Linear Elastic Fracture Mechanics: energy approach (Griffith), stress intensity factor, fatigue crack propagation, Low Cycle Fatigue
Module 3: Composite materials:
Laminate theory and stress-strain relations for orthotropic materials.
Module 4: Introduction to Abaqus
Software skills: Software-Aided-Design to solve practical engineering problems by means of commercial softwares.
Module 5: Welding design (Depending on the activation of a pratical project with a company)
Design of fillet- and butt-welding.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i condizionato (a scelta del docente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully take written test with exercises and oral test with theoretical questions and/or discussion of the written exam. Both the tests are mandatory.
Written test with exercises
Via this exam, it will be possible to test students’ capability of application of the topics developed during the class to practical cases regarding machine components and systems.
Oral test
Via this exam, it will be possible to test students’ knowledge and understanding of the topics included in the program.
Matlab (or equivalent) script
The studens will be required to bring a script for the computation of stresses and strain on sinple laminate structures.
Report (to be decided)
Depending on the number of students, it might be possible to propose small projects to be discussed together and developed with the proposed software. In this case a report will be required and evaluated.

https://webeep.polimi.it/login/index.php
Note: Lecture notes of the teacher available on Polimi WeBeep
J.E. Shigley et Al,, Mechanical Engineering Design, Editore: McGraw-Hill, ISBN: 978-00-7123-270-8
J. N. Reddy, A. Miravete, Practical analysis of composite laminates, ISBN: 978-08-493-9401-0
E.J. Barbero, Introduction to composite materials design, ISBN: 978-14-200-7915-9

The course presents methodologies for the analysis of automotive part features and the subsequent identification of the most suitable manufacturing and assembly technologies in automotive production. At the end of the course, the student will be able to make decisions on early-stage process selection considering technological, economic, and sustainability factors to identify the most suitable manufacturing technology. Special focus will be dedicated to process signatures and capabilities, production inherences, expected lifecycle costs, as well as design requirements.

After completing the course, the student will be able to:
·Assess an industrial manufacturing project for automotive parts including also environmental and cost factors - capability of knowledge and understanding (DdD1).
·Select manufacturing technologies for newly developed automotive parts - capability of applying knowledge and understanding (DdD2), capability of making judgements (DdD3)
·Communicate the selection results through a written report and an oral discussion - capability of communication (DdD4)

The course consists of three fundamental modules:
Process and system selection module: methods to assess and screen manufacturing technologies and general approaches for evaluating technology potentials in different automotive manufacturing scenarios from small batch size to mass production taking into account the process signatures and assembly tolerance chain.
Cost prediction module: economic evaluation of the components in the previously identified different manufacturing scenarios with cost analysis
Eco audit module: Assessment of the impact of the process and technologies selection outcomes over the overall lifecycle of the transport systems, before and after production of the components including the quantification of the technology’s advantages, e.g., lightweight design.
The electric vehicle serves as an application example and applicative case studies to introduce and apply the methodology developed in the three modules. Two different sub-assembly are considered in the case studies. In the case studies students will communicate with experts from automotive industries.
The course concludes with a general evaluation of the results of the methodology in preventing efficiency losses that occur when developing a component according to technologies and production processes that are subsequently identified as unsuitable.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The students will work on the project work in groups. The project work will be based on case studies and will be resolved using the methods taught of the course. The projects will recieve a grade for each group. Each student will discuss the contents of the submitted project during as well as the theory taught during the course within the oral exam. The final mark will be based on the project grade (50%) and the oral exam performance (50%).

Michael F. Ashby, Materials Selection in Mechanical Design, ISBN: 978-1-85617-663-7 https://www.sciencedirect.com/book/monograph/9781856176637/materials-selection-in-mechanical-design#book-info
K. G. Swift, J. D. Booker, Manufacturing Process Selection Handbook, ISBN: 9780080993577 https://shop.elsevier.com/books/manufacturing-process-selection-handbook/swift/978-0-08-099360-7
Michael F. Ashby, Materials and Sustainable Development, ISBN: 978-0-08-100176-9 https://www.sciencedirect.com/book/monograph/9780081001769/materials-and-sustainable-development
K. G. Swift, J. D. Booker, Process Selection From Design to Manufacture, ISBN: 9780080474007 https://shop.elsevier.com/books/process-selection/swift/978-0-7506-5437-1
Helmut Hügel, Thomas Graf, Materials Processing with Lasers Fundamentals and Procedures, ISBN: 978-3-658-50896-8 https://link.springer.com/book/10.1007/978-3-658-50896-8

The design and management of manufacturing and de-manufacturing systems call for methods devoted to the performance evaluation and optimization of system configuration and control. In the scope of the new needs dictated by the twin transition digital and ecological, this course deals with mathematical models of manufacturing/de-manufacturing systems aimed at evaluating their performance and optimizing their configuration and control. Different mathematical models are studied and applied based on the characteristics of various systems.
The goals of the course are:
Identify trends, technologies and key methodologies in the industrial domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
The methodologies studied in the course will be applied within the Project lab to a real case study. The Project lab is part of the innovative didactics program of Politecnico di Milano.

After passing the exam, the student will be able to:
Analyse production problems and devise the requirements for manufacturing/de-remanufacturing systems;
Develop models of manufacturing/de-remanufacturing systems based on a mathematical representation of their characteristics and behaviour and according to the required level of detail;
Identify, select, and manipulate mathematical methodologies to support the design, management and control of manufacturing/de-remanufacturing systems;
Design the configuration and control of manufacturing/de-remanufacturing systems and estimate their performance.
After completing the Project work, the student will be able to:
Write a technical project report;
Analyse production data from complex manufacturing systems to extract relevant performance metrics and use it to validate mathematical models;
Present the results achieved during the analysis, modelling and testing activities.
The course is based on lectures, classworks, project work and optional activities. Guest international speakers will be invited to give special lectures.

Technical design of Manufacturing/de-remanufacturing systems. Relations between technological specifications and production system types. State-based modelling of manufacturing/de-remanufacturing systems. Continuous-time Markov chains to model simple manufacturing/de-remanufacturing systems. Analytical methods (queueing networks) to model complex systems and estimate key performance indicators. Approximate analytical methods to model unreliable manufacturing/de-remanufacturing systems and evaluate their performance. Decomposition techniques to evaluate the performance of long flowlines.
Design of Manufacturing/de-remanufacturing Systems Control. Optimization of token based production policies. Hedging point policies with applications to energy-saving policies and de-remanufacturing control policies.
Analysis of real manufacturing/de-remanufacturing systems.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The assessment will be based on a final exam (70% of the assessment) and the evaluation of the Project Work reports (30% of the assessment). Project Work reports are required during the semester and are aimed at assessing the capability of applying the knowledge to a real case. The final exam consists of a written test including practical and theoretical exercises. Practical exercises assess the ability to understand and analyse realistic industrial problems and then create appropriate models based on the learnt methodologies to design manufacturing systems and evaluate the impact of possible reconfigurations. Theoretical exercises request to describe and elaborate on concepts, models, techniques and methodologies presented during the course.
In addition to the mandatory evaluation, students will be given the possibility to improve the final grade through:
an optional oral exam on theoretical and practical questions related to the topics included in the program (max 3 points);
optional seminar work (max 3 points). The work will focus either on the application of a learnt methodology to a real industrial case or the further development of a learnt methodology.
In total, a maximum of 4 points can be added to the grade of the written test.

The design and management of manufacturing and de-manufacturing systems call for methods devoted to the performance evaluation and optimization of system configuration and control. In the scope of the new needs dictated by the twin transition digital and ecological, this course deals with mathematical models of manufacturing/de-manufacturing systems aimed at evaluating their performance and optimizing their configuration and control. Different mathematical models are studied and applied based on the characteristics of various systems.
The goals of the course are:
Identify trends, technologies and key methodologies in the industrial domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
The methodologies studied in the course will be applied within the Project lab to a real case study. The Project lab is part of the innovative didactics program of Politecnico di Milano.

After passing the exam, the student will be able to:
Analyse production problems and devise the requirements for manufacturing/de-remanufacturing systems;
Develop models of manufacturing/de-remanufacturing systems based on a mathematical representation of their characteristics and behaviour and according to the required level of detail;
Identify, select, and manipulate mathematical methodologies to support the design, management and control of manufacturing/de-remanufacturing systems;
Design the configuration and control of manufacturing/de-remanufacturing systems and estimate their performance.
After completing the Project work, the student will be able to:
Write a technical project report;
Analyse production data from complex manufacturing systems to extract relevant performance metrics and use it to validate mathematical models;
Present the results achieved during the analysis, modelling and testing activities.
The course is based on lectures, classworks, project work and optional activities. Guest international speakers will be invited to give special lectures.

Technical design of Manufacturing/de-remanufacturing systems. Relations between technological specifications and production system types. State-based modelling of manufacturing/de-remanufacturing systems. Continuous-time Markov chains to model simple manufacturing/de-remanufacturing systems. Analytical methods (queueing networks) to model complex systems and estimate key performance indicators. Approximate analytical methods to model unreliable manufacturing/de-remanufacturing systems and evaluate their performance. Decomposition techniques to evaluate the performance of long flowlines.
Design of Manufacturing/de-remanufacturing Systems Control. Optimization of token based production policies. Hedging point policies with applications to energy-saving policies and de-remanufacturing control policies.
Analysis of real manufacturing/de-remanufacturing systems.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The assessment will be based on a final exam (70% of the assessment) and the evaluation of the Project Work reports (30% of the assessment). Project Work reports are required during the semester and are aimed at assessing the capability of applying the knowledge to a real case. The final exam consists of a written test including practical and theoretical exercises. Practical exercises assess the ability to understand and analyse realistic industrial problems and then create appropriate models based on the learnt methodologies to design manufacturing systems and evaluate the impact of possible reconfigurations. Theoretical exercises request to describe and elaborate on concepts, models, techniques and methodologies presented during the course.
In addition to the mandatory evaluation, students will be given the possibility to improve the final grade through:
an optional oral exam on theoretical and practical questions related to the topics included in the program (max 3 points);
optional seminar work (max 3 points). The work will focus either on the application of a learnt methodology to a real industrial case or the further development of a learnt methodology.
In total, a maximum of 4 points can be added to the grade of the written test.

The course reviews the design criteria for new materials, with special focus on those materials produced by innovative processes in industry. Specific attention will be devoted to the existing numerical simulation tools (e.g sw for alloy design, for prediction of deformation and casting processes) and their applications to practical metalworking operations. After recalling few concepts about solidification and plastic deformation, the course will be focused on densification mechanisms and powder metallurgy, covering sintering principles and solidification of powders under high-density power beams, as typical conditions of press and sintering and of metal Additive Manufacturing process, respectively. Solidification by direct deposition and cladding with powders and wires will additionally be considered.

After attending the course, the student will have:
a wider knowledge about the design criteria for new metallic alloys together with the additional options offered by the use of innovative processing routes;
a sound understanding about the influence of the specific processing route on material performance;
knowledge about the opportunities offered by simulation tools for the understanding of metallurgical processes
an increased sensitivity toward the use of critical rather than sustainable raw materials, the issues related to their recycling, cost and performance.

Review of principles about solidification and plastic deformation of metals, physical theories ruling the generation of microstructure and for the prediction of the resulting properties.
Use of CALPHAD methods for the design of metalic alloys and for the prediction of phases and constituents after equilibrium and non-equilibrium transformations.
Production of metal powders and other forms of feedstock: mechanical methods, chemical methods water vs. gas atomization from liquid melts. Powder properties.
Densificaton mechanisms and powder metallurgy: thermal diffusion and pressure assisted sintering principles.
Solidification of powders under high-density power beams: solidification by direct deposition and cladding with powders and wires. Product-related properties: effect of heat input and (fast) cooling rate on properties. Defect generation due to solidification and sintering, development of residual stresses.
Perspectives for alloy design: care to the use of sustainable raw materials. Hot-crack prevention in critical materials. Scenarios of available materials for AM: cost and properties. Metallic alloys available. Structural polymers and composites for AM. Ceramics and hard metals.
A number of visits to companies working with the processes covered during the course will be organized to collect real impression about the working environments.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam of Materials and Simulation tools for sustainable processes consists of an written exam where the student will summarize what he/she has learnt during the course.
Additional evaluation includes the presentation of a project work. Teams of students will use a simulation software for the prediction of alloy behaviour during specific metalworking operations/tretaments. The output will be presented to the class, organizing a discussion and a critical comments of the results.

Slides about lectures will be made available through We-Beep channel, Anno edizione: 2023
Anish Upadhyaya, Gopal Shankar Upadhyaya, Powder Metallurgy: Science, Technology and Materials, Editore: CRC Press Publisher, Anno edizione: 2018
A selection of the most updated scientific papers reviewing the state of the art about recycling and sustainability of metallic materials and about their processing will be collected

Energy infrastructure, encompassing power plants, pipelines, and transmission systems, must withstand extreme conditions and operate reliably over the long term. The longevity and efficiency of energy systems depend on materials capable of enduring high temperatures, corrosion, mechanical stress, and other demanding factors. The primary objective of this course is to acquaint students with the material families utilized in specific sectors of the energy industry. The selection of these materials is guided by the unique requirements of each application and their corresponding physical and mechanical properties, ensuring their suitability for the intended purpose. By the end of the course, students will develop an understanding of the essential considerations for material selection in each sector and will be familiar with the currently available materials that best meet these criteria. This knowledge plays a vital role in mitigating risks and preventing failures in energy infrastructure.

Upon completion of the course, students will be able to:

• Acquire a comprehensive understanding of the primary physical and mechanical requirements for material selection in specific sectors of energy production and distribution systems.
• Understand the properties of the various material families that meet the requirements of these sectors, based on the relationship between material structure and physical properties.
• Critically evaluate the most appropriate material for a given design application and demonstrate a basic understanding of the most likely causes of material failure and the corresponding mitigation strategies.

A brief overview of the principles of physical and mechanical metallurgy, including the intricate nature of modern structural alloys and their strengthening mechanisms.
Materials used in oil and gas distribution systems (midstream): carbon steels and low-alloy steels, including API 5L line pipes.
Materials employed in energy transmission and distribution: copper and aluminum for electrical conductors, and insulating materials.
Materials utilized in electric motors, generators, and transformers: permanent magnets and silicon steels.
Materials required for thermal power plant components: stainless steels and nickel alloys.
Materials used in gas turbine components, such as compressor and turbine blades and vanes: titanium alloys, nickel-based alloys, cobalt alloys, and superalloys.
Materials employed in steam turbine components, such as rotors, blades, and vanes: high-temperature steels and stainless steels.
Materials utilized in wind turbine blades: fiber-reinforced composites, laminates, and sandwich panels.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The examination for Materials for Energy typically comprises a written test that assesses students' understanding of the course material. The main section of the exam will encompass 5 or 6 questions related to specific topics covered throughout the course. The written test may incorporate multiple-choice questions as well. Additionally, at the discretion of the professor, an oral examination might be conducted to further discuss selected topics. The purpose of these examinations is to evaluate students' communication effectiveness, grasp of course subjects, and their ability to apply acquired knowledge in resolving the presented questions.

F.C. Campbell, Elements of Metallurgy and Engineering Alloys, Editore: ASM International, Anno edizione: 2008, ISBN: 978-0-87170-867-0
R. Abbaschian, L. Abbaschian, R.E. Reed-Hill, Physical Metallurgy Principles, Editore: Cengage Learning, Anno edizione: 2008, ISBN: 0495082546
ASM Metals Handbook Set, Editore: ASM International, Anno edizione: 2023, ISBN: 978-1-62708-026-2
W.F. Smith, Structure and Properties of Engineering Alloys, Editore: McGraw Hill, Anno edizione: 1993, ISBN: 0070591725
K.K. Chawla, Composite Materials: Science and Engineering, Editore: Springer, Anno edizione: 2016, ISBN: 978-1-4939-5015-7
G. Dieter, Mechanical Metallurgy, Editore: McGraw Hill, Anno edizione: 1986, ISBN: 0071001786

The course introduces the main materials used in the design and manufacturing of high-performance vehicles, with a specific focus on motorsport applications. The content is structured by vehicle subsystems, linking each to the relevant material families, their properties, and performance under extreme operating conditions.

By the end of the course, students will be able to:
Understand materials and processes for lightweighting and emission reduction in vehicles.
Select appropriate alloys and manufacturing methods for automotive applications; apply basic Life Cycle Assessment (LCA).
Evaluate materials critically based on performance, sustainability, and design needs.
Communicate material choices and design strategies effectively in technical contexts.
Develop autonomous learning abilities in the field of advanced engineering materials.

The course explores the selection and application of advanced materials aimed at reducing vehicle weight and improving performance and sustainability. Students learn how to choose suitable materials and manufacturing processes for structural, powertrain, and braking components, focusing on metals (e.g. high-strength steels, aluminium, magnesium), composites (CFRP/GFRP), and materials for electric motors braking systems and tyres. The course also introduces concepts of Life Cycle Assessment (LCA) and sustainability, with real-world examples from motorsport and commercial vehicles. Practical activities and project work reinforce the technical content and promote critical and analytical thinking.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The final grade (30/30) will be based on the following components:
A) Written examination (25 points)
The written examination consists of four open-ended questions covering the main topics of the course. The questions are designed to assess the student's knowledge and understanding of materials for sustainable transportation systems, including material properties, processing technologies, material selection, sustainability, recycling, and engineering applications. Students are expected to demonstrate critical thinking and the ability to discuss engineering choices supported by scientific principles.
Maximum score: 25 points.
B) Life Cycle Assessment (LCA) exercise (5 points)
Students will solve a short quantitative exercise related to Life Cycle Assessment (LCA). The exercise will assess the ability to apply the LCA methodology to compare materials or transportation solutions, interpret environmental indicators, and critically discuss the obtained results.
Maximum score: 5 points.
C) Optional oral examination (maximum additional 5 points)
Students may choose to take an optional oral examination to improve their final grade. The oral examination consists of a discussion of one or more topics covered during the course and aims to assess the student's ability to integrate concepts, justify engineering decisions, and communicate technical content effectively.
Maximum additional score: 5 points.

Michael F. Ashby, Materials Selection in Mechanical Design, Sixth Edition, Editore: ButterworthHeinemann, Anno edizione: 2005, ISBN: 9780443160295
Michael F. Ashby, Materials and the Environment: Eco-informed Material Choice - 3rd edition, Editore: Butterworth Heinemann, Anno edizione: 2021, ISBN: 9780128215210
Chawla K.K, Composite Materials: Science and Engineering, Editore: Springer, Anno edizione: 2012
Flake C. Campbell Jr., Manufacturing Technology for Aerospace Structural Materials, Editore: Elsevier, Anno edizione: 2006

The Measurements and Industrial Internet of Things course offers and in-depth introduction to signal processing and data analysis techniques applied to mechanical and thermal systems, with a focus on industrial and engineering applications. Students will gain the capability to acquire signals from physical systems relying to sampling and analog-to-digital acquisition, process the data effectively, and extract meaningful parameters that describe the behavior and condition of machinery or mechanical components.
The course includes theoretical and practical approaches to signal analysis in both the time and frequency domains. Topic covered range from basic and advanced statistical methods in time domain, multichannel techniques, frequency domain analysis and frequency response function estimation. A particular emphasis is places on the interpretation of signals for diagnostic and monitoring purposes in modern contexts such as Industry 4.0, smart structures, and general mechanical systems health assessment.
Throughout the classes, students will examine real-world case studies to understand how processed data can be used to detect faults, assess performance, and characterize system dynamics. The use of signal-derived indicators in artificial intelligence frameworks will also be discussed, highlighting the transition from raw data to actionable information.
By the end of the course, students will be equipped with the knowledge and practical tools to select appropriate signal processing techniques, apply them to mechanical and thermal systems, interpret the results to support diagnostics, maintenance, and systems optimization in practical engineering scenarios.

The expected learining outcomes include both general and in-depth knowledge of the topics covered throughout the course, gained via theoretical lectures, numerical exercises and laboratory activities.
In particular, in terms of acquired knowledge and understanding, students will be able to:
describe and analyze the most appropriate data acquisition and analysis strategies, based on the ability to classify the signal according to their nature
consciously and engineering-wise select the most suitable strategy for analyzing data in both time and frequency domains, based on the type of information to be extracted from the system
identify the advantages, limitaitons, implementation procedures, and expected outcomes of both basic and advances data analysis techniques
discuss how to use system excitation and data analysis techniques to the aim of system identification and issue diagnostics
discuss the main features of sensors for Industry 4.0, the main communication technologies, protocols, and architectures to implement IIoT solutions.
Concerning the ability to practically apply the acquired knowledge and understanding, students will be able to:
perform proper signal sampling and conversion, avoiding distorsions (e.g., clipping, aliasing, leakage) of the acquired information
design and operate an appropriate measurements chain to accurately infer the behavior of the physical system under investigation
implement data analysis techniques into algorythms and numerical codes to post-process previously acquired signals
estimate the transfer functions in SISO systems to mechanically characterize the physical system
quantify system parameters / features towards failures detection and diagnostics.
Through the practical activities, students will also acquire the skills to independently formulate a judgment, meaning to:
identify the most appropriate sensors layout, measurement chain, and data acquisition parameters based on the characteristics of the physical system to be analyzed
judge the quality of the measures, addressing statistically the data in time domain and with advanced frequency domain analysis techniques
infer the state of a mechanical system starting from the analysis of the measured signals.

The course content will be delivered thorugh frontal lectures, including both theoretical concepts and practical exercises, supported by innovative teaching approaches, as well as hands-on laboratory activities. The aim is to equip students with all the necessary and sufficient tools to independently develop an experimental project related to the topics covered within the course.
The course covers the following topics divided in modules as per the description below:
Module 1: INTRODUCTORY CONCEPTS FOR SIGNAL PROCESSING
Topic 1.1: Measurements and uncertainty, data acquisition, synchronous / asynchronous sampling, digitalization and measurement chains
Topic 1.2: Signals classification and their characteristics: deterministic vs. random signals; periodicity and stationariety.
Module 2: ANALYSIS IN THE TIME DOMAIN, STATISTICAL PARAMETERS AND CORRELATION
Topic 2.1: Basic statistical and time-varying parameters; Root Mean Square (RMS) and time domain analysis
Topic 2.2: Biased and unbiased auto-correlation, cross-correlation, and coherence functions.
Module 3: SIGNAL ANALYSIS IN THE FREQUENCY DOMAIN, SPECTRAL FUNCTIONS AND WINDOWING
Topic 3.1: Band analysis, Fourier-direct and inverse transform, and spectrum representation
Topic 3.2: Sampling theorem and errors: aliasing and leakage
Topic 3.3: Windowing techniques and basic windows (i.e., rectangular, Hanning, flat-top, and Kaiser-Bessel) overview
Topic 3.4: Signal power and spectral functions estimation; signals averaging and noise.
Module 4: ANALYSIS OF LINEAR TIME-INVARIANT SYSTEMS
Topic 4.1: Linear systems generalities and characteristics
Topic 4.2: Dirac function, unit-impulse response, convolution integral and the theorem of convolution
Topic 4.3: Convolution to explain sampling errors and signal distortions on real signals
Topic 4.4: Frequency Response Function (FRF); averaging and coherence function
Topic 4.5: Mehcanical systems excitation techniques and FRF estimation.
Module 5: SENSORS FOR INDUSTRY 4.0, MEMS AND COMMUNICATION
Topic 5.1: MEMS sensors for mechanical measurements
Topic 5.2: Embedded systems generalities and typical architectures
Topic 5.3: Introduction to communcation technology
Topic 5.4: Basics of a rtificial intelligence for mechanical system diagnostics.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The attendance to any of the course activities is not mandatory but strongly recommended towards a smooth and linear journey. Indeed, participation in lectures and laboratory sessions is at the student's discretion but the content of each module (under any form of subministration) may be included in the final assessment.
In order to successfully pass the Measurement and Industrial Internet of Things course, students must achieve a positive outcome in both the assessment components scheduled at the end of the course:
delivery of a technical report, presentation, and discussion of an experimental project (to be addressed in teams during the laboratory classes)
assessment of course concepts comprehension through an oral exam including theoretical and practical topics discussed during ANY course activity.
The final grade will be calculated as a weighted average of the results achieved by the student in the two assessment components. It is at the teacher's discretion to assign weights and individual evaluations to the projects, based on the overall quality of the work and its presentation, the depth of the analyses, the extensive use of the techniques covered during the course, and the clarity fo the written report. All the evaluated aspects will be appropriately justified at the time of communicating the exam results.

J. Bendat and A.G. Piersol, Engineering applications of correlation and spectral analysis, Editore: John wiley and Sons
J. Bendat and A.G. Piersol, Random data, Editore: John Wiley and Sons
A. Brandt, Noise and Vibration Analysis, Signal Analysis and Experimental Procedures, Editore: Wiley
G. D'Antona, A. Ferrero, Digital signal processing for measurement systems, Editore: Springer
Alberto Corigliano, Raffaele Ardito, Claudia Comi, Attilio Frangi, Aldo Ghisi, and Stefano Mariani, Mechanics of Microsystems, Editore: John Wiley and Sons

The main objectives of the course are:
To provide students with a comprehensive understanding of signal processing and data analysis theory.
To teach students how to apply signal processing and data analysis techniques to extract information from mechanical systems and products.
To develop students' skills in data analysis, data interpretation and data visualization
Some specific examples of the skills that students might learn in a MSc course in signal processing and data analysis for mechanical engineers include:
How to process time series to extract information related to a mechanical system.
How to use Frequency Domain analysis to derive information about signals' periodicity.
How to visualize data in order to ease their interpretation
How to apply signal processing and data analysis techniques to solve real-world problems.
In addition to these technical skills, by working in teams on the course project:
Problem-solving skills.
Communication skills.
Teamwork skills.
Critical thinking skills.
The course will be a valuable investment for students who want to support their projects with experiments and will help understanding the best techniques to extract information from measurement data with a "learning by doing" approach.

In terms of acquired knowledge and understanding, students will be able to:
describe and discuss data acquisition strategies
identify the proper strategies for analysing data in time and frequency domains when facing given engineering problems
describe the procedures for the implementation of signal analysis techniques
describe the main theorems associated with the analysis of linear, time-invariant systems
describe advanced signal analysis techniques
describe how to use the data analysis techniques to the aim of system identification and diagnostics
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
select the most appropriate signal processing strategy for specific mechanical engineering applications
make informed choices about data acquisition parameters based on the characteristics of the system and the analysis objectives
analyse a signal in time and frequency domain
develop and implement MATLAB code for processing and analysing measured signals
estimate the transfer function in SISO systems
extract relevant system parameters and features from measured signals
Through lab and project activities, students will also acquire the skills to formulate a judgment, meaning to:
critically interpret the results of signal processing analyses
compare different signal processing techniques for specific engineering problems
assess the suitability and limitations of the adopted analysis methods
infer relevant information about the state of a mechanical system from measured signals

The course contents are delivered through lectures and laboratory activities. The course covers the following topics:
Module 1: Introductory concepts
Topic 1.1: Classification of signals and their features: stationary and non-stationary signals, random and deterministic signals.
Module 2: Analysis in the time domain: statistical parameters and correlation
Topic 2.1: Basic and time-varying statistical parameters.
Topic 2.2: Correlation functions.
Module 3: Signal analysis in the frequency domain
Topic 3.1: Band analysis, Fourier-direct and inverse transform, frequency resolution
Topic 3.2: Windowing techniques.
Topic 3.3: Characterization of systems in the frequency domain: spectra, power-spectra, cross-spectra
Module 4: Analysis of Linear Time Invariant Systems
Topic 4.1: Dirac function, impulse response, the convolution integral and the theorem of convolution
Topic 4.2: Frequency response function of mechanical systems and its estimation
Topic 4.3: Coherence function
Module 5: Project work
Topic 5.1: Discussion of a representative signal processing project and its methodological workflow.
Topic 5.2: Development of team projects: implementation, interpretation of results, and preparation of the final presentation and report.

Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Attendance to lectures and laboratory activities is not mandatory, but strongly recommended.
The exam consists of the presentation and discussion of a project, carried out in teams, concerning the application of signal processing and data analysis techniques to a mechanical engineering problem.
Project
The project will assess the students’ ability to apply the knowledge acquired during the course, select and implement appropriate signal processing strategies, and critically interpret the obtained results. The project discussion will also assess their ability to present technical activities clearly, justify the adopted choices, and demonstrate individual understanding of the work carried out by the team.
Final Grading
The final grade will be based on the following components:
Quality of Project Work: up to 20 points
Presentation Skills: up to 5 points
Project Discussion and Individual Understanding: up to 5 points
The final grade will be assigned individually. Although the project is carried out in teams, members of the same team may receive different grades based on their individual performance during the presentation and discussion. Honours may be awarded to students who achieve full marks and demonstrate an outstanding overall performance.

J. Bendat and A.G. Piersol, Random data, Editore: John Wiley and Sons
A. Brandt, Noise and Vibration Analysis, Signal Analysis and Experimental Procedures, Editore: Wiley
G. D'Antona, A. Ferrero, Digital signal processing for measurement systems, Editore: Springer
PP Vaidyanathan, Signals, Systems, and Signal Processing, Editore: Cambridge University Press, Anno edizione: 2024

The aim of the course is to provide a comprehensive overview of data collection strategies, signal processing, and data analysis techniques for the analysis and characterization of mechanical systems. The course also addresses edge devices and Industrial Internet of Things (IIoT) technologies to support the sensorization of machines operating at shop-floor level.
The course is divided into two modules:
1. DATA ANALYSIS Module (DAM)
Algorithms and techniques for data processing in the time and frequency domains are discussed, including basic and advanced statistics, basic and advanced frequency analysis, and multichannel analysis. Machine Learning/Artificial Intelligence-based approaches will also be explored. Each topic is addressed theoretically, through the discussion of case studies, and practically, through dedicated interactive tutorial sessions.
2. EDGE- BASED SENSING AND IIoT Module (ESM)
Attendees will learn how to select appropriate sensors and embedded systems tailored to specific industrial applications. Concepts such as the dynamic performance of devices, linearity, and stability with respect to interfering or modifying inputs, such as temperature and vibration, will be addressed to provide students with the knowledge required to design measurement systems based on embedded solutions.
The main communication technologies, such as Bluetooth Low Energy, Wi-Fi, and LoRa, and the protocols used in the Industry 4.0 framework, such as MQTT, will be discussed. The module will also cover the main architectures for managing data and information transfer from the Operational Technology (OT) level to the Information Technology (IT) level, such as sensor–gateway–cloud architectures.
These concepts aim to increase students’ awareness of how to design, deploy, and implement IIoT solutions

Dublin Descriptors (DD)
Expected learning outcomes
Knowledge and understanding (DD1)
The lecture and exercise sessions will enable students to:
DATA ANALYSIS Module (DAM)
Describe and discuss data acquisition strategies.
Identify suitable strategies for analysing data in the time and frequency domains when addressing engineering problems.
Describe the procedures for implementing signal analysis techniques.
Describe the main theorems associated with the analysis of linear time-invariant systems.
Describe advanced signal analysis techniques.
Explain how data analysis techniques can be used for system identification and diagnostics.
EDGE- BASED SENSING AND IIoT Module (ESM)
Understand and describe the main components of an IIoT-based measurement system.
Understand and describe the main metrological characteristics of MEMS sensors.
Understand and describe the main communication buses and protocols used in IIoT-based measurement systems.
Understand and describe suitable strategies for making data available to supervising agents, including field devices, gateways, and cloud platforms.
Application of knowledge and understanding (DD2)
The laboratory sessions will enable students to:
DATA ANALYSIS Module (DAM)
Identify appropriate data acquisition parameters for a specific mechanical system.
Analyze signals in the time and frequency domains.
Avoid leakage and aliasing errors.
Assess the quality of measured data.
Identify system parameters and relevant features.
EDGE- BASED SENSING AND IIoT Module (ESM)
Identify the requirements for developing an Industry 4.0-compliant IIoT measurement system.
Select a suitable architecture for developing an Industry 4.0-compliant IIoT measurement system.
Design an appropriate IIoT measurement solution to address a target Industry 4.0-compliant measurement problem.
Forming judgments (DD3)
The laboratory and project sessions will enable students to:
DATA ANALYSIS Module (DAM)
Implement MATLAB/Python code to analyze previously acquired signals.
Select the most appropriate signal-processing technique to extract specific information about the system.
Infer the condition of a mechanical system based on the analysis of measured signals.
Compare different signal-processing techniques for solving specific engineering problems.
EDGE- BASED SENSING AND IIoT Module (ESM)
Demonstrate the ability to write requirements and design specification documents.
Demonstrate the ability to design an architecture for an Industry 4.0-compliant IIoT measurement system.
Integrate the theoretical concepts learned during the course and deploy an IIoT application.

The course content is delivered through lectures, interactive discussions of case studies, and lab activities.
The course covers the following topics divided into modules as described below:
DATA ANALYSIS Module (DAM)
DAM1: Introductory concepts
Topic 1.1: Classification of signals and their features: stationary and non-stationary signals, random and deterministic signals
Topic 1.2: Basics of signal acquisition.
DAM2: Analysis in the time domain: statistical parameters and correlation
Topic 2.1: Basic and time-varying statistical parameters
Topic 2.2: Correlation functions
DAM3: Signal analysis in the frequency domain
Topic 4.1: Band analysis, Fourier-direct and inverse transform, frequency resolution
Topic 4.2: Leakage and Aliasing
Topic 4.3: Windowing techniques
Topic 4.4: Characterization of systems in the frequency domain: spectra, power-spectra, cross-spectra
DAM4: Analysis of Linear Time Invariant Systems
Topic 4.1: Dirac function, impulse response, convolution integral and the theorem of convolution
Topic 4.2: Coherence function
DAM5: Advanced data analysis techniques
Topic 5.1: Time-frequency transform
Topic 5.2: Synchronous and Asynchronous sampling. Order analysis
Topic 5.3: Introduction to machine learning and artificial intelligence-based analysis
EDGE- BASED SENSING AND IIoT Module (ESM)
ESM1: Introduction to Edge-devices
Topic 1.1: Microcontrollers, data acquisition and conditioning
Topic 1.2: Peripherals and main communication buses - GPIO, SPI, I2C, UART/USART)
ESM2: Introduction to MEMS-based sensing
Topic 2.1: MEMS sensors operating principles and metrological performance
Topic 2.2: Advantages and Usage Issues of MEMS-based monitoring systems
ESM3: IIoT solutions
Topic 3.1: Definition and design principles of IIoT systems and architectures (e.g., field devices - gateways - cloud)
Topic 3.2: Buses and Communication protocols for IIoT
Topic 3.3: Machine vision for IIoT
Topic 3.4: Data Visualization Dashboard Creation
Topic 3.4: Cybersecurity in IIoT and manufacturing
Topic 3.5: Machine Learning and Artificial Intelligence at the Edge: From Data to Information transmission

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam will be structured differently for the two modules: Data Analysis Module (DAM) and Edge-Based Sensing and IIoT Module (ESM).
Data Analysis Module (DAM)
Students will pass the module after successfully completing a written test and an oral test. Questions in both the written and oral tests may refer to topics covered during lectures and laboratory sessions. Students may also be asked to solve practical signal-processing problems.
Only students who obtain a mark higher than 18 in the written test will be allowed to take the oral test.
As an alternative to the standard oral test, students may choose to carry out a practical data analysis project, either individually or in groups of up to three students. The project will be discussed during the oral examination session.
Written test (DD1, DD2)
Students are expected to demonstrate strong theoretical knowledge of the course topics. They are also required to show the ability to correctly choose and apply methods and algorithms in given scenarios, through both exercises and theoretical questions based on simulated cases.
Oral test (DD1, DD2, DD4)
In the oral part of the exam, specific sections of the programme are explored in greater depth through theoretical questions. Students are expected to demonstrate the ability to integrate different topics and apply them to given cases. They are required to demonstrate knowledge of the main definitions and concepts related to data analysis and signal processing, as well as the fundamental principles of the theory.
Project (DD3, DD4, DD5)
Students are asked to identify a project topic aligned with the course contents. Students who choose to undertake the project will receive support through periodic discussions on the progress of their work.
Through the project, students are expected to demonstrate their ability to independently make analysis and processing choices (DD3, DD5) and to communicate them effectively (DD4). If the project is carried out in a group, the contribution of each participant must be clearly highlighted.
Final grading
The final grade is the arithmetic mean of the marks obtained in the written test and in the oral component of the exam, which may consist of either the standard oral test or the project discussion.
Edge-Based Sensing and IIoT Module (ESM)
Students will pass the module after successfully presenting and discussing a project, carried out either individually or in groups of up to three students.
Students may choose a topic from a provided list or propose their own topic, subject to approval by the professor. The project requires students to address an Industry 4.0-compliant IIoT measurement problem through its different phases:

• analysis of the requirements and definition of the design specifications (DD3);
• identification of suitable data acquisition strategies (DD3);
• identification of appropriate processing and communication strategies (DD3, DD5);
• critical analysis of the results obtained (DD3);
• discussion of the results and defence of the engineering choices made (DD3, DD4).
  Clarity of presentation and exposition (DD4) will also be taken into account in the final grade.
  Students enrolled in both modules will be evaluated according to the examination rules of the Edge-Based Sensing and IIoT Module.
  Dublin Descriptors
  DD1: Knowledge and understanding
  DD2: Application of knowledge and understanding
  DD3: Forming judgments
  DD4: Communication
  DD5: Learning skills

Students may refer to the reference materials provided during the course.
J. Beyerer, F. Puente León, C. Frese, Machine Vision, Editore: Springer-Verlag
Note: The main reference are the slides and the digital documents provided by the professor. This is and additional (non mandatory) material.

The course will provide the knowledge concerning mechatronic systems used for manufacturing, focusing on their performances and main components. The interaction with the manufacturing process will be modelled, to perform system stability analysis and vibrational issues. The fundamentals for developing advanced monitoring solutions will be provided as well as concepts of Prognostics and Health Management (predictive maintenance). The course will provide basics for production quality assessment. Concepts of sustainable manufacturing will be introduced together with several industrial case-studies. In this perspective, the additive manufacturing of thermoplastics, reinforced with recycled carbon fibre (rCFRTP), will be studied. The course makes extensive use of laboratory sessions

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In order to pass the exam, the student has to develop the following capabilities:
Knowledge and understanding of the course topics (DdD1). To describe, interpret and discuss on the main course subjects.
To apply and critically elaborate the learnt concepts with the aim of selecting a mechatronic system and enhancing its performances, from different perspectives, both during the design and use phase (DdD2, DdD3).
Developing a project work in which non-trivial technological solutions need to be conceived (DdD2, Dd3, DdD5) – flipped classroom
Communication skills are requested both during the oral session and for explaining the choices carried out in the project work development (DdD4).
DdD: Dublin Descriptors

The course contents are delivered through lectures, exercise courses and laboratory (numerical/experimental) activities.
The course covers the following topics divided in modules as per the description below:
Module 1: Basics of Mechatronic systems used in manufacturing
Topic 1.1: Manufacturing and mechatronics systems (machine tools and robots): introduction, performances and applications
Topic 1.2: Architectures and structures
Topic 1.3: Guides, transmissions and joints
Topic 1.4: Spindles and Tools
Module 2: System dynamics and process interaction
Topic 2.1: System dynamics and vibrational issues. Theory of the dynamic instability, related numerical and experimental techniques (laboratory session)
Topic 2.2 Vibration mitigation and control strategies.
Module 3: Machine Programming
Topic 3.1: CAM, machining strategies definition and part-program optimization
Module 4: Machine energy consumption, sustainability in manufacturing and remanufacturing
Topic 4.1: Evaluation of energy efficiency of the mechatronic systems: scenario description and introduction.
Topic 4.2: Energy assessment procedures (laboratory session) and energy modelling development
Topic 4.3: Energy reduction-oriented strategies and process parameters optimization.
Topic 4.4: Cryogenic machining
Topic 4.5: Composite manufacturing. Recycling approaches for composites.
Topic 4.6: Additive manufacturing of recycled carbon fibre reinforced thermoplastics (rCFRTP)
Module 5: Fundamentals of industrial quality control
Topic 5.1: Statistical process control; Shewhart control charts; Type I and II errors; control limits and specification limits.
Topic 5.2: Capability analysis: performance index; natural tolerance limits; known and unknown distributions; capability indexes; actual capability and potential capability; non-conforming percentage estimation.
Module 6: Monitoring and Predictive Maintenance
Topic 6.1: In-process monitoring: from product measurements to in-process measures; statistical monitoring of sensor signals; control charting for non-independent data; brief introduction to multivariate analysis and profile monitoring.
Topic 6.2: Prognostics and Health Management (Predictive Maintenance) approaches: features extraction and selection (dimensionality reduction techniques), introduction to clustering/classification for diagnosis; prognostics introduction and hybrid prognosis techniques.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully take an oral exam and after submitting a project-work report (both mandatory).
Part 1: A project-work needs to be developed (students will be arranged in groups) applying and elaborating the main course concepts (DdD 2, DdD3, DdD5). Each group can decide the topic of the project-work (among the course topics).
A project report and a presentation (flipped classroom) containing the explanation of all the performed choices/analysis and the main final considerations (DdD1, DdD3, DdD4) needs to be prepared and carried out. The project globally accounts for 15/30.
Part 2: An oral session on all the course topics (DdD1, DdD4) has to be carried out. During the oral section, the discussion of the project work could be done (DdD4). Questions on the course topics with specific focus on possible industrial cases.
The oral session accounts for 15/30.
Final grading:
The project globally accounts for 15/30.
The oral session accounts for 15/30.

Lecture Notes
Altintas Y., Manufacturing automation: metal cutting mechanics, machine tool vibrations, and CNC design, Editore: Cambridge University Press, Anno edizione: 2012, ISBN: 05-211-7247-0
Douglas C. Montgomery, Introduction to statistical quality control, Editore: Wiley, Anno edizione: 2020, ISBN: 978-11-19-72309-7
Iternational Standards https://www.biblio.polimi.it/strumenti/normativa-tecnica
Altintas; Budak, Analytical prediction of stability lobes in milling, Editore: CIRP ANNALS-MANUFACTURING TECHNOLOGY, Anno edizione: 1995, Fascicolo: 44(1):357-362
Montgomery D, Design and Analysis of Experiments, Editore: Wiley, Anno edizione: 2013, ISBN: 978-11-18-09793-9
Albertelli, Energy saving opportunities in direct drive machine tool spindles, Editore: Elsevier- Journal Cleaner Production 10.1016/J.JCLEPRO.2017.07.175, Anno edizione: 2017, Fascicolo: 165
Borgia, Albertelli, Bianchi, A simulation approach for predicting energy use during general milling operations, Editore: Springer - The International Journal of Advanced Manufacturing Technology doi:10.1007/s00170-016-9654-5., Anno edizione: 2017
Rajemi, Mantivegna, Aramcharoen, Sustainable machining: selection of optimum turning conditions based on minimum energy considerations, Editore: Elsevier - Journal Cleaner Production 1059-1065 doi:10.1016/j.jclepro.2010.01.025, Anno edizione: 2010, Fascicolo: 18
Albertelli, Strano, Tube bending machine modelling for assessing the energy savings of electric drives technology, Editore: Elsevier - Journal Cleaner Production 10.1016/J.JCLEPRO.2017.03.212, Anno edizione: 2017, Fascicolo: 154
Albertelli, Mussi, Strano, Monno, Experimental investigation of the effects of cryogenic cooling on tool life in Ti6Al4V milling, Editore: Springer - The International Journal of Advanced Manufacturing Technology - 10.1007/s00170-021-07161-9, Anno edizione: 2021
Albertelli, Monno, Energy assessment of different cooling technologies in Ti-6Al-4V milling, Editore: Springer - International Journal of Advanced Manufacturing Technology -10.1007/s00170-020-06575-1, Anno edizione: 2021
An Introduction to Statistical Learning: with applications in R https://doi.org/10.1007/978-1-0716-1418-1
FDM-based additive manufacturing of recycled thermoplastics and associated composites, Editore: J Mater Cycles Waste Manag - https://doi.org/10.1007/s10163-022-01588-2, Anno edizione: 2023, Fascicolo: 25
Krajangsawasdi N, Blok LG, Hamerton I, Fused Deposition Modelling of Fibre Reinforced Polymer Composites: A Parametric Review, Editore: J Compos Sci - https://doi.org/10.3390/jcs5010029, Fascicolo: 5

The goal of Design Methods is to provide knowledge and application skills in methods related to the embodiment design of industrial products.
The principles that allow the study and development of suitable solutions to meet the design requirements will be illustrated during the lectures. The methods to achieve this objective will be proposed and applied during the exercises.
Specifically, the course will cover the study of models and design tools suitable for developing new products and improving existing ones.
The proposed systematic design concepts will be applied to concrete cases that students will develop.

By the end of the course, students will learn content and practices according to the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
identify the methods available to detect the functionality of an industrial product;
describe the techniques able to analyse and subdivide a product into its sub-assemblies and parts, organising them based on their functions;
define the approaches for the systematic designing of a new product or for the improvement of an existing one;
collect the techniques for gathering information on technical systems able to satisfy specific functions;
discuss the rules for developing embodiment solutions of industrial products according to a specific X target (Design for X).
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
apply the analysis of the operating functions of an industrial product;
illustrate the subdivision of a product into groups of organs able to perform a specific function;
solve the search for technical systems and solutions able to satisfy defined requirements;
classify and compare different technical systems using evaluation methods and tools to select the best solution for the problem posed;
complete the definition of the embodiment of a product or one of its sub-assemblies.
Through project work, students will also acquire the skills to formulate a judgment, meaning to choose the better design solution among different design solutions based on objective criteria.
Furthermore, through the assigned project work, students can autonomously compare and design different engineering solutions that satisfy the same functions until they formulate the embodiment of the final chosen solution.
Finally, students will improve their communication skills by performing the technical documents required to fabricate the product and communicating and discussing the results of the design developed.

The course content is delivered through lectures, exercises, and project activities. Periodically, students will be called to communicate and discuss with the class the results of design problems proposed weekly in the form of exercises.
The course is designed to equip students with practical knowledge and skills. It covers the following topics divided into modules as per the description below:
Introduction: We'll delve into the design of industrial products, their historical context, and their evolution. We'll explore the logical steps in the design process and their connection to a product's life cycle, giving you a comprehensive understanding of the subject.
Theory of technical systems: principles and methods of design science (axiomatic design, heuristic design, systematic design, etc.); schematic and practical models adopted for the analysis, the simulations, and the development of industrial products; physical principles of operation of machines and industrial products; beneficial use of the archives of constructive solutions for gathering information. Knowledge management.
Design for X: Designing the embodiment of the product, basing the functional solutions on the properties arising from the phases of the product life cycle (production, assembly, installation, performance, ergonomics, maintenance, reliability, quality, cost, environmental sustainability, etc.); Criteria for the choice of optimal constructive solution. Communication methods for product manufacturing and control.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course after completing an oral presentation and discussing the report written on the assigned project.
As a crucial part of the course, students, grouped in teams, will be tasked with a design problem. This could involve developing a new product or enhancing an existing one. The problem must be approached using the methods and techniques learned. The team is expected to create a comprehensive report detailing their solution process and the outcome. They will also need to present their work and results orally. The final grade will be determined based on the written report and the oral presentation, underlining the significance of this project in the course.
The design project intends to check if the students have the following abilities:
to detect the functionality of an industrial product and its sub-assemblies;
to apply systematic methods to solve a design problem;
to collect the information required to develop a design solution;
to arrange an abstract solution into a complete embodiment design for a product;
to select, also in a critical manner, the more helpful method to face the problem posed;
to communicate own results in agreement with the technical communication languages adopted in the mechanical engineering field.
Students who do not attend or participate in the design project will be evaluated based on a written test followed by an oral discussion. This test will be focused on a specific and confined design problem.
Using these tests and discussions, you intend to validate the abilities acquired by the student:
to analyse, using a systematic approach, the problem posed and identify the main functionalities of the system proposed;
to arrange and collect the information required to solve the problem using one of the methods learned;
to apply an evaluation criterion to select the best solution between those discovered;
to describe the embodiment architecture of the final solution;
to communicate the result obtained.

Teacher's notes https://webeep.polimi.it/
George E. Dieter, Linda C. Schmidt, Engineering Design, Editore: McGraw-Hill, Anno edizione: 2021, ISBN: 978-0-07263703-2
Pahl G, Beitz W, Engineering design. A systematic approach, Editore: Springer, Berlin Heidelberg New York, Anno edizione: 2007, ISBN: 978-1-84628-318-5

The course aims at giving participants all the tools required for the analysis and the design of control systems, together with the basics on technological aspects related to their implementation. A classic mechatronic problem, i.e., the design of a motion control system, is used as a case study to show a realistic application of these tools.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to:
represent the behaviour of a linear and time invariant dynamical system with respect to both time and frequency domain;
analyse the properties of dynamical system and the possibility to modify them through feedback;
use numerical tools to verify the properties of a dynamical system.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
derive a simple dynamical system to represent the behaviour of a simple, yet real, dynamical system;
propose a feedback control law for a given dynamical system which satisfies given requirements in terms of performance and robustness.
Finally, students will improve their written communication skills, being able to link all the acquired theoretical backgrounds to elaborate and communicate the solution to simple questions, which are not of immediate application of known results.

The course contents are delivered through lectures and exercises courses (some of them with the help of numerical softwares).
The course covers the following topics divided in six modules as per the description below:
Dynamical systems (time domain):
Fundamentals of continuous time dynamical systems. Solutions and equilibrium points. Lyapunov stability. Linear Time Invariant (LTI) systems: solutions (Lagrange formula) and equilibrium points, stability analysis. Structural properties of LTI systems: observability and reachability.
Dynamical systems (frequency domain):
LTI systems in the frequency domain. Frequency response. Transfer function. Step responses of first and second order systems. Bode diagrams. Introduction to feedback control systems. Loop stability analysis (Bode criteria) and indices for robust stability (gain and phase margins).
Design of feedback control systems:
Transient and steady-state performance. The “gang-of-four” sensitivity transfer functions. Control system design. Feedforward compensation. Cascaded control. PID regulators: standard form and anti-windup techniques. Root locus for analysis and synthesis. Contour locus. Introduction to state space design. Full-state feedback. Observer design. Combining observer and control law. Introduction of a reference input. Adding feedforward actions to closed-loop control systems. Calculation of the equivalent transfer function for the 2-dof controller.
Discrete time and digital control systems:
Introduction to discrete time systems (motivations). Introduction to digital control systems. Effects of sampling on the closed loop system. Indirect digital controller design: selecting the sampling rate and determining the transfer function of the digital regulator. Code implementing discrete-time transfer functions.
Hardware and software technologies for automation:
Transistors and operational amplifiers. Analog I/O conditioning and filtering (anti-aliasing). Analog-to-digital and digital-to-analog converters. Programmable Logic Controllers (PLCs). Sequence Function Charts (SFC) for action sequencing.
Motion planning and control:
Introduction to motion control problems. Motion control with electro-hydraulicactuators. Models of an electric motor and of rigid and elastic transmissions. P/PI (position/velocity) control: tuning for elastic transmissions using motor feedback, intrinsic performance limitations. Introduction to motion planning. Point-to-point motion planning with polynomial functions and trapezoidal velocity profiles. Filtering of encoder signals.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Students will pass the course after having successfully taken a written examination of 2 hours (120 minutes).
The following supports are allowed:

• printed copies of slides;
• printed copies of suggested books;
• hand written annotations.
  In turn, the use of electronic devices of any kind (laptops, smartphones, smart glasses, headphones,...) is forbidden, except for a non-graphical calculator. For all the other and non-specified matters, the following applies: https://www.polimi.it/fileadmin/user_upload/Il-Politecnico/statute-regulations/Reg._commissione_disciplina_studenti_EN.pdf.
  The exam consists of 1 (one) question and 4 (four) exercises. More in particular:
  the question is intended to evaluate the ability of the student to interconnect the acquired knowledge in order to elaborate and communicate the solution, which is not of immediate application of topics explained during lectures;
  the exercises are intended to test the capability of the examinee of applying the acquired skills to numerical problems.
  Final Grading to pass the course, students must successfully score as at least 18 points out of 32. The exam can be taken in any of the 5 annual calls, without restrictions.
  A compulsary oral examination will be requested by the lecturer in case of doubts regarding the outcome of the written part.

A.M. Zanchettin, Feedback Control Systems: Methods and Technologies for Mechatronic Engineers, ISBN: 9791221085259 https://re.public.polimi.it/handle/11311/1282765
Katsuhiko Ogata, Modern Control Engineering, Editore: Prentice Hall, ISBN: 978-0-13-615673-4
Karl Johan Astrom and Richard M. Murray, Feedback systems - An Introduction for Scientists and Engineers http://www.cds.caltech.edu/~murray/amwiki/index.php/Second_Edition

The course aims to develop the student's critical skills for addressing mechanical design toward environmentally, economic, and socially sustainable solutions, by means of innovative design methodologies and tools that consider the overall life cycle of the product, from the concept to the end-of-life and by focusing on the peculiar aspects of mechanical constructions.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding, students will be able to:
develop design solutions that consider and minimize the environmental impacts while guaranteeing feasibility and profitability.
develop a quantitative environmental assessment of the products by means of a quantitative Life-Cycle-Assessment (LCA).
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
solve practical case studies by using different tools (analytical and numerical).
Through activities of the project, students will also acquire the skills to formulate an assessment, meaning to analyse a problem with different tools to understand their assumptions and limitations, and to analyse and critically discuss and compare the results in the light of circular design.
Furthermore, by applying the methodological skills gained in the course, students will gain the ability to autonomously addressing the multidisciplinary aspects of mechanical design including the peculiar environmental aspects for the different categories of products that are more and more important in the professional activity of engineers.
Finally, students will improve their communication skills through the assigned project and practices and will learn or improve their skills to communicate and explain their achievements, conclusions and recommendations with the argumentation of the knowledge and rationale underpinning these, to both specialist and non-specialist audiences clearly and unambiguously convincing them of the correctness of their final solution.

The course contents are delivered through lectures, practical exercises and project laboratory.
Lectures
Introduction to sustainability and circularity in engineering design.The industrial and natural life cycles and their interactions. Environmental aspects of product development and engineering design.
The engineering design process. Definition of mechanical systems, product life cycle phases, and feasibility analysis. The role of engineering codes and standards. Materials selection for sustainable design. The fundamental principles of Design for the Environment (DfE).
Design for eXcellence (DfX). Design for Assembly and Manufacturing (DfMA), Design for Disassembly (DfD), and Design for Reliability and Maintainability (DfRM). Introduction to Robust Design and multi-objective optimization techniques.
End-of-Life (EoL) strategies. Recycling, reuse, and remanufacturing: methodologies for selecting the most appropriate EoL option. Life extension strategies: methods for assessing residual life and improving product durability and service life.
Life Cycle Assessment (LCA). Functional Unit and Reference Flow. Definition of system boundaries (cradle-to-gate, gate-to-gate, cradle-to-grave, and cradle-to-cradle). The phases of LCA: Goal and Scope Definition, Life Cycle Inventory (LCI), Life Cycle Impact Assessment (LCIA)—including classification, characterization, normalization, and weighting—and interpretation of results. Overview of ISO 14040/14044 standards and related LCA guidelines.
Economic sustainability assessment. Methods for evaluating the life cycle costs of sustainable products, considering the different phases of the product life cycle and supporting decision-making in sustainable engineering design.
Seminars and technical visits. Two or three seminars delivered by recognized experts from industry and academia will complement the lectures. In addition, one technical visit to a company operating in the field of sustainable engineering and manufacturing will provide students with direct exposure to industrial applications.
Practice
During practice time students will be asked to solve problems and exercises about the subjects of the course.
Project Lab
Students will be asked to form groups to develop the design of a simple mechanical system, critically considering and discussing the aspects related to the environmental impact evaluation of the proposed solution.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The groups are requested to present the results of the Project Lab before the exam. This part of the exam is aimed at assessing the results of the project and the communication skills of the groups' members.
The individual exam is formed by a written test (duration 1h) aimed at assessing the global understanding and knowledge of the main aspects of the course and an oral discussion aimed at assessing the critical ability of the students to critically discuss and apply the subjects of course.
The students are not admitted to the oral discussion if the written test is not passed.
The final evaluation is based on the Project Lab (40%), the written test (30%) and the oral discussion (30%) results.

Lecture notes of the teacher available on Polimi WeBeep https://webeep.polimi.it/
Nand K. Jha, Green Design and Manufacturing for Sustainability, Editore: CRC Press-Taylor&Francis group, Anno edizione: 2016
Karl T. Ulrich, Steven D. Eppinger,, Product Design and Development, Editore: McGraw-Hill, Anno edizione: 2016
G. Boothroyd, P. Dewhurst, W. Knight, Product Design for Manufacturing and Assembly, Editore: Marcel Dekker Inc.
A. Ertas, J.C. Jones,, The Engineering Design Process, Editore: John Wiley & Sons
A. Desai, A. Mital, Sustainable Product Design and Development, Editore: CRC PRess - Taylor&Francis Group

The increasing computer power is nowadays essential to deal with the numerical solution of large dimensional problems, however a computational reduction is still determinant whenever interested in real-time simulations and/or repeated output evaluations for different values of some inputs of interest. In order to reduce this computational burden, we may rely on suitable reduced order models (ROMs), which are faster and cheaper to simulate, yet accurately represent the original high-fidelity (or full-order) system behavior. Within this class of techniques, parametric model reduction has emerged only in the last decade as a very active research area. Parametric ROMs target the broad class of problems for which the equations governing the system behavior depend on a set of parameters, such as in the case of parameterized PDEs. These parameters may represent, for instance, material properties, system geometry, boundary or initial conditions. The goal of parametric ROMs is thus to generate rapid but reliable models that characterize the system’s response over the whole parametric range. Such a strategy proves to be necessary in order to speedup design, control, optimization, and uncertainty quantification settings, usually requiring several repeated model evaluations.
This course surveys the state-of-the-art of parametric reduced order models, describing the most popular approaches related to physics-driven techniques (such as reduced basis methods and proper orthogonal decomposition) and data-driven techniques (such as non intrusive ROMs based on interpolation, surrogate models involving, e.g., neural networks, and model discovery techniques), providing also a comparative discussion that lend insights to potential advantages/disadvantages entailed by their application.

Besides the knowledge of theoretical results and numerical methods presented during lectures and Lab sessions, a critical comprehension of the class’ topics is expected by the students at the end of the class, justifying the followed procedures. Attending the course, students are expected to:
know and understand how to perform numerical simulation of problems of interest in mechanical engineering (e.g., heat and mass transfer, linear and nonlinear elasticity/elastodynamics, fluid dynamics) in many-query contexts (e.g., repeated simulations in multiple scenarios; control and optimization) or real-time contexts (e.g., predictive digital twins);
set, analyze and apply reduced order modeling techniques for differential problems built on top of classical numerical methods (e.g., finite element method), of both physics-driven and data-driven type;
exploit already acquired numerical methods in Engineering to set up physics-based ROMs (e.g., reduced basis methods);
exploit recent strategies in scientific machine learning for the efficient numerical simulation of physical systems through data-driven ROMs (including, e.g., simple neural networks);
adapt the proposed methodologies to more general problems of applied interest in Engineering;
interpret the results, assessing both accuracy and efficiency of simulation strategies, from both a numerical and a statistical point of view.

The course is organized in a series of lectures and practical lab sessions. Lectures will provide the theoretical background; practical Lab sessions will provide algorithms' implementation and examples of application of the considered methodologies by using basic (e.g., Matlab or Python) codes. After reviewing basic concepts in numerical methods for differential problems, the course will focus on the following topics:
Dimensionality reduction algorithms
Singular value decomposition, optimal low-rank approximations, proper orthogonal decomposition. Autoencoders.
Projection-based reduced order modeling techniques
The reduced basis method for (linear) parametrized partial differential equations: reduced space construction, (Petrov-)Galerkin projection, a posteriori error estimation. Affine parameter dependence.
Hyper-reduction techniques
Extension of the reduced basis method to nonlinear and/or nonaffinely parametrized problems. Empirical interpolation method.
Non-intrusive reduced order modeling techniques
POD with interpolation (e.g., Neural Networks, Gaussian Process) strategies. Autoencoders and basic ideas on deep-learning reduced order models for parametrized systems.
Data-driven dynamical systems
Dynamic mode decomposition. Sparse identification of nonlinear dynamics (SINDy). Neural ODEs. Model discovery techniques for the latent dynamics.
Physics-informed machine learning
SINDy Autoencoders: extension of SINDy to high-dimensional systems. Shallow recurrent decoder networks for reduced order models embedding sensor data. Learning nonlinear operators (e.g., deep operator networks).

Prova orale obbligatoria
The oral exam covers the content of both theoretical lectures and practical Lab sessions.
During the exam, students are required to present the detailed solution of two selected assignments (among a list of assignments proposed during the practical Lab sessions), commenting both the numerical results obtained and the computational procedures employed, and to answer to theoretical questions related with the topics of the course.
Assignments will require students to apply, adapt, or extend some of the methods presented during the course to selected practical case studies. The assignments will be evaluated during the oral examination and must be submitted to the examiners by the deadline communicated during the classes.
Theoretical questions will assess students' knowledge of the methodologies covered throughout the course. During the examination, students will first be required to sketch written answers to the theoretical questions, before presenting and discussing them with the examiners.
The course will be based on a selection of chapters of the following books, class notes, and some selected scientific papers provided:

A. Quarteroni, A. Manzoni, F. Negri, Reduced Basis Methods for Partial Differential Equations. An Introduction, Editore: Springer, Anno edizione: 2016
Steven L. Brunton, J. Nathan Kutz, Data-Driven Science and Engineering. Machine Learning, Dynamical Systems, and Control, Editore: Cambridge University Press, Anno edizione: 2022

This course introduces the fundamental concepts of ship hydrostatics and hydrodynamics, learning the interaction between a fluid and a floating structure. The general definitions used in the marine sector will be presented and illustrated during the classes. The naval architecture concepts will be provided, focusing on the methodology to perform hydrostatic and hydrodynamic studies.
The course will provide the background in ship typologies and characteristics, ship stability, hydrodynamic resistance and propulsion, giving some information on its dynamics.
The course consists of a mix of lectures and hands-on sessions on the computer where the students will implement some examples under the instructor's guidance.

This course introduces the fundamental concepts of ship hydrostatics and hydrodynamics, learning the interaction between a fluid and a floating structure. The general definitions used in the marine sector will be presented and illustrated during the classes. The naval architecture concepts will be provided, focusing on the methodology to perform hydrostatic and hydrodynamic studies.
The course will provide the background in ship typologies and characteristics, ship stability, hydrodynamic resistance and propulsion, giving some information on its dynamics.
The course consists of a mix of lectures and hands-on sessions on the computer where the students will implement some examples under the instructor's guidance.

General notions, nomenclature, references and definitions. References of descriptive geometry, masses and hydrostatics. Float statics Equilibrium conditions of a freely floating body totally or partially immersed. General equations of equilibrium. Curve of the centers of isocarenic floats. Balance and stability of a free floating ship. Metacentric evolution. Moment of transverse static stability (for small angles <10 ° -12 °). Metacentric method, Pair of shape and weight stability, Metacentric height, Moment of longitudinal static stability. Equilibrium conditions of a ship Stability diagram, stability or instability of equilibrium at angles of zero momentum, capsize angle, dynamic stability, stability reserve, behavior of the ship under the action of inclining causes, elements that influence the course of the stability diagram, Influence of the height of the center of gravity. International legislation concerning stability in the intact state of ships. The stability test. Variation of stability in the cases of movement and loading of weights Effects on stability following the loading or unloading of a relevant weight, Loading or unloading of small weights, Effect on the stability of the ship for loading a weight. Compartmentalization of ships Diagram of floodable lengths, Compartmentalization factor. The flaw: Method for hull subtraction, Method for loading weights. Solution of the problem of the balance of a stranded ship and verification of stability. Static launch study with the descending ship method.
HYDRODINAMICS: The problem of resistance to the naval architect and the different types of resistance. Friction and wave resistance. The dimensional analysis and the corresponding speeds: application of the similarity to the study of the hull models. Frictional resistance. The resistance of the flat plate. ITTC '78 transfer methodology. The form factor. The addition of roughness and the tank-sea correlation. Residual resistance Wave types. Wave systems generated by the ship: The theoretical calculation of wave resistance. Other components of the resistance. Resistance due to eddies. Aerodynamic drag. Effect of the shallow water and the banks. Trim effect. Resistance due to the hull appendages Naval tanks and trailer tests. Naval tanks. Features of the model. Presentation of resistance data. Series of Hulls. Parameters that affect the resistance to motion: coefficients and characteristic ratios. The systematic series of hulls and their use: examination of some series for different projects. The prow bulb. Statistical methods applied to systematic series. Advanced marine vehicles. Semi-displacement hulls. Planing hulls. Catamarans. Swath. Hydrofoil. Air cushion vehicles. Similititude for propellers and hull-propeller. Dimensional analysis. Isolated propeller tests. Hull-propeller interaction: wake, relative rotary efficiency, thrust deduction, hull efficiency and propulsion efficiency. Use of the dimensionless propeller features. Self-propulsion tests. Difference between the working conditions of the propeller from the model to the ship and correction procedures. Propeller theory. Propeller geometry and design. The impulsive theory. Palar element theory and hydrodynamic sections. The vortical theory. Cavitation. Nature and types of cavitation. Effects of cavitation and criteria for prevention. Propeller project. General criteria: choice of the fundamental characteristics of the propeller. Systematic series and their use for the project. Initial data processing. The hydrodynamic calculation.

Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists in the discussion of a project, defined during the course.
The project will be agreed with the teachers and the evaluation phase will be done in two steps:

• a written part, where the students will submit a written report of the activities and the results of the project
• an oral part where the students will present the activities and the results of the project
  Questions about general program, (oral answer)

The course is aimed at enabling students to master advanced engineering methods for analysing noise and vibration problems, with a special focus on transportation and industrial applications. The course covers fundamental analytical models, experimental techniques and numerical methods. Each topic is treated both theoretically and practically, through traditional lectures and experimental/computer labs.

By the end of the course, students will learn contents and practices according to what defined in the learning objectives.
In terms of acquired knowledge and understanding (DD1), students will be able to:
describe the modelling approaches to vibration and wave propagation analysis of one-dimensional and two-dimensional continuous systems;
interpret sound waves, acoustic quantities, and wave propagation models;
discuss the basic physical principles of sound radiation and sound transmission.
Concerning the ability to apply the acquired knowledge and understanding (DD2), students will be able to:
apply theoretical knowledge to the handling of complex vibroacoustic problems in real structures;
perform vibroacoustic measurements and employ proper data processing techniques.
Through the lab activities, students will also acquire the skills to formulate a judgment, meaning to critically analyse numerical results and experimental data, and compare alternative modelling/testing approaches (DD3).
Furthermore, through the lab assignments worked out in groups, students will gain the ability to autonomously rearrange and judge the results of the developed models and of the processed data. Finally, students will improve their communication skills, being able to prepare and present a professional report on the results achieved during the lab activities (DD3, DD4).

The course contents are delivered through traditional lectures and experimental/computer labs (focused on specific methodologies, case studies and practical applications).
The course covers the following topics divided in modules as per the description below.
Module 1. Vibration and waves in one-dimensional continuous systems
Topic 1.1. Review of the partial differential equation governing transverse vibration of strings and axial vibration of bars (one-dimensional wave equation). Traveling waves and standing waves. Wave propagation speed, wavenumber, mechanical impedance. Transmission and reflection at an impedance change.
Topic 1.2. Review of the partial differential equation governing bending vibration of slender beams (Euler-Bernoulli beam). Dispersion, phase and group velocities, evanescent waves.
Module 2. Vibration and waves in two-dimensional continuous systems
Topic 2.1. The partial differential equation governing bending vibration of thin plates (Kirchhoff plate).
Topic 2.2. Bending waves propagation, the wavenumber vector, point mobility.
Topic 2.3. Bending vibration of finite plates. Vibration modes of rectangular and circular plates with different boundary conditions (analytical and finite-element numerical solutions).
Module 3. Sound waves
Topic 3.1. The homogeneous acoustic wave equation. Sound pressure, particle velocity and acoustic velocity potential.
Topic 3.2. Propagation of plane and spherical sound waves. Acoustic impedance. Far-field and near-field. Sound intensity and sound power. Fundamental acoustic source models. Directivity.
Topic 3.3. The description of sound through levels, decibels and frequency-band spectra. Sound perception and weighting networks.
Topic 3.4. Acoustics of enclosed spaces: direct and reverberant field, average sound absorption coefficient of a room, reverberation time.
Topic 3.5. Sound pressure and sound intensity measurement techniques. Test equipment and test environment. Anechoic and hemi-anechoic chambers, reverberation chambers. Methodologies for estimating sound intensity and sound power levels of noise sources.
Module 4. Interaction between sound waves and solid structures
Topic 4.1. Sound radiation from vibrating structures: formulation of the problem, the Kirchhoff-Helmholtz integral equation, sound radiation from an infinite plate, wave/boundary matching, critical frequency, sound radiation from finite plates, radiation efficiency, Rayleigh’s equation.
Topic 4.2. Sound transmission through partitions: sound transmission through a single rigid panel subjected to a normally incident plane wave, sound transmission through a single flexible panel in case of obliquely incident plane wave and diffuse incident field, transmission loss, double-leaf panels, sound transmission from one room to another, noise reduction.
Topic 4.3. Introduction to finite-element and boundary-element methods for sound field simulation in case of an acoustic enclosure and of free-field radiation. Statement of the problem and corresponding numerical formulation. Examples.
Module 5. Engineering applications and noise and vibration mitigation
Topic 5.1. Overview of noise and vibration transfer mechanisms. Mitigation measures at the source, along the transmission path, at the receiver. Practical examples.
Topic 5.2. Elements of transportation noise (railway noise and tyre/road noise): issues, generation mechanisms, common mitigation measures.

Prova orale obbligatoria
Students will pass the course after successfully taking an oral exam organized in two parts:
questions on the topics covered during the lectures;
discussion on the lab reports (students are requested to prepare short reports on the assignments given during the experimental and computer labs, to be delivered at the final exam).
Part 1. Via this part of the exam, it will be possible to test students’ acquired knowledge and understanding and their ability to independently form judgements and to communicate with a clear and appropriate technical language.
Part 2. The discussion on lab reports is intended to verify students’ ability to apply the acquired theoretical knowledge and the adopted modelling/testing approaches to practical vibroacoustic problems and to evaluate their communication skills.
Final Grading: s tudents will receive a single grade for the entire oral exam (consisting of the two parts illustrated above).

Course handouts available on WeBeep
M.P. Norton, Fundamentals of noise and vibration analysis for engineers, Editore: Cambridge University Press, Anno edizione: 2010
W. Soedel, Vibrations of shells and plates, Editore: Marcel Dekker, Anno edizione: 1981
F. Fahy and D. Thompson, Fundamentals of sound and vibration, Editore: CRC Press, Anno edizione: 2015
A. Nilsson and B. Liu, Vibro-acoustics, Editore: Springer-Verlag, Anno edizione: 2016
F. Fahy and J. Walker, Advanced applications in acoustics, noise and vibration, Editore: Spon Press, Anno edizione: 2004

With a view to enriching the student's preparation with the experimental issues related to Structural Diagnostics and to the evaluation of the Structural Integrity of components and structures, the objective of the Course is to provide the theoretical foundations and the necessary practical experience regarding the application of the methods and tools of Non-Destructive Testing and Evaluation. In addition, the student will learn how to navigate between the different approaches, which he/she will be able to make use of in his/her work, both during the design processes of components and structures, and for the verification of their structural integrity during the production and service (maintenance) stages
For this purpose, numerous experimental experiences are planned on a weekly basis so that the student can apply, firsthand, the methods and tools covered in class and understand in detail their potential, subtleties and application difficulties
More specifically, the objectives of the Course are to:
introduce the methods and tools of Non-Destructive Testing and Evaluation used in industry, in order to assess the structural integrity of components and systems
experimentally apply the methods and tools introduced in lectures to real components and systems, with critical evaluation of results
provide the essentials and general principles on experiment design, instrumentation management and calibration, signal analysis, and analog and digital acquisition techniques

Knowledge and understanding
After the successful completion of the Course and its final evaluation, the student:
knows the methods and tools of Non-Destructive Testing and Evaluation used in industry, in order to assess the structural integrity of mechanical components and systems
learns the essentials and general principles on experiment design, instrumentation management and calibration, signal analysis, and analog and digital acquisition techniques
Ability to apply knowledge and understanding
After the successful completion of the Course and its final evaluation, the student:
is able to experimentally apply the methods and tools of Non-Destructive Testing and Evaluation used in the industrial field, in order to assess the structural integrity of mechanical components and systems
is able to perform quality experiments according to the essential elements and general principles of experiment design, appropriately handle instrumentation, effectively analyze acquired signals, and use both analog and digital data acquisition approaches
Autonomy of judgment
After the successful completion of the Course and its final evaluation, the student:
is able to critically evaluate and verify the results of experiments that he/she has performed
is able to critically evaluate and verify the results of experiments that have been performed by others
Learning ability
After the successful completion of the Course and its final evaluation, the student has performed firsthand several laboratory experiences by independently solving the practical issues which showed up

Introduction to NDT&E: NDT vs. NDE, main aim and basic principle, standardization, qualification and certification of personnel
Defectology of industrial materials and components: inherent, manufacturing and in-service flaws of metals, polymers and composites (mainly lightweight, as resin-based and honeycomb)
Basic principles and inspection/monitoring practice of the main and most widespread industrial methods: visual testing, liquid penetrant testing, magnetic particle testing, eddy current testing, radiographic testing (including digital radiography and computed tomography), ultrasonic testing (including phased array, TOFD and EMAT), ultrasonic guided waves, acoustic emission
Basic principles and inspection practice of some special methods: thermography, shearography and tap testing, extensively adopted in some specific, but still very important, fields, such as resin-based composites (or honeycomb) and adhesive bonded joints
Design of NDT&E inspection procedures: analysing and understanding the context, numerical simulations for inspection design and response interpretation (FEM, CIVAnde), experimental validation of numerical simulations and design of sample blocks, choice of the optimal sensitivity
NDT&E as an element of mechanical design, manufacturing and in-service maintenance: reliability and capability of NDT&E (Probability of Detection, Modal-Assisted Probability of Detection, Multi-Parameter Probability of Detection), damage tolerant design, “design for inspectability”, acceptability levels for indications
Applications and case studies: all the above-mentioned topics will be enriched by deepening the application to and by studying real life cases dealing with metals and welds, transportation (automotive, railway, aerospace and marine), power generation, additive and sustainable smart manufacturing, bioinspired structures, lightweight structures (via composite materials and adhesive bonded joints)
Experimental labs: it is expected to prepare a different either experimental or mixed (experiment + analytical and/or numerical calculation) experience every week of the Course on the topics given during lectures

Prova orale obbligatoria
The final evaluation can be taken at one of the programmed calls on July, September or February and consists of an oral exam carried out by taking an on-site case study among those being performed in the laboratories of the Department of Mechanical Engineering at the moment of the exam. The student must describe and motivate how he/she would choose and set up an effective experimental set-up for Non-Destructive Testing and Evaluation and how he/she would interpret the obtained results
The final examination is designed to test knowledge and understanding of the topics of the Course, the ability to apply that knowledge and understanding to real cases, the autonomy of judgment in choosing the correct and most effective methods for the case at hand and critically evaluating the results, and communication skills in defending and justifying the choices made

Handouts by the Lecturer (available on WeBeeP)
The American Society for Nondestructive Testing Inc., Materials and Processes for NDT Technology, Editore: ASNT, Anno edizione: 2016, ISBN: 978-1-57117-329-4
Note: 2nd Edition
Charles J. Hellier, Handbook of Nondestructive Evaluation, Editore: McGraw-Hill Education, Anno edizione: 2020, ISBN: 9781260441437
Note: 3rd Edition
Aquil Ahmad, Leonard J. Bond, ASM Handbook, Volume 17: Nondestructive Evaluation of Materials, Editore: ASM International, Anno edizione: 2018, ISBN: 978-1-62708-152-8
J. Prasad, C. G. Krishnadas Nair, Non-Destructive Test and Evaluation of Materials, Editore: McGraw Hill Education (India) Private Limited, Anno edizione: 2011, ISBN: 9780070707030
Note: 2nd Edition
D. Balageas, C.P. Fritzen, A. Güemes, Structural Health Monitoring, Editore: ISTE Ltd, Anno edizione: 2006, ISBN: 9781905209019

Obiettivi : Il corso si propone un duplice scopo:
1) approfondire, estendendola al caso multidimensionale, l'analisi agli elementi finiti per problemi ad equazioni alle derivate parziali, in continuità con gli argomenti proposti nel Corso di Analisi Numerica delle Equazioni alle Derivate Parziali I;
2) affiancare l'analisi teorica con esercitazioni in aula e al calcolatore al fine di fornire agli studenti un riscontro sperimentale ed applicativo di quanto appreso.

The course fits into the overall program curriculum and in particular it contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment under the life cycle thinking perspective, and the impact of those factors on business performance towards the entire product life cycle
Identify trends, technologies and key methodologies in the domain of product life cycle management, within a pletora of different application contexts such as industrial design and engineering, mechanics and automation, fashion and food industry
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in business and industrial environments
The aim of the course is to introduce students to the basic concepts of Product Lifecycle Management (PLM) and Life Cycle Thinking. The acronym PLM enables a holistic life cycle-oriented way of thinking through a set of principles, methods and tools supporting a more effective and efficient management of the life cycle stages of industrial products and systems, from their design/engineering, to production, distribution, usage until disposal/end of life.
In its comprehensive meaning, PLM is a business approach based on collaboration and integration of people, processes and technologies, which aims to support the development of more innovative, reliable and sustainable solutions (products and services) in a shorter time.
From a managerial perspective PLM encompass (i) a strategic management point of view where the product is the enterprise value creator; (ii) the application of a collaborative model for the empowerment of the core competences distributed along the different actors involved in the lifecycle (e.g. designers, engineers, manufacturers, suppliers, etc.); (iii) the adoption of a number of IT solutions for establishing an access-safe product information management environment.
From a technical perspective, PLM is a matter of methods, standards and techniques for structuring the engineering processes, as well as a matter of computer-based tools for enabling virtual prototyping and collaborative workspaces.
In this context, Lean Product and Process Development is a paramount support for the effective understanding and accomplishment of the above mentioned points and will play an important role, not only as topic of discussion taught within the course, but also used to generate within the students critical attitude towards problem understanding, problem setting and problem solving.
The aim of the PLM course is to introduce students to the concepts and elements of PLM, life cycle thinking and lean product and process development, from both managerial and a technical perspective, giving also the basics to run the introduction of PLM (as approach, models, methods, and tools) in the industrial practice, approach problems and process improvement via lean thinking, with the ultimate purpose to grow a life cycle thinking attitude into the students.

Expected results from Product Life Cycle Management Class are:
Understand - provide students with the prevalent knowledge in the field of PLM and Life Cycle Thinking from a theoretical and practical side to show how these aspects reflects on real business. The students are expected to gain general knowledge on PLM, life cycle thinking and all related topics.
Identify - students, will gain general knowledge needed to understand PLM, and will be provided with specific knowledge on trends and approaches existing in effective and advanced PLM impelmentation solutions from industry, such as lean product and process development. Students will be expected to be able to identify how specific approaches enable and impact life cycle thinking within enterprises. In the specific lean product and process development as a overall and growing body of knwoledge will be taught to the class that is expected to acquire deep knowledge on that.
Design - most importantly, students will be provided with the ability to aquire and develop a critical thinking attitude in business process understanding and problem solving. This will be achieved through a continuous link between in class theoretical applications and real world applications, as well as challenges proposed to students to be addressed in class via exercises, serious games, projects and teamwork activities. The ultimate purpose is to make this class not as the arrival learning point for these concepts, but to be the starting platform to build and link what has already been learned and what needs to be learned in the future to address growing buiness needs-by applying either what has been introduced in this course or learnt soemwherelse- enable a relentless life cycle thinking mindest.

Course topics include:
-Life C ycle T hinking, P roduct L ife C ycle M anagement, P roduct L ife C ycle phases
-Innovation, New Product Development Process and Concurrent Engineering
-Lean Product and Process Development
-Set-Based Concurrent Engineering (SBCE)
-The Front-End Process
-Design Methods (Design for X: Design for Manufacturing and Design for Environment)
-Value and Function Analyses (QFD & VA/VE)
-Prototyping, Examples from Virtual Prototyping and CAD tools
-Process Mapping and mapping application case
-Collaborative Platforms (PDM & PLM)
-PLM system and PLM system implementation
-PLM Projects Evaluation. Application case s
-Introduction to S ustainable P roduct D evelopment and C ircular E conomy

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Class attendance is not mandatory, though encouraged. All material will be provided digitally on line (Beep). Supporting books and references will also be suggested throughout the course. In-class exercises and teamwork will be used to facilitate advanced learning of PLM material and concepts.
The final exam will be a bout 1,5 hour written test, divided in two part: theory and problems/exercises. Questions are mainly multiple-choice questions + some short open questions. The maximum score achievable through the written exam is 30 Laude.
There are not intermediary evaluations.
Complementing the learning activities, a not-mandatory team project can be conducted to go through some of the topics investigated in class with the purpose of enhance the overall topics understanding, determining an indirect improvement of learning and exam performances. Additionally, the project enables students to gain extra score, at a maximum of 3. Time will be dedicated in class for project and practical activities. The project score does not expire through the months/years. It is not possible to run the project individually.

Ulrich and Eppinger, Product Design and Development
Note: 5th edition
Rossi, Morgan, Shook, The Routledge Companion to Lean Management - Lean Product and Porcess Development Chapter, Anno edizione: 2017
John Stark, Product Lifecycle Management, Editore: Springer, Anno edizione: 2012
Note: 2nd edition

The goal of Materials Engineering, Recycling & Environmental Impact is to enable students to achieve a complete comprehension about the processes and plants aimed at the production of metal alloys (i.e. pig irons, steel grades, aluminium alloys, zinc, copper, nickel, titanium) and at studying the environmental impact of the process and the recycling techniques (even assisted by Artificial Intelligence) to select the scrap, to recover the wasted heat and exploit by-products and wasted residuals. The theoretical concepts about the thermodynamics and kinetics will allow the students to design the correct technological route in order to produce and recycle the metal alloys featured by specific mechanical and corrosion properties and to minimize the environmental impact involved in the production process in terms of polluting emissions and to decrease of the green-house gases. Specific items are focused on the design and material selection to study practical case for food industries (i.e. cans for food and beverages, machinery equipment for food), mechanical and agricultural components through a vision including the Life Cycle Assesment.

Upon successful completion of the exam, the student will be able to:
DdD 1 & 2 – Knowledge and understanding / Applying knowledge and understanding
understand and apply thermodynamic and kinetic principles to design the correct technological route for producing and recycling metal alloys (e.g., pig irons, steel, aluminium, zinc, copper, nickel, titanium) with specified mechanical and corrosion properties;
analyze processes and plants for metal production to minimize environmental impact in terms of polluting emissions and greenhouse gas reduction, including the use of artificial intelligence for scrap selection, waste heat recovery, and by-product exploitation;
DdD 3 & 5 – Making judgements / Learning skills
critically evaluate different production and recycling scenarios for metal alloys, autonomously selecting materials and designing solutions for practical case studies (e.g., food industry cans and machinery, mechanical and agricultural components) based on Life Cycle Assessment (LCA) principles;
DdD 4 – Communication skills
compose a clear and structured technical report that describes the production route, environmental impact assessment, recycling strategies, and material selection choices, and present the findings synthetically to an audience.

1st Item: Fundamentals of thermodynamics and kinetics involved in the production process of the main metallic materials. Fundamentals about the slags and powders used and involved in the production process.(1 CFU)
2nd Item: Production systems for the reduction of the ores (Blast Furnace, Direct Reducing Process, Hydrogen-based process, Electrochemical/Electrowinning Process). (2 CFU)
3rd Item: Techniques for recycling. The electric furnace for the production and recycling: Electric Arc Furnace, Induction Furnace, Resistance Furnace, Gas Furnace. Techniques for capture and use of the CO 2 involved in the process to achieve the carbon neutrality. Electrochemical techniques to separate the base-metals from metal coatings (2CFU).
4th Item: Use of advanced techniques for scrap selection and checks (Artificial Intelligence Based Techniques, Grinding). The market of the raw material (1 CFU)
5th Item: The control of air and water emissions and the correct management of the processes wastes and by products according to the Best Available Technologies as defined by the European Commission.(1 CFU).
6th Item: Pyrolysis techniques for destroying the wasted materials, recovery of CO, CH 4 and H 2 and biochar and biomethane application for soil treatment (even combined with wasted slag) and/or for use in the metallurgical plants.(1CFU
7th item: Design of the final products in order to avoid the leakage of dangerous metals and to allow the complete recycling of the materials and the recovery of the functional metals (i.e. scrap conditioning, zinc recovery, tin recovery etc.). (1CFU)
8th item Practical application of Life Cycle Assesment to define the environmental impact: food and beverage cans, vehicles, agricultural devices and buildings. (1 CFU)
PRODUCTION AND ENVIRONMENTAL IMPACT OF MATERIALS AND ENGINEERING AND STEELMAKING B includes only item 1st, item 3rd, items 5th, item 6th.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, con presentazione/discussione finale
Oral examination and discussion about the performed computational trials.
PRODUCTION AND ENVIRONMENTAL IMPACT OF MATERIALS AND ENGINEERING AND STEELMAKING B covers only item 1st, item 3rd, items 5th, item 6th.

Nicodemi - C. Mapelli, Siderurgia, Editore: AIM, Anno edizione: 2023, ISBN: 978-88-85298-91-1
F. Oeters, Metallurgy of Steelmaking, Editore: Springer Verlag, Anno edizione: 1994, ISBN: 9783514004658

The course aims to provide students with the fundamental concepts for the management of production and logistics systems, integrating theoretical concepts with practical examples. Students are expected to learn the general criteria and methods, and to improve their skills in order to be able to take decisions that affect the management of production systems.
Specifically, the course objectives are intended to develop students’ knowledge and competences about:

• The main features and types of production and logistics systems;
• Advantages and disadvantages stemming from the adoption of different types of production systems;
• The proper Key Performance Indicators to measure the performance of production and logistics systems;
• The process of production planning and scheduling (PPS);
• The main models and methods for demand forecasting, aggregate production planning, inventory management, materials requirement planning and production scheduling;
• Major developments and concepts in production and logistics.
  The course targets the following Goals, within the broader context of the Programme, so as to empower the Student capabilities to:
• Understand context, processes and performance with reference to production systems
• Apply the main models to the management of production systems (for demand forecasting, aggregate production planning, inventory management, materials requirement planning and production scheduling)

The main expected learning outcomes of the course, achievable through lectures and practice, consist in the comprehension of the main criteria and methods for the management of production and logistics systems in industrial management contexts, and the ability to apply them.
In particular, at the end of the course students are expected to be able to:

• Use the proper terminology to describe different configurations of production systems;
• Describe the general features, strengths and weaknesses of different configurations of production systems;
• Define and use the proper indicators and metrics to measure the key performance of production and logistics systems;
• Understand the main problems related to the management of production and logistics systems;
• Apply the reference methods and techniques to solve production and logistics decision problems within a systematic approach;
• Acquire the basic knowledge to effectively interact with company experts and professionals;
• Decide and discuss production and logistics systems elements.

The following topics are presented during the course:

• Introduction to production systems (fabrication, assembly) and taxonomy;
• Performance measurement regarding effectiveness (quality and service) and efficiency (productivity, value, costs);
• Introduction to the management of production and logistics systems: objectives, constraints, decision variables, relevant costs, main phases and methods;
• Demand forecasting: analysis of time series, examples of forecasting techniques;
• Inventory management: the role of inventories, basic models for inventory management (fixed-quantity model, fixed-time period model – s/S/t/q policies), ABC analysis;
• Aggregate production planning: process, examples of models to define the MPS (Master Production Schedule);
• Materials planning: push approaches and the MRP (Materials Requirement Planning) technique;
• Scheduling: example of models and techniques for operational production planning;
• Future developments & management outlook.
  The course contents are delivered through a mix of theoretical and practical lessons (exercises), with the primary goal of providing concrete examples of how to apply the concepts and models discussed in class.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
The exam is a combination of a written test and an optional oral test on the content of the theoretical and practical lessons.
The written test consists of a set of theoretical questions and numerical exercises. The written text is a closed-book exam. The written test aims at highlighting the knowledge of the students, their capacity to communicate and to understand and apply the contents of the course.
The optional oral test aims at highlighting the knowledge of the students and the capacity to make links among the topics of the course.

This teaching program aims to equip students with the knowledge of production planning and control principles, methods, and techniques in the context of nano and micro production systems, covering both the fundamentals and the latest trends.
Upon completion of the program, students are expected to develop a comprehensive understanding of the core concepts and theories of production planning and control processes, to acquire capabilities in fluently applying basic and advanced methods to manage and optimize the planning and control processes in nano and micro production systems, and to effectively communicate of the planning decisions.

By the end of the course, students will have mastered the content and practices as set out in the teaching objectives.
In particular, students will be able to:

• understand the basics and principles of production planning and control in nano and micro production systems (ILO1)
• identify and analyze the problems associated with production planning and control in the context of nano and micro production systems (ILO2.1)
• apply appropriate production planning and control method and technique to the focal production planning and control problem (ILO2.2)
• design solutions and take decisions for the focal production planning and control problem (ILO2.3)
• communicate concepts, strategies, and solutions effectively in the context of production planning and control in nano and micro production systems (ILO3)

Teaching activities are carried out by means of frontal lectures, exercise sessions and other formats, with interventions from the industry.
The topics covered in the course are divided into the following modules:
Module 1: Introduction to Production Systems

• Introduction to Production Systems: Definition and terminologies
  Module 2: Basics of Production Systems (10%)
• Classification of production systems, typologies and characteristics; Classification of assembly systems, typologies and characteristics
• Basics of Nano and Micro Production Systems: Overview of nano and micro production systems, manufacturing technologies, and processes
  Module 3: Basics of Production Planning and Control (10%)
• Key concepts and principles of production planning and control;
• Relevant costs for production planning and control cycle
  Module 4: The Production Planning and Control Cycle for Nano and Mirco Production Systems (60%)
• Demand planning and management; forecasting methods and techniques
• Long/mid-term planning: aggregate planning, capacity planning and resource allocation; master production schedule
• Material management and Inventory management: material requirements planning; Inventory management methods and techniques
• Short-term planning: production scheduling and sequencing, optimization algorithms
  Module 5: Basics of Performance Measurement (10%)
• Performance measurement concepts and terminologies, operating conditions and internal/external performance, performance measurement scorecards
• Performance measurement basics for productive factor, warehouse and services
  Module 6: Advanced Topics and Trends in Nano and Micro Production Systems (10%)
  Note: The syllabus may subject to change at the discretion of the instructor – any changes will be timely communicated to the students. Please refer to the course WeBeep channel.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The assessment of learning outcome will take the form of a combination of group assignment and oral test.

• Oral test, covering all contents introduced and discussed in the lectures, designed to evaluate ability of the students in understanding (ILO 1) and applying (ILO2.2) appropriate principles, method and technique in the area of production planning and control for nano and micro systems and aims to evaluate the ability of the students in communicating and discussing concepts, strategies, and solutions in the context of production planning and control in nano and micro production systems (ILO3).
• Group assignment, developed on specific themes addressed in the lectures, is set to assess the ability of the students in identifying and analyzing the problems associated with production planning and control (ILO2.1) and consequently in drawing up appropriate solutions and decisions based on informed analysis (ILO2.3). Together with the oral test, it also evaluates ability of the students in presenting and justifying strategies and solutions of production planning and control in the context of nano and micro production systems (ILO3).
  Note: The assessment methods may subject to minor changes at the discretion of the instructor. Please refer to the information presented at the beginning of the course.

All lecture materials will be made available on WeBeep WeBeep Channel
Andrea Sianesi, Production systems management: Planning, scheduling, control, measurement and improvement, Editore: Mondadori, Anno edizione: 2021, ISBN: 9788861848924
Toly Chen, Production Planning and Control in Semiconductor Manufacturing: Big Data Analytics and Industry 4.0 Applications, Editore: Springer, Anno edizione: 2022, ISBN: 9783031140655
F. Robert Jacobs, William Lee Berry, D. Clay Whybark, Thomas Vollmann, Manufacturing Planning and Control for Supply Chain Management, Editore: McGraw-Hill Education, Anno edizione: 2011, ISBN: 9780071750318

The course focuses on quantitative methods for modeling, monitoring and improving quality of products and services in actual productive scenarios, characterized by multi-dimensional quality indicators. Techniques for both continuous and ordinal quality data (e.g., survey data) are presented.
After successfully completing the course, students should be able to do the following:
1. Understand the philosophy and basic concepts of quality monitoring and improvement.
2. Extract relevant information from complex, high-dimensional quality data
3. Identify models to predict the expected pattern of quality indicators
4. Design and use appropriate tools to design and manage quality in industrial and service scenarios.

Objective of the course is to introduce the principles of rail vehicle dynamics and of the interaction between rail vehicle and infrastructure, considering the main dynamical aspects and related technical problems such as running safety, ride quality, wear and damage at wheel/rail contact.
At the end of the course, the students will master the principles of railway vehicle dynamics and the main related engineering issues including running stability, curving, longitudinal dynamics, vertical dynamics.

After a positive evaluation at the exam:
1)the student will be familiar with the anatomy of different types of railway vehicles (locomotives, freight wagons, isolated passenger vehicles, articulated train sets) and with typical designs of primary/secondary suspensions in railway vehicles;
2) the student will know the fundamentals of the dynamics of railway vehicles and the main variables affecting the behavior of a vehicle;
3) the student will know the fundamentals of wheel/rail contact modelling and the effect of wheel/rail contact forces on the dynamics of a railway vehicle or complete train set;
4) the student will be familiar with using multi-body simulation packages to model and simulate the running behaviour of a railway vehicle and with evaluating the outputs of the simulations;
5) the student will be able to understand how the loads are transferred to the wheel-rail interface and will have fundamental knowledge about how these loads contribute to the degradation of the contacting surfaces/bodies.

Rail vehicle modelling:
1.1 Detailed rail vehicle structure
1.2 Wheel-rail contact forces: stresses and deformation of contacting bodies, definition of creepages, geometrical aspects of wheel-rail contact, models for contact forces
1.3 Modelling of suspension components.
1.4. Semi analytical models: wheelset on tangent track and curve, bogie on tangent track and curve: dynamics and steady state condition.
1.5 Numerical models: multi-body simulation of rail vehicle dynamics.
Track and infrastructure modelling:
2.1 Track typologies for standard lines, high speed lines and urban and metro lines.
2.2 Modelling of the main track elements: rail, fastenings, sleeper, slab, elastomeric elements.
2.3 Train-track-structure interaction: frequency domain model of train-track interaction.
Lateral dynamics of railway vehicles
3.1 Stability of a wheelset / bogie (incl. Linear vs. non-linear)
3.2 Curving of a wheelset / bogie
3.3 Running safety
Vertical dynamics of railway vehicles
4.1 Human perception of vibration, ride quality indexes
4.2 Rigid-body models
4.3 Effect of car body flexibility
4.4 Excitation from track irregularities and wheel out-of-roundness.
4.5 Stochastic track irregularities, track measuring vehicles
Longitudinal dynamics of railway vehicles
5.1 Running resistance, longitudinal motion of a train as a 1-DOF system
5.2 Inter-car forces, longitudinal dynamics of a train
5.3 Traction and braking control in railway vehicles (in brief)
Damage phenomena at wheel/rail interface
6.1 Wear
6.2 Rolling Contact Fatigue
6.3 Rail corrugation and wheel out-of-roundness

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The grading will be based on the evaluation of a group work, followed by an oral exam.
The group works will be assigned to small groups formed by 2-3 students. While developing their group work, the students will have to apply to a practical case the notions learnt in the course, also using advanced simulation tools. At the end of the course, all groups will present and defend their works.
The partial grading of the group work will be done individually for each student in the group and will be based on the contents of the work and on the performance of the student in the presentation and in the following question & answer time.

Course notes https://webeep.polimi.it/course/view.php?id=20620
Knothe Klaus, Stichel Sebastian, Rail Vehicle Dynamics, Editore: Springer, Anno edizione: 2017, ISBN: 978-3-319-45374-3
Iwnicki, S., Spiryagin, M., Cole, C., & McSweeney, T. (Eds.), Handbook of Railway Vehicle Dynamics, Second Edition, Editore: CRC Press, Anno edizione: 2019, ISBN: 9780429469398 https://doi.org/10.1201/9780429469398

Reverse Engineering (RE) is a multidisciplinary scientific method that can be applied to several different fields. Although in broad sense the term Reverse Engineering is used in many different areas (e.g., from software code development for decode the mechanism of a function, to Internet network security), the version of the concept considered in this course is the digital reconstruction of a physical object or environment, starting from a set of 3D data captured in the real world.
The course aims at illustrating the operating principle of the various 3D sensors currently available on the market, framing them in a general context, specifying their functions and motivating their performance. A substantial practical laboratory activity is planned, during which the students, through individual or group exercises, develop digital 3D models of real objects both with active and passive techniques.

After passing the exam, the student:
knows the theoretical principles of 3D measurement;
knows the basic terms and principles of active and passive sensor measurement technologies;
knows the characteristics of the principal instruments usable for a 3D survey;
Knows the process workflow to go from a real object to a digital 3D model;
Is able to analyse an object or scene to survey and identify the most appropriate measurement system;
Is able to determine in advance the problems of a survey and adopt the appropriate solutions;
Is able to characterize or calibrate an instrument;
Is able to select and execute the working pipeline to obtain a result appropriate to the requirements of the specific work (for example accuracy, resolution, number of model polygons);
Is able to motivate its design choices and communicate the results of its activities in a clear and convincing way.

Theoretical introduction
General information on 3D measurement methods, with and without contact.
Nature of light.
Light-matter interaction.
Taxonomy of non-contact systems based on different forms of radiant energy.
Passive and active 3D sensing techniques.
Active 3D sensors
3D measurement for triangulation:
Laser scanner with single spot, single light plane, multiple light plane.
Full-field measurement based on fringe projection.
Active systems based on measurement of distances:
3D flight time measurement (TOF); direct estimation of flight time (PW); indirect estimation of flight time (CW); indirect estimate of flight time (FM-CW).
Principles of 3D metrology
Characterization of the errors of a range device.
Study of the possible artefacts generated by an active sensor.
Construction of polygonal models from acquired data
Topological concepts.
Working pipeline: draft project; acquisition, meshing; alignment; (Iterative Closest Point algorithm); merge; optimization; editing.
Passive 3D sensors.
Principles of photogrammetry.
Camera calibration.
Structure from motion, image matching, generation of dense 3D clouds.
Creating models from images.
Standard software packages for the realization of the entire Reverse Engineering process with active and passive techniques.

Prova scritta obbligatoria, con prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The overall evaluation will be based on:
attendance at lessons, mandatory with a minimum of 75%.
1 multiple choice theoretical test, based on the contents illustrated in class and the bibliography texts.
The test is structured in order to verify the expected learning outcomes from 1 to 4.
Practical exercises with active and passive acquisition techniques.
The exercises aim at verifying the learning related to the expected outcomes from 5 to 8.
A critical presentation of the work carried out at the end of the course.
The presentation aims to verify mainly the learning outcome expected in point 9.

Course slides https://webeep.polimi.it/
Gabriele Guidi and Fabio Remondino, 3D Modelling from Real Data, Editore: Intech, Anno edizione: 2012, ISBN: 978-953-51-0012-6 https://webeep.polimi.it/
Note: In Modeling and Simulation in Engineering, Catalin Alexandru (Ed.)
Szeliski, Richard, Computer Vision: Algorithms and Applications, Editore: Springer, Anno edizione: 2011, ISBN: 978-1-84882-935-0
Luhmann, Thomas; Robson, Stuart; Kyle, Stephen; Boehm, Jan, Close-Range Photogrammetry and 3D Imaging, Editore: De Gruyter, Anno edizione: 2014, ISBN: 978-3-11-030278-3
Gabriele Guidi, Michele Russo, Jean-Angelo Beraldin, Acquisizione 3D e modellazione poligonale, Editore: McGraw-Hill, Anno edizione: 2010, ISBN: 9788838665318

This course aims at introducing the main concepts related of rotor dynamics and diagnostics.
Rotor dynamics is the key for the design and operation of many machines: turbine of any kind used for power generation, aircraft engines, electrical motors, centrifugal compressors, etc. Thus, the dynamics of the complete machine and of its main components, like shafts, bearings, seals and blades is presented in detail. Several design tools and examples are introduced.
Diagnostics is an emerging requirement in modern mechanical systems in order to shorten out-of-service and reduce operation costs. Very often, the faults are affecting the same components analysed by rotor dynamics and this makes the two parts of the course strictly connected. State-of-the-art techniques, based on both system model and data analysis, are introduced.
All the topics are analysed under practical and theoretical points of view, with several examples of application in real machines, of design cases and of case histories. The seminars, conducted by industry experts, are essential parts of the course.
A visit in a factory of a major OEM in rotordynamics sector is scheduled during the course.
More in detail, the aims of the course are:
To provide tools and methods to define the mathematical model of a rotor system, by considering its main sub-components
To provide the basics for the mechanical analysis of rotating machinery
To provide tools and methods to perform diagnostics of mechanical systems, by considering their main sub-components
To provide the basics for fault and damage diagnostics in mechanical systems
To provide the morphological description of the main sub-components of rotor systems

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
Descriptor
Cycle
Description
1 - knowledge and
Understanding
MSc
Have demonstrated knowledge and understanding within the main field of study, implementing methodologies
appropriate for solving complex problems, both systematically and creatively.
In terms of acquired knowledge and understanding, students will be able to:
know the methodologies and the principles to describe in mathematical terms a rotor system and its main sub-components;
understand and knows how a rotor system is composed;
know the basic aspects of diagnostics of mechanical systems;
know the methodologies to perform diagnostics of some components of mechanical systems;
learns the methods of modeling rotor systems;
Descriptor
Cycle
Description
2 - applying
knowledge and
understanding
MSc
Ability to critically, independently and creatively solve problems with some originality in new or unfamiliar
environments within multidisciplinary context related to their field of study.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
perform the modeling of rotor systems;
understand and describe the functioning of a rotor system;
calculate the dynamic response of a rotor system;
address and analyze basic problems of diagnostics in a mechanical system;
effectively communicate the results of the analysis performed on the dynamics of a rotor system;
effectively communicate the results of the diagnostics of a mechanical system.
Descriptor
Cycle
Description
3 - making
Judgment
MSc
Ability to synthesize and integrate knowledge; Ability to deal with complex issues both systematically and creatively, make sound judgments even on the basis of incomplete or restricted information.
Through lab activities, students will also acquire the skills to formulate a judgment, meaning to analyse the behaviour of rotor systems, to connect the measured data to possible faults, to classify the faults for diagnostic purposes and to compare different fault symptoms.

Rotor dynamics
Finite beam models for lateral and torsional vibrations. Supporting structure modelling. Review of design standards (API, ISO). Flexible rotors balancing
Critical speeds, Campbell diagram, System response to common linear (unbalance, bow, misalignment) and non linear (rub, magnetic fields) excitations
Crack effects
Stability (effects of fluid film bearings, of fluid flow, of magnetic bearings/fields, of squeeze-film dampers)
Fluid-film bearings
Hydrodynamic lubrication, computational hydrodynamics, Geometry of fluid film bearings
Gas bearings
Bearing design (static and dynamic characteristics), Journal bearing testing, Thrust bearing testing, Bearing coating materials, Bearing damages
Effects of electrical pitting
Seals
Geometry, modelling (bulk-flow, and CFD), dynamic characteristics calculation
Brush seals
Abradable seals
Blade dynamics
Blade mechanical design
Excitation causes
Blade vibration
HCF (high-cycle fatigue) failures and correction, LCF (low-cycle fatigue) failures and correction
Damping, snubbing, friction, vibration measurements
Diagnostics
Maintanance policies, condition monitoring, setting of alarms and trips, review of current standards
Model based approach (inverse dynamic problem), with case history analysis (steam, gas and hydro turbines)
Data driven approach (advanced signal analysis: time-frequency transformations, 2nd order cyclostationarity, envelope analysis, spectral kurtosis), with case histories (turbine gearbosx, train traction systems, engine firing)
Special topics
Wind turbine diagnostics
Roller element bearings diagnostics
Gear diagnostics
Seminars (speakers from industry)
Industrial turbine design and operational requirements
Blade design
Technical visit
A visit in a factory of a major OEM in rotordynamics sector is scheduled during the course.

Prova orale obbligatoria
Organization of the course and methods of verification
The course is divided into a series of lessons and practical exercises, related to the topics of the lessons, aimed at consolidating the knowledge and methods learnt during the lessons.
The exam consists of an oral exam.
The oral exam consists in answering questions, in open form, that focus on all the topics covered in the course, accompanying the answering with equations, graphs, sketches, in a synthetic and complete exposition. Depending on specific logistics problems, it could be required to perform the oral exam by answering the questions by composing a written document, which will be discussed with the teacher.
The purpose of the oral test is to verify the knowledge underlying the study of rotordynamics and diagnostics, and the applications covered in the course, evaluating both the understanding of physical phenomena and their mathematical implementation (demonstration). The oral test also verifies the ability to transmit the results of the analyses carried out both in mathematical terms and with graphic representations.
Slides of the lessons, which include all the topics of the course, are provided via BeeP. The bibliography is suggested and can be fruitful consulted for individual in-depth analysis.
Final Grading
To pass the course, students must successfully pass the oral exam

Sl https://webeep.polimi.it/mod/folder/view.php?id=472178
Note: Slides of the lessons
Tadashi Tanuma, Advances in Steam Turbines for Modern Power Plants, Editore: Woodhead Publishing, Anno edizione: 2016, ISBN: 9780081003145
Note: Available on www.biblio.polimi.it - The book is useful for the description of main components of typical rotating machines
Michel Lalanne, Guy Ferraris Lalanne, Rotordynamics prediction in engineering, Editore: Wiley, Anno edizione: 1998, ISBN: 04-7197-288-6
Note: Some hardcopies are available in Polimi libraries
Maurice L. Adams, Rotating Machinery Vibration From Analysis to Troubleshooting, Editore: CRC Press, Anno edizione: 2000, ISBN: 978-0-203-90216-5 http://www.crcnetbase.com/isbn/9780824702588
Note: Available on www.biblio.polimi.it
Childs, Dara W., Turbomachinery rotordynamics: phenomena, modeling and analysis, Editore: Wiley, Anno edizione: 1993, ISBN: 04-7153-840-X
Note: Some hardcopies are available in Polimi libraries
Agnieszka Muszynska, Rotordynamics, Editore: CRC Press, Anno edizione: 2005, ISBN: 0-8247-2399-6 http://www.crcnetbase.com/isbn/9780824723996
Note: Available on www.biblio.polimi.it
Andrew D. Dimarogonas; Stefanos A Paipetis, Analytical Methods in Rotor Dynamics, Editore: Springer Netherlands, ISBN: 94-007-5904-5 http://link.springer.com/book/10.1007/978-94-007-5905-3/page/1
Note: Available on www.biblio.polimi.it

Il corso fornisce una visione completa della tecnologia MEMS, dai principi fondamentali alle applicazioni pratiche, introducendo gli studenti a future prospettive di carriera nel settore della microelettronica. Accelerometri, giroscopi e sensori di pressione fungeranno da casi di studio. Gli argomenti trattati riguardano: le principali tecniche di fabbricazione nell'ambito dei semiconduttori e dei MEMS in particolare (fotolitografia, deposizione, etching, HF vapor release, wafer bonding), i principi di base di progettazione e simulazione, l'integrazione con l'elettronica di controllo e il "packaging", le modalità di test per garantire le prestazioni e l'affidabilità di un dispositivo. Il programma del corso esplora lo sviluppo di un prodotto MEMS dalla prima fase di "ricerca e sviluppo" fino alla produzione e alla qualifica finale. Teoria e pratica si mescolano: esercitazioni di simulazione al computer e attività sperimentali nei laboratori Polifab integrano e supportano le lezioni frontali. Due visite agli impianti industriali di STMicroelectronics offrono agli studenti la possibilità di vedere dal vivo i concetti e le teorie apprese in classe.

The course is aimed at providing the students with sufficient background to allow their efficient interaction with naval engineers in the definition of inputs and the assessment of the outputs for structural analysis and design of a ship. To this aim, the following objectives are pursued:

• untroduce students with generic background (mainly mechanical engineers) to the field of ship structural design and analysis; to this aim, the first part of the course is devoted to the general definitions and illustration of structural components of a generic steel ship;
• provide students with theoretical concepts and practical instruments for design and analysis of ship structures;
• provide students with practical examples of application, referring to realistic case studies;
• illustrate the most common problems affecting ship operation, from structural point of view, and new trends toward operation and maintenance optimization.

At the end of the course, students will have acquired the content and exercise practices as established in the learning objectives.
In terms of knowledge and understanding, students will be able to:

• identify the most common loads acting on the ship structure and determining the stresses for ship design and verification
• understand best practices for ship structural analysis and assessment according to standards
• appreciate the future trends of research in the context of ship design, operation and maintenance
  Regarding the application of acquired knowledge and understanding, students will be able to:
• calculate stresses and perform structural analysis and assessment of primary ship elements (including joints)
• apply the theoretical aspects to realistic use cases, based on Finite Element Simulation
  The active participation of students in the proposed teaching activities is encouraged through the use of an interactive teaching method based on a combination of lectures and practical group activities. In particular, these exercises aim to directly involve the students and analyze real-world issues from a firsthand perspective.
  Critical team discussions primarily facilitate the acquisition and subsequent enhancement of problem-solving skills and independent judgment. The following phases will be addressed during the practical activity, under the guidance of the instructor:
  1. problem definition and active discussion in macro-groups;
  2. generation of alternatives: Students, typically exposed to lectures and closed problems, are invited to develop creative solutions to the given question;
  3. evaluation of alternatives: The ability to select, separate, and reorganize emerging design choices is stimulated;
  4. practical implementation of theoretical solutions and possible presentation of the obtained results.
  Finally, the students will have improved their communication skills, specifically their ability to correctly formulate design problems and/or structural verification using appropriate technical language combined with proficiency in the necessary methodologies for their solution. The use of specific terminology is enhanced both during the learning phase in the exercises and during the evaluation phase in the completion of written and oral exams and/or the potential presentation related to the laboratory activity.

The course covers the following topics:

• Design of joints (welded and bolted connections)
• Buckling analysis of pillars
• Analytical description of plate bending elastic problem
• Unstiffened and stiffened plate buckling
• Fatigue of weldings
• Operation and maintenance of ships (current and new trends)
  The theoretical aspects introduced in the course will be correlated with practices and laboratories, for a direct implementation of the methods.
  Specific laboratory experiences will be dedicated to the application of Finite Element theory for static linear and nonlinear (buckling) analysis with emphasis on result post-processing, their critical analysis and presentation.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, senza presentazione/discussione finale
The final exam will consist of a written examination and the delivery of a report on a limited number of practices.
The written exam will include theoretical questions and possibility to solve simple exercises.
The report will be assessed based on a 0-8 points scale, and will concurr to the final grade.

Hughes, Owen F.; Paik, Jeom Kee, Ship Structural Analysis and Design
All material will be provided digitally on line (WeBeep).

The course provides a survey about the main groups of materials with special functional properties, classified as “smart materials” owing to their ability to fulfil special functions other than the load-bearing ability, in some instances by reacting to changes or stimuli coming from the environment. Aspects related to their structure, physical and mechanical properties, manufacturing routes, application-oriented design and case studies are covered. As introductory topics to the course, concepts about physical metallurgy of materials will be recalled and several non-conventional applications of ferrous and nonferrous metals and alloy exploiting some of their peculiar functional and structural properties will be reviewed.

After attending the course, the student will:

• have a wide knowledge about the scenario of metal-based and ceramic-based alloys that can be used as smart materials for the design of devices and components;
• have basic understanding about the phenomena leading to the achievement of specific properties.
• know how the properties of these materials can be modified and affected by the manufacturing processes;
• be able to critically select the proper material for any specific design application.

1. Recall about the principles of physical metallurgy and of the production and transformation process of materials, introducing the relations among manufacturing route, material structure and achievable properties.
2. Traditional and non-conventional applications of ferrous and nonferrous metals. Review about properties of special steels and cast irons, application-oriented selection of non-ferrous alloy considering their strength and physical properties (e.g Al, Mg, Ti, Cu, Ni alloys).
3. Concepts about composite materials and their applications in industrial fields (lightweight design, wear resistant tools, structural ceramic-matrix composites)
4. Principles and applications of shape-memory and superelastic alloys.
5. Design criteria and applications of materials for thermal storage.
6. Porous materials and lattice structures for lightweight design and other opportunities as smart materials.

Prova scritta obbligatoria, con prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam of Smart Materials consists of a written test with 3/4 questions about selected topics, where the students will summarize what they have learnt during the course. A further contribution to the evaluation includes the preparation and presentation of a project work where students in team can propose a project idea about the application of a smart material to originally fulfil a special function for a practical application. The project work is not mandatory, those students who will present it successfully will gain and additional score for the final exam evaluation.

Slides about lectures will be made available through We-Beep channel
Reza Abbaschian, Robert E. Reed-Hill, Physical Metallurgy Principles, Editore: Cengage Learning Publisher, Anno edizione: 2009
Michael F. Ashby and David R. H. Jone, Engineering Materials 1 - An Introduction to their Properties and Applications, Editore: Butterworth Heinemann Publisher, Second Edition, Anno edizione: 2001
Michael F. Ashby and David R. H. Jone, Engineering Materials 2 - An Introduction to Microstructures, Processing and Design, Editore: Butterworth Heinemann Publisher, Second Edition, Anno edizione: 1999
A selection of the most updated scientific papers reviewing the state of the art about smart materials will be collected

The course provides a survey about the main groups of materials with special functional properties, classified as “smart materials” owing to their ability to fulfil special functions other than the load-bearing ability, in some instances by reacting to changes or stimuli coming from the environment. Aspects related to their structure, physical and mechanical properties, manufacturing routes, application-oriented design and case studies are covered. As introductory topics to the course, concepts about physical metallurgy of materials will be recalled and several non-conventional applications of ferrous and nonferrous metals exploiting some of their peculiar functional and structural properties will be reviewed.

After attending the course, the student will:

• have a wide knowledge about the scenario of metal-based and ceramic-based alloys that can be used as smart materials for the design of devices and components;
• have basic understanding about the phenomena leading to the achievement of specific properties.
• know how the properties of these materials can be modified and influenced by the manufacturing processes;
• be able to critically select the proper material for any specific design application.

Recall about principles of physical metallurgy and of production and transformation processes of materials, introducing relations among manufacturing route, material structure and achievable properties.
Traditional and non-conventional applications of ferrous and nonferrous metals. Review about properties of special steels and cast irons, application-oriented selection of non-ferrous alloy considering their strength and physical properties (e.g Al, Mg, Ti, Cu, Ni alloys).
Principles and applications of shape-memory and superelastic alloys.
Design criteria and applications of materials for thermal storage.
Porous materials and lattice structures for lightweight design and other opportunities as smart materials.
Properties and applications of composite materials (Metal, Polymer & Ceramic Composites)

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
The Smart Materials exam generally consists of a written test with four questions on selected topics, in which the student summarizes what they learned during the course. An optional oral exam may also contribute to the assessment. The oral exam can be chosen by the student and, if passed, can add an additional score to the final grade.

Reza Abbaschian, Robert E. Reed-Hill, Physical Metallurgy Principles, Editore: Cengage Learning Publisher, Anno edizione: 2009
Michael F. Ashby, David R. H. Jone, Engineering Materials 1 - An Introduction to their Properties and Applications (2nd edition), Editore: Butterworth Heinemann Publisher, Anno edizione: 2001
Michael F. Ashby, David R. H. Jone, Engineering Materials 2 - An Introduction to Microstructures, Processing and Design (2nd Edition), Editore: Butterworth Heinemann Publisher, Anno edizione: 1999
Slides about lectures will be made available through We-Beep channel

The course is aimed to achieve a deep comprehension about the principles of solidification and welding metallurgy, as well as the most common welding processes for metals and their alloys. The fundamentals of solidification of metals are presented and the main industrial welding processes are discussed in depth. The fracture toughness of welded joints is also discussed and guidelines for its experimental evaluation are provided.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to understand the metallurgical requirement involved by the solidification and transformation during welding.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to define a correct welding process to obtain the required metallurgical features strictly related to the mechanical resistance.
Through presentation of scientific paper, students will also acquire the skills to formulate a judgment, namely to analyse the soundness of the processes referred to the final properties required.
Furthermore, through the assigned case study students will gain the ability to autonomously compare different technologies and different metallurgical conditions to choose the best solution.
Finally, students will improve their communication skills, being able to discuss their case studies through presentations (flipped classrooms) during the course itself and through written report at the end of the course.

The course contents are delivered through lectures.
The course covers the following topics divided in modules as per the description below:
Module 1 Introduction to Solidification: Nucleation in pure liquids; Solidification of Binary Alloys; Solidification Modes; Solidification Parameters.
Module 2 Welding: Fusion Welding Processes; Heat Flow in Welding; Residual Stresses and Distortion.
Module 3 The Fusion Zone: Weld Metal Solidification; Post-Solidification Phase Transformations; Weld Metal Chemical Inhomogeneities; Weld Metal Solidification Cracking.
Module 4 The Partially Melted Zone: Formation of the Partially Melted Zone; Problems associated with the Partially Melted Zone.
Module 5 The Heat-Affected Zone (HAZ): Formation of the Heat-Affected Zone; Problems associated with the Heat-Affected Zone.
Module 6 Quality testings & Fracture Toughness of Welded Joints: tensile test; shear test; impact thoughness (Charpy test); bending test; hardness; Elastic-Plastic Fracture Mechanics (CTOD, J-Integral, etc.); Crack Growth Resistance Curves; Standardized Methodologies for Fracture Toughness Evaluation.

Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
Evaluation
Students will be continuously evaluated through the conduction of flipped classrooms, each for each of the modules in the course. To deepen the knowledge and the familiarity with the welding features, some question about the courses could be done during the presentation. Moreover, a practical project in form of short paper or proceeding or report will be presented and discussed at the end of the course, based on actual experimental results. The project will be a case-studies related to a welding process and to the microstructural evolution associated. The project will be executed by revising scientific papers and related bibliography.
Final Grading
Each of the flipped classrooms will be evaluated for maximum 6 points per presentation, for a total score of 24. Final project accounts for maximum 9 points. Thus, maximum evaluation mark will be 33 (= cum laude).
An oral examination will always be possible to supplement, improve or consolidate the evalutation obtained through participatory teaching tools.

K. Easterling, Introduction to the Physical Metallurgy of Welding, Editore: Butterworth-Heinemann, Anno edizione: 1992, ISBN: 9781483141664
S. Kou, Welding Metallurgy, Editore: Wiley-Interscience, Anno edizione: 2003, ISBN: 9780471434917
K. Weman, Welding Processes Handbook, Editore: Woodhead Publishing, Anno edizione: 2012, ISBN: 9780857095107
J. Dantzig, M. Rappaz, Solidification, Editore: CRC Press, Anno edizione: 2017, ISBN: 9782940222971

The capability to conceive and generate digital representations of their products and projects is an essential skill for engineers. As the design and manufacturing technologies advance, the shape of the products evolves as well, becoming more and more complex. This course aims at giving students the ability to make 3D models of complex shapes through surface modeling approaches and understand the role of this technology in different phases of the product development process. The course will present an introduction to 3D surface modeling techniques and their applications in Engineering. The mathematical foundation of parametric curves and surfaces (splines, Bezier, NURBS) will be briefly presented. Beyond the theory, the course will adopt a hands-on approach by allowing students to practice with modern computer-aided design tools. Different 3D models of both aesthetic surfaces and technical surfaces (e.g. ship hull, airfoils, blades, etc.) will be made and discussed. Finally, the capability to prepare those models for numerical analysis will be also discussed.

Upon completion of the course, students will be able to:
understand the theoretical foundations of CAD tools and 3D surface modeling techniques, and explain the role of surface modeling in the product development process;
create complex 3D models using surface modeling techniques and develop suitable modeling strategies for different engineering applications;
assess the suitability of 3D models for specific applications, including numerical analysis;
communicate design choices, modeling strategies, and project results effectively through technical presentations and discussions.

The course covers the following topics:

• Introduction to surface modeling: the role in the product development process and comparison with solid modeling.
• Mathematical foundation of parametric curves and surfaces. The Bézier, Spline, Coons and NURBS both in their rational and non-rational forms will be introduced. The concept of geometric continuity will be discussed.
• Surface modeling approaches: Freeform, patch and subdivision surface.
• Algorithmic and generative approaches to surface generation.
• Reverse Engineering: from point clouds/meshes to surface models.
• Implications of surface topology and geometry for numerical analysis and mesh preparation.
• Strategies to approach the modeling of complex objects with applications and examples to specific domains, such as p roduct design, marine, wind, automotive and manufacturing.
  The course contents will be delivered through lectures and laboratory activities using a 3D modeling software.

Prova scritta obbligatoria, con prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will be evaluated through both an individual test and a project assignment, designed to assess their understanding of the course topics and their ability to apply the acquired skills in practice.
The individual test is a multiple-choice test and accounts for 30% of the final grade.
The project assignment accounts for 70% of the final grade. The topic of the project is free, but some proposals will be presented during the last month of the course. The project evaluation will be based on the project material, including 3D models, and the quality of the presentation. Generally, the project will be carried out in groups, but individual projects will also be allowed.

Gerald Farin, Curves and Surfaces for Computer-Aided Geometric Design, Editore: Elsevier, Anno edizione: 2014, ISBN: 978-0-12-249052-1
Michael E. Mortenson, Geometric modeling, Editore: Wiley, Anno edizione: 1997, ISBN: 978-04-7112-957-8
Slides and lecture notes on webeep www.webeep.com

Questo corso fornisce agli studenti competenze relative alle curve e alle superfici per il Computer-Aided Design. Pur concentrandosi sulle tecniche di modellazione per superfici, si discuterà del ruolo delle curve e delle superfici nel design computazionale, nella robotica e nella produzione manifatturiera. Il corso copre le basi matematiche delle curve e delle superfici parametriche, tra cui splines, Bézier e NURBS, e fornisce numerosi esempi delle loro applicazioni in ingegneria. Inoltre, verrà adottato un approccio fortemente applicativo, con sessioni pratiche con software CAD per modellare superfici sia tecniche che estetiche, attraverso casi studio reali nei settori Automotive, Navale e Product Design.Infine, il corso approfondirà le implicazioni della topologia delle superfici nell'analisi numerica e nella preparazione delle mesh.

The course "Bio-Inspired Design" is delivered as an independent module offered to diverse tracks or as integrated course "SYSTEMS BIOLOGY AND BIOINSPIRED DESIGN" as fundamental module of the Bio-Inspired Engineering Track.
The “Bio-Inspired Design” course offers interdisciplinary, advanced design competencies and critical thinking skills, exploiting the lessons learned from nature and showing how this knowledge can lead to more creative and sustainable engineering solutions. It provides theoretical competencies and application skills to build a conceptual model of a product or a process with a system thinking perspective, extract design principles from natural solutions, apply heuristics for triggering idea generation, and guide a problem-driven or a solution-driven bio-inspired design process.

By the end of the course, the students will be able to:
Knowledge and understanding
discuss how biological systems can work to solve engineering or design problems
know the working principles of bioinspired design and biomimetic design
understand analogical reasoning and design by analogy
Apply the acquired knowledge and understanding
build a conceptual model of a product or a process
apply system thinking to engineering problems
extract design principles from natural solutions
apply heuristics for triggering idea generation for conceptual design and problem-solving
guide a problem-driven or a solution-driven bio-inspired design process
Further developed skills
develop familiarity with reasoning across disciplines to come up with novel solutions
develop collaboration abilities through interaction with the team-mates
develop learning abilities by autonomously acquiring information and data needed for the advancement of the project activities

Problem-driven and solution-driven bio-inspired design process
Analogical reasoning and design by analogy
Models and tools of system thinking
Conceptual models of products and processes (e.g. mind map, functional model, event diagram, cause-effect diagram)
Working principles of bioinspired design and biomimetic design
Heuristics for stimulating idea generation (natural solutions, Biomimicry Life’s principles, TRIZ key concepts)
Biological information retrieval in problem-driven design processes
Extracting design principles from natural solutions

Prova scritta obbligatoria, senza prove in itinere
The course consists of lectures and practice sessions.
The evaluation is based on an individual written test based on the practice sessions proposed in the semester: more specifically, the assessment consists of a written open-book individual test with exercises similar to those proposed within the practice sessions, aimed at checking the acquisition of the knowledge and related application abilities, as well as learning and communication skills.

Benyus J., Biomimicry:Innovation Inspired by Nature, Editore: Perennial, Anno edizione: 1998
Bar-Cohen Y., Biomimetics, Biologically Inspired Technologies, Editore: CRC/Taylor & Francis, Anno edizione: 2006

The course aims to provide the basic concepts of topology optimization with reference to structural optimization and lightweight design. At first, historical notes on topology optimization methods are provided.
Size and topology optimization approaches of frame structures will be discussed, with reference to static and dynamic loading conditions.
Density-based topology optimization approaches will be introduced. Design parametrization and interpolation schemes will be discussed, along with computational algorithms and related issues (checkerboards, mesh independence filtering etc.).

By the end of the course, students will learn contents and practices according to the objectives of the course.
In terms of knowledge and understanding, the course will allow students to:
understand the basic concepts of constrained optimization and convex programming
understand the general formulation of a topology optimization problem
understand the theoretical foundations and application techniques related to the numerical solution of topology optimization problems
In terms of application of the acquired knowledge and understanding, students will be able to:
perform structural calculations and formulate a structural optimization problem
set-up and apply numerical methods based on convex approximation to solve simple topology optimization problems.
set-up and solve a sizing and topology optimization problem by means of finite elements
Through exercises and project, students will also acquire the ability to formulate independent judgment, namely:
to evaluate critically and motivate the results of a topology optimization problem
to acquire teamwork skills and practical experience in applying topology optimization for solving actual engineering problems

The topics covered in the course deal with:
1) Introduction. The basic idea of topology optimization, classification among size, shape and topology optimization approaches. Brief historical notes on the method.
2) The general formulation of topology optimization problems. Basic terminology, objective function, design variables, constraint. Nested formulation.
3) Basics of convex programming. Definition of local and global optima. Definition of convexity. Necessary conditions for constrained optimization (KKT) and graphical interpretation. Lagrange multipliers and Lagrangian duality.
4) Numerical solutions based on convex approximations. Explicit approximation with Sequential linear programming (SLP). Convex linearization (CONLIN) and Method of Moving Asymptotes (MMA).
5) Topology optimization of truss structures.
6) Sensitivity Analysis. Numerical and analytical methods for sensitivity analysis, direct and adjoint methods.
7) Topology optimization of distributed parameter systems. From the variable-thickness sheet problem to the general 3D problem and necessity to penalise intermediate densities. Material parametrization and interpolation schemes (SIMP, RAMP…).
8) Well-posedeness of the continuum formulation problem and numerical issues. Numerical issues (checkerboards, mesh dependency, local minima….). Restriction of the set of solutions (filters, constraints on design gradient....). Relaxation by allowing optimal microstructures (homogenization).
9) Introduction to the level-set Method and application of topology optimization to dynamic and multiphysic problems.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
The exam will be oral. There are no partial tests.
During the oral exam, the student will be offered at least two open questions on the topics covered in the lectures and in the exercises. Short numerical exercises may also be required.
Project report Discussion

• report presentation
• discussion of the results
  The questions are formulated in order to verify the achievement of the expected results from the module.
  To pass the course, students must successfully pass the oral test and complete the project report.
  The final mark is the non-weighted mean of the marks obtained answering the questions and discussing the report.

Peter W. Christensen, Anders Klarbring, An Introduction to Structural Optimization, Editore: Springer, Anno edizione: 2009
F. Ballo, M. Gobbi, G. Mastinu, G. Previati, Optimal Lightweight Construction Principles, Editore: Springer, Anno edizione: 2021
M. Bendsoe, O. Sigmund, Topology Optimization - Theory, Methods and Applications, Editore: Springer, Anno edizione: 2004

The course aims at studying the dynamics of road vehicles and how to control them. Models are developed adopting several methodology and different complexity levels from simple linear models to multibody models. Tire-road contact forces are analyzed and modeled. Then vehicle longitudinal, lateral, and vertical dynamics are studied to evaluate the vehicle performance, handling capability, and comfort. Some relevant control systems like active suspensions, ABS, VDC, and others are presented.

At the end of the course, students will develop theoretical and practical knowledge of the basic principles and problems of vehicle dynamics and control as established in the course objectives.
Knowledge and understanding
After passing the exam student will:
know the methods and principles of modeling a real vehicle with mathematical models based on concentrated bodies, distributed bodies, and multibody approach.
understand and know how to study vehicle stability by adopting linearized equations of motion.
know and understand the stability and safety conditions of a vehicle in full operating nonlinear region.
know and understand how the individual parts of the vehicle work: chassis, suspensions, tires, etc. and their effect on the dynamics of the vehicle itself.
demonstrate knowledge and understanding within the main field of study, implementing methodologies appropriate for solving complex problems, both systematically and creatively.
Ability to apply the acquired knowledge and understanding
After passing the exam students will be able to:
critically, independently, and creatively solve problems with some originality in new or unfamiliar environments within multidisciplinary context related to the field of vehicle dynamics and control.
perform modeling with "N" degrees of freedom of the vehicle for comfort, performance, and handling analysis.
write a Matlab® or Simulink® code to simulate the vehicle dynamic behavior (referred to in the previous point).
use some commercial multibody codes (ADAMS®, VI GRADE®, CAR MAKER®) to simulate the behavior of the vehicle exploiting the capacities relative to the previous points.
calculate the motion of the vehicle and the forces transmitted to the environment.
design the vehicle from the point of view of its dynamic behavior.
organize and communicate the results of laboratory tests and simulations activities.
synthesize and integrate knowledge with knowledge gathered form previous courses.
deal with complex issues both systematically and creatively.
make sound judgments even based on incomplete or restricted information.
carry out optimizations of vehicle dynamic behavior taking into account the characteristics and performance of the individual subsystems looking the vehicle as a complex system.
Making Judgment
Through numerical lab activities, students will also acquire the skills to formulate a judgment, meaning to analyse, explain, connect, classify, compare, explain physical problems and find the best methodology to solve specific task.
Communication skills
Students can communicate their conclusions and recommendations with the argumentation of the knowledge and rationale underpinning these, to both specialist and non-specialist audiences clearly and unambiguously.
Finally, students will improve their communication skills, being able to
Use appropriate lexicon related to automotive and mechanical engineering field.
Organize and comment results, experimental and numerical data, in a correct, critical and responsible way.
work in team for a project
Learning skills
Furthermore, through the assigned activity, group numerical labs, case studies, students will gain the ability to autonomously, integrate and design solutions to problems related to road vehicles dynamics and control, applying the skills to judge,compare, select, test, and to present the results explaining and summarizing.

The course contents are delivered through lectures and numerical lab activities.
Module 1 General notions.
Topic 1.1 The dynamic behavior on the straight line and cornering of the vehicle
Topic 1.2 Concepts of "performance", "handling", “stability”, "ride comfort" and “safety”.
Module 2 Analysis of vehicle dynamics with Multi-Body techniques.
Topic 2.1 Definition of space kinematics. Equations of motion in matrix form for nonlinear systems: the minimal set and the Lagrange multipliers methods.
Topic 2.2 Steady state and transient conditions, linearization; perturbed motion analysis.
Module 3 The characteristics of the tire-road contact forces.
Topic 3.1 Tire-road: definition of slips and slip angles, force characteristics, generalities, and dependencies with respect to most relevant quantities.
Topic 3.2 Brush model for pure longitudinal slip, pure lateral slip, combined slip.
Topic 3.3 Magic Formula, transient tire models.
Module 4 Vehicle longitudinal dynamics
Topic 4.1 Longitudinal dynamics, acceleration and braking motion, aerodynamic forces (notes)
Topic 4.2 Cruise control.
Topic 4.3 Braking system generalities, optimal force distribution, EBD, ABS
Module 5 Vehicle vertical dynamics
Topic 5.1 The irregularity of the runway: random vibrations, track and road irregularity. Human response to vibration, and effects on health.
Topic 5.2 Vehicle models for vertical dynamics, comfort indices (regulations),
Topic 5.3 Active suspensions system. Active and semiactive dampers. Skyhook control law.
Topic 5.4 Chassis deformability effects.
Module 6 Vehicle lateral dynamics
Topic 6.1 Analysis of lateral dynamics. General behavior, definition of vehicle kinematics
Topic 6.2 Dynamics of the car on the straight line and cornering with simplified and complex models; steady state and transient definition;
Topic 6.3 linearization and stability analysis; vehicle over and under steering concepts, handling diagrams.
Topic 6.4 Simulation of the behavior on the straight and cornering of the complete vehicle (MB models). Safety and regulations.
Topic 6.2 Control of vehicle lateral dynamics, ESP and Torque Vectoring, and active rear wheel steering.
Topic 6.6 Driver model

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Organization of the course and verification method
The exam consists of a final mandatory oral test. During the test, the students are asked to discuss about the topics presented in lectures and labs supporting their answers with equations and diagrams.
Knowledge of the models and critical analysis are both tested and requested to obtain a positive evaluation.
Results from numerical and experimental laboratories are discussed during the exam. Students must submit a written report at the time of the final test containing the results obtained during their laboratory activities, which will be discussed and examined.
Final Grading
The final grade is given by the student performance in the oral test. The grade accounts for the student capability in:
writing equations of models presented in the course explaining the physical meaning of the written equations,
clearly and rigorously presenting the required arguments and related demonstrations,
discussing and justifying the meaning of the modeling procedures and starting hypotheses,
arguing and analysing the results in the form of graph,
discussing the numerical lab results

F.Cheli, G.Diana, Advanced Dynamics of Mechanical Systems, Editore: Springer, Anno edizione: 2015
Lesson/esercise notes https://webeep.polimi.it/
H. Pacejka, Tire and Vehicle Dynamics, Editore: Butterworth-Heinmann
J.Y.Wong, Theory of Ground Vehicle, Editore: Wiley & Sons
M.Guggiani, The Science of Vehicle Dynamics, Editore: Springer
W.F. Milliken, Race car vehicle dynamics

The course is aimed at studying and developing vision-based 3D measurement techniques, such as stereoscopy, time-of-flight, fringe projection and photogrammetry, with a hands-on approach. 3D scanning prototypes based on different scanning principles will be developed during the laboratory classes, so that the students to participate actively to the teaching activities. The course will include the description of many real applications of 3D vision systems developed by the professor and his staff in cooperation with other Universities and Companies. The exam is based on the discussion of a project that the students, alone or in small groups, develop during the semester, under the guidance of the teaching staff.

In terms of acquired knowledge and understanding (DdD1), students will be able to:
know the fundamentals of image acquisition and how to set-up an image acquisition system,
examine the critical issues in a specific 3D measurement application to find the correct solution,
understand the working principle of the most common 3D scanners,
develop custom 3D scanners,
properly use commercial 3D vision-based systems,
estimate the uncertainty associated to the measurement.
Concerning the ability to apply the acquired knowledge and understanding (DdD2), students will be able to:
design the appropriate measurement approach for each 3D vision-based measurements in the most common industrial applications,
correctly select the most appropriate hardware for each specific 3D scanning application,
propose a test methodology for the performance qualification of 3D vision-based measuring systems.
Through project and lab activities and experiments, students will also acquire the skills to formulate a judgment (DdD3), meaning to understand the critical issues in 3D vision-based measurement techniques and find the correct measuring and processing approach.
Furthermore, students will improve their communication skills (DdD4), being able to write a synthetic report about the case study proposed in the course.
Furthermore, through the assigned group project, students will gain the ability to autonomously integrate (DdD5) commercial scanners provided in the lab with processing units to create a working prototype.

The course contents are delivered through lectures and lab activities. The slides of the lessons will be available for the students in advances and contain all the information needed for the course. The support books listed in the references can be useful for further analysis of the topics but are not compulsory.
The course covers the following topics divided in modules as per the description below:
Module 1: Image acquisition techniques and systems
Topic 1.1: introduction to the image acquisition techniques, line scan and area scan sensors, sensor technologies
Topic 1.2: Smart cameras
Module 2: Image processing
Topic 2.1: operators on single pixels, on image subsets and on the full image. Convolution operators and image transformation
Topic 2.2: 2D camera calibration to compensate for perspective and distortion due to the lens
Topic 2.3: image processing techniques to extract measurements from images: edge detection, blob analysis, pattern matching and geometric matching
Module 3: 3D measurements and scanning of shapes
Topic 3.1: Basic theory of image generation: pinhole cameras, optical aberration modelling
Topic 3.2: Stereoscopy theory and applications: calibration of stereoscopic system and algorithms for 3D measurements.
Topic 3.3: Pose estimation for 3D tracking of targets with a single camera
Topic 3.4: Structured light scanners: Fourier Transform Profilometry and Lidars
Topic 3.5: Digital Image Correlation for 3D shape recovery and for the estimation of 3D strain field
Topic 3.6: Time-of-Flight cameras and LiDARs
Topic 3.7: Photogrammetry fundamentals and applications
Module 4: 3D data processing and storage:
Topic 4.1: Techniques to enhance the accuracy of the 3D measurement result. Effect of motion on scanning accuracy and enhancement strategies
Topic 4.2: algorithms for point clouds processing, standard file formats for 3D data management and storing (VRML, IGES, STL,…).

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The students, alone or in small group of up to 5 people, will be asked to develop a project in the ambit of the course. The professor will assign the topic of the project also considering the main interest of the student. The professor, to offer the students the necessary support, will periodically review the development of the projects.
Students’ skills and knowledge will be evaluated by an oral exam that will focus on the discussion of the developed project.
Project
Every group of students is asked to develop a project, using hardware provided in the laboratory and prepare a short final report that will be used in the oral test, where the discussion of the work will be done.
Oral test
In the oral exam each student is expected to present the project, discuss it to demonstrate that it has been developed setting-up the image acquisition system correctly (correct measurement approach and hardware selection), considering the potential critical issues for the specific application and evaluating correctly the quality of the obtained results.
Final Grading
The students will have to show good capability to present their job and to discuss it with proper technical language, justify the choices and assumptions, after having shown good critical approaches to the problems faced in the work.

Richard E. Woods Rafael C. Gonzales, Digital Image Processing, Editore: Pearson, ISBN: 9789332570320
Note: The main reference are the slides and the digital documents provided by the professor. This is and additional (non mandatory) material.
Hubert Schreier, Jean-Jos Orteu, Michael A. Sutton, Image Correlation for Shape, Motion and Deformation Measurements, Editore: Springer US, Anno edizione: 2009, ISBN: 978-0-387-78746-6
Note: The main reference are the slides and the digital documents provided by the professor. This is and additional (non mandatory) material.
An Invitation to 3-D Vision https://www.eecis.udel.edu/~cer/arv/readings/old_mkss.pdf
Note: The main reference are the slides and the digital documents provided by the professor. This is and additional (non mandatory) material.

Actuators are key enabling components in mechatronic systems, as they determine how control inputs and energy are transformed into physical motion or force. This course provides students with the theoretical and methodological tools needed to understand, compare and select different actuator technologies, with particular attention to their role within integrated mechatronic architectures.
The course covers both conventional and smart actuators, addressing their operating principles, performance limits, control requirements and typical fields of application. Students will learn how to evaluate actuator solutions in terms of force, displacement, bandwidth, efficiency, dynamic response, integration constraints and compatibility with the overall system requirements.

By the end of the course, students will be able to:

• critically compare different actuation technologies, including both conventional and smart actuators;
• select the most suitable actuator for a given mechatronic system, taking into account the functional requirements, performance constraints and integration needs of the application;
• design and synthesize control strategies that enhance the performance, efficiency and operational capabilities of the selected actuator.

Introduction
Part 1: Fluid Power Actuators
Proportional Valves: electromagnetic and electromechanical converters, electrohydraulic and electro-pneumatic valves
Switching Valves: electrohydraulic and electro-pneumatic valves
Fluid Power Motors: hydraulic and pneumatic motors
Controller Types: various controller types used in fluid power systems
Part 2: Electromagnetic Actuators
Self-Clocked Motors with Mechanical Commutator: electrically excited DC motors, permanent-magnet DC motors, pulsating-current DC motors, AC commutator motors
Self-Clocked Motors with Electronic Commutator: brushless DC motors, servo motors, switched reluctance motors
Externally Commutated Motors: asynchronous motors, synchronous motors, stepper motors
Limited Motion Drives: electromagnets, voice-coil motors
Control Methods: closed and open loop control techniques
Part 3: Smart Actuators
Piezoelectric Actuators
Magnetostrictive Actuators
Shape Memory Alloy Actuators
Actuators with Electrorheological and Magnetorheological Fluids
Soft Actuators: Electroactive polymers.
Microactuators
Students interested in deepening their knowledge on specific topics are encouraged to reference the books listed below.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
The exam consists of two parts: a written test and an oral interview.
In the written test, students will be asked to select and size an appropriate actuator for a given mechatronic application. This part assesses their ability to apply theoretical concepts to practical engineering problems, compare alternative actuation technologies, and justify their choices on the basis of performance requirements and design constraints.
The oral interview will cover the topics discussed during the course. It is intended to assess the students’ understanding of the underlying principles, their ability to discuss technical aspects in a clear and rigorous way, and their capacity to justify design and control choices.
Overall, the exam aims to verify both the acquisition of the course contents and the ability to apply them to realistic mechatronic problems, while also assessing the students’ technical communication skills.

H. Janocha, Actuators: Basics and Applications
R. Krishnan, Eletric Motor Drives: Modeling, Analysis, and Control
A.H. Hansen, Fluid Power Systems: A Lecture Note in Modelling, Analysis and Control
K. Uchino, Advanced Piezoelectric Materials Science and Technology
W. Heywang, K. Lubitz, W. Wersing, Piezoelectricity: Evolution and Future of a Technology
Q.-H. Qin, Advanced Mechanics of Piezoelectricity
J. Yang, An Introduction to the Theory of Piezoelectricity
G. Engdahl, Handbook of Giant Magnetostrictive Materials
K. Otsuka, C.M. Wayman, Shape Memory Materials
D.C. Lagoudas, Shape Memory Alloys: Modeling and Engineering Applications
C. Lexcellent, Shape Memory Alloys Handbook
K. Asaka, H. Okuzaki, Soft Actuators: Materials, Modeling, Applications, and Future Perspectives
Y. Bar-Cohen, Electroactive Polymer (EAP) Actuators as Artificial Muscles
L. Dai, Intelligent Macromolecules for Smart Devices
M. Tabib-Azar, Microactuators: Electrical, Magnetic, Thermal, Optical, Mechanical, Chemical & Smart Structures

This advanced course explores modern developments in the field of smart structures, with a focus on piezoelectric systems, nonlinear dynamics, bio-inspired computing paradigms, morphing structures, and morphological computation (refer to the course topics for more details). Students will gain a deep understanding of the fundamental principles and advanced concepts in the context of electromechanical interactions, structural vibration control, soft robotics, and computational applications inspired by biological systems. The course addresses both theoretical modeling and practical physical interpretations of these phenomena, thereby equipping students with versatile skills for addressing complex engineering challenges.

By the end of the course, students will:
Be able to model and analyze the behavior of piezoelectric structural systems, with applications in vibration suppression, stability analysis, and energy harvesting (knowledge and understanding; applying knowledge and understanding).
Develop expertise in the design and control of advanced materials and structures, including metamaterials, reconfigurable systems, and soft robotics.
Independently conduct a project, including modeling, computational analysis, experimental design, synthesis, and presentation of results (applying knowledge and understanding; making judgements; communication skills).

The course will cover:
Piezoelectric structural vibrations: modeling and suppression techniques.
Electromechanical coupling in piezoelectric beams and structural systems.
Stability analysis and nonlinear dynamics, including buckling and multistability of nonlinear systems.
Morphing and reconfigurable structures for adaptive mechanical systems.
Fundamentals of metamaterials and metastructures for vibration control and wave manipulation.
Nonlinear metamaterials: modeling, design, and applications.
Morphological computing: concepts, and applications in structural systems.
Boolean logic versus bio-inspired computation.
Application of morphological computing to the design and control of soft robotics.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
There will be a course project, developed by the students during the course under the supervision of the course assistants. The project will focus on applying course concepts to a specific challenge, combining theoretical modeling and practical analysis.
The exam consists in the evaluation of the project and in particular of the following elements:
A written report detailing the project’s objectives, methodology, and results (applying knowledge and understanding; making judgements).
An oral presentation of the project, including a Q&A session with the instructors to assess understanding and communication skills.
The overall evaluation will depend on all these elements, paying attention to all the steps of the project development and presentation (modelling, analysis of the results, report quality, presentation, answers to the teachers' questions)

Additive Manufacturing (AM), commonly known as 3D Printing, is a pivotal technology driving the green and digital transitions. It revolutionizes the design and production of eco-friendly, high-performance, and durable products, with diverse applications across multiple industrial sectors such as aerospace, biomedical, machinery and tooling, energy, and creative industries.
This course provides a comprehensive overview of AM technologies for polymers, metals, and ceramics. It explores the design considerations, technical limitations, and strengths associated with each material type. Additionally, the course delves into new models for assessing the techno-economic and sustainability aspects of AM, in comparison to traditional manufacturing solutions.
The course targets both technical and business-oriented professionals, including designers, engineers, and potential users seeking to harness the transformative power of AM. By the end of the course, participants will have gained a deep understanding of the potential and limitations of AM, enabling them to make informed decisions and leverage this technology to drive innovation in their respective fields.

After succesfully completing the course, the student will be able to:
Redesign x AM, having a correct landscape of all the principal AM processes (pros and cons), carry out a cost-and-value analysis of substituting current technologies with AM ones (Knowledge and understanding skills)
Identify trends, technologies and key methodologies related with digital and advanced manufacturing in the Industry 4.0 framework (Applying Knowledge).
Develop new ideas and solutions in emerging industrial businesses. In fact, Additive manufacturing is one of the more active playground for new solutions, innovative ideas and start-ups. (Applying knowledge and making judgements)
Interact in a professional, responsible, effective and constructive way in a working environment. The project work will allow all the students to interact in a multi-disciplinary environment. In fact the project team will mix students in management, mechanical, design, automation and physics engineering (Team-working and communication abilities).

Course Outline
Module 1: Introduction to Additive Manufacturing
Definition and principles of additive manufacturing
Layer-by-layer principle. Benefits and limitation of AM. Generalized AM process chain.
Materials and industrial applications.
Overview of the green and digital transitions and the role of AM
Case studies showcasing the impact of AM in different industrial sectors
Module 2: Additive Manufacturing Technologies for Polymers
Overview of polymer-based AM processes
Material landscape: selection criteria, resulting properties, applications
From process parameters to process control
Design guidelines and open challenges in polymer-based AM
Techno-polymers and composites
Module 3: Additive Manufacturing Technologies for Metals
Exploration of AM processes for metal and ceramics
Principles, materials, properties and applications across processes
Process optimization: parameters, control and ptinting strategies
Design principles and constraints specific to metal- and ceramic-based AM
Module 4: From Design to Post-processing and Qualification
Thermal-treatments and finishing
AM product verification: 3D X-ray computed tomography; In-situ and In-line quality monitoring. Solutions and perspectives
AM product qualification:c Thermo-mechanical performances
Module 5: Techno-Economic and Sustainability Assessment of AM
Process selection: comparison of AM with traditional manufacturing in terms of cost, time, and resource efficiency
Evaluation of environmental impacts and sustainability benefits of AM
Case studies and tools for conducting techno-economic and sustainability assessments
Module 6: Future Trends and Applications
Market availability and trends, business opportunities.
Exploration of emerging trends and advancements in AM technologies
Convergence frontiers: bioprinting as a case study — printing with cells, bioinks and printability challenges, sectors and applications, opportunities and open problems
Novel applications and disruptive potentials of AM in various industries
Implications for designers, engineers, and other stakeholders in the AM ecosystem
Course organization
The course is organised into lectures, discussion of case studies, testimonials from industry, in-class exercises, and laboratory activities. Laboratory activities will be held at AddMe.Lab of the Mechanical Engineering Department and allow students to develop hands-on knowledge on specific AM problems.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente) o condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Grading will be based on a written and oral examination. During the exam, the students will be asked to show the acquired knowledge on AM processes, techniques and methods and and their skills to identify current AM trends, the existing technologies and key methodologies (Knowledge and understanding and Applying Knowledge and understanding abilities)
A team project will be carried out using the teaching lab of the AddMe lab of the Department of Mechanical Engineering. The project will check the acquired ability to develop new ideas and solutions and their capability of multidisciplinary team-working (Making Judgements, Learning skills and Communication abilities).

Ian Gibson, David Rosen, Brent Stucker, Additive Manufacturing Technologies, Editore: Springer, New York, NY, ISBN: 978-1-4939-2112-6 available as ebook on biblio.polimi.it

The course will offer a unique opportunity to acquire a deep understanding of all currently state of the art Additive Manufacturing technologies used on high-end industrial sectors. Each manufacturing process used on metals (conventional and non-conventional), polymers, composite materials, ceramics and glasses, living cells/human organs will be described in detail. Every process will be analysed in terms of main applications for which the process offers the ideal performances as well as all associated benefits, advantages and drawbacks.
The course will subsequently address all currently open technical challenges. In fact, Additive Manufacturing is showing great potential on a very large number of space and aerospace applications, however open challenges have been identified. These include design aspects and associated design rules for AM. Manufacturing challenges start with the raw material procurement and control (powder-screening methods, procurement specification and verification requirements). On the manufacturing process itself, process stability and its monitoring/controlling, the understanding of changes of process and parameters impact on final product play the major role. Moreover, space qualification and validation routes will be addressed. Lastly, standardisation will be presented in order to facilitate the market uptake of 3D printing and promote its innovation potential to industrial competitiveness.
Once the student will be fully aware of all currently available technologies their benefits and drawback as well as the main open challenges, real life case studies (mainly from the space and aerospace domain) will be presented. The objective of this part of the course is to provide the student with a current industrial implementation approach of Additive Manufacturing on high quality products. Real spacecraft, satellites, rockets or aircraft parts end-to-end design/manufacturing process will be shown. Starting with the design/topology optimisation (bionic design), moving to the selection of the ideal Additive Manufacturing technology up to the optimisation of the process parameters, the mechanical characterisation (static, fatigue, microstructure, NDI, computer tomography, eddy current, etc.) and the production of a breadboard to be full scale tested and then flown in orbit. Moreover, the course will also provide case studies and examples of failure investigations on real components.
Lastly, the course will provide an outlook on the future developments related to Additive Manufacturing, including the 4D printing as well as the industry 4.0 developments.

After succesfully completing the course, the student will be able to:
Identify trends, technologies and key methodologies related with digital and additive manufacturing for high-value-added products ( Applying Knowledge).
Develop new ideas and solutions in emerging industrial businesses. In fact, Additive manufacturing is one of the more active playground for new solutions, innovative ideas and start-ups. ( Applying knowledge and making judgements)
Interact in a professional, responsible, effective and constructive way in a working environment. The project work will allow all the students to interact in a multi-disciplinary environment. In fact the project team will mix students in management, mechanical, design, automation and physics engineering ( Team-working and communication abilities ).

Additive Manufacturing (AM or 3D Printing) is changing the industrial landscape worldwide, particularly in high-end technology sectors, including space, aerospace, racing and medical applications. The course will provide the student with a very deep understanding of the different Additive Manufacturing technologies and their industrial applications with focus on space and aerospace. A wide range of materials will be presented ranging from conventional and non-conventional metals, polymers, ceramics and geopolymers (e. g. moon regolith) and even covering living cells and human organs. All the currently open technical challenges will be presented. Moreover, the course will be complemented with “real-life” case studies from the aerospace sector. The case studies will cover real design developments from concept phase to in-orbit space flight as well as failure investigations on real components and units.
Detailed Program:
Detailed overview of all AM Technologies used on:
o Metals
o Polymers
o Composite Materials
o Ceramics and Glasses
o Living Cells/Human Organs
Description of all benefits per domain of application of the above mentioned technologies
Detailed overview of the open technical challenges, including:
o Dimensional Challenges
o Design Challenges
o Manufacturing Challenges (starting from materials supply chain up to manufacturing stability, pre-/in-/post-processing, etc.)
o Qualification/Verification challenges (mechanical characterisation, Non-Destructive Investigation, in-situ monitoring, etc.)
o Standardisation challenges
Case studies (2 to 3) providing deep understanding of the end-to-end design/manufacturing process:
o Design/topology optimisation
o AM technology selection and parameters optimisation
o Mechanical characterisation (static, fatigue, microstructure, NDI, computer tomography, eddy current, etc.)
o Manufacturing of the breadboard
o Full scale testing
o In-flight verification
What happens when it goes wrong?:
o Failure investigation case studies (2 to 3)
o Usual “illnesses” of Additive Manufacturing
What’s next:
o The future developments in Additive Manufacturing
Course timetable - please check WeBeep for the detailed schedule
*Please check the news on webeep for latest news on rooms and locations.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Grading will be based on a written examination, which include open questions. During the exam, the students will be asked to show the acquired knowledge on AM processes, techniques and methods and and their skills to identify current AM trends, the existing technologies and key methodologies ( Knowledge and understanding and Applying Knowledge and understanding abilities)
A team project will be carried out using the teaching lab of the AddMe lab of the Department of Mechanical Engineering. The project will check the acquired ability to develop new ideas and solutions and their capability of multidisciplinary team-working ( Making Judgements, Learning skills and Communication abilities ).

Il corso, a partire dalla descrizione di alcuni sistemi di trasmissione significativi e dei relativi componenti, mette in evi-denza l'importanza della corretta scelta e applicazione degli elementi di macchine.
In una prima fase del corso vengono pertanto presentati, o approfonditi nel caso di elementi già introdotti in insegna-menti precedenti, gli elementi di macchine fondamentali quali i collegamenti filettati, con perni e spine, molle, cuscinetti a rotolamento e lisci, assi, alberi e calettamenti. Di questi verranno descritti in modo sistematico la morfologia, le di-verse soluzioni costruttive, il progetto, l'applicazione, le tolleranze e il calcolo di verifica rispetto ai principali cedimenti.
Successivamente saranno presentati gli ingranaggi cilindrici, con i necessari richiami di geometria e cinematica, e i principali cedimenti quali la fatica al piede, il pitting, il micropitting, lo scuffing e l'usura.
Infine saranno considerati alcuni sistemi di trasmissione, sia ordinari che epicicloidali, mediante i quali gli allievi si confronteranno con lo studio dei flussi di potenza, degli equilibri di forze e momenti, delle perdite e dell'efficienza.
Esercitazioni e laboratori di progetto saranno l'occasione per applicare i principi teorici a casi pratici.
Completano il corso una visita tecnica presso il centro di ricerca FZG della Technische Universität München e presso un'azienda da definire.

Il corso affronta i fondamentali della teoria della stima, l'elaborazione statistica dei segnali e l'analisi di serie temporali di dati usando un approccio application-driven con esempi pratici da diversi campi dell'ingegneria come sistemi GPS e di navigazione, comunicazioni audio/video e digitali, analisi vibrazionale, e tele-rilevamento. L'obiettivo è quello di acquisire conoscenza sui seguenti-argomenti chiave: l'algebra per l'elaborazione del segnale e teoria della stima, fondamenti della teoria della stima (BLU, MLE, CRB, MMSE, MAP), parameter tracking e filtraggio Kalman, filtraggio adattativo LMS/RLS, analisi spettrale (AR/MA/ ARMA) e metodi ad alta risoluzione per elaborazione di array, detection theory, pattern e feature detection/classification, e metodi di classificazione supervisionati / non supervisionati. Gli esercizi sono su aspetti teorici e casi pratici con l'uso del software Matlab e la simulazione di Montecarlo. Durante il semestre ci sono 3 esercizi interattivi su casi pratici di studenti organizzati in gruppi di lavoro.

Il corso affronta i fondamentali della teoria della stima, l'elaborazione statistica dei segnali e l'analisi di serie temporali di dati usando un approccio application-driven con esempi pratici da diversi campi dell'ingegneria come sistemi GPS e di navigazione, comunicazioni audio/video e digitali, analisi vibrazionale, e tele-rilevamento. L'obiettivo è quello di acquisire conoscenza sui seguenti-argomenti chiave: l'algebra per l'elaborazione del segnale e teoria della stima, fondamenti della teoria della stima (BLU, MLE, CRB, MMSE, MAP), parameter tracking e filtraggio Kalman, filtraggio adattativo LMS/RLS, analisi spettrale (AR/MA/ ARMA) e metodi ad alta risoluzione per elaborazione di array, detection theory, pattern e feature detection/classification, e metodi di classificazione supervisionati / non supervisionati. Gli esercizi sono su aspetti teorici e casi pratici con l'uso del software Matlab e la simulazione di Montecarlo. Durante il semestre ci sono 3 esercizi interattivi su casi pratici di studenti organizzati in gruppi di lavoro.

This advanced course is designed to train students with theoretical and practical knowledge of Human Machine Interfaces (HMIs) and their application in various fields, including industrial, product design, automotive, and more. By delving into the fundamentals of human perception, cognition, and behaviour, students will gain a profound understanding of how these aspects influence the usability of an HMI. The course will also explore advanced visualisation, monitoring, and interaction technologies and techniques, enabling students to see their direct applications in creating effective HMIs. Moreover, the course will cover usability, user experience (UX) basics, and methodologies for acquiring quantitative and qualitative data for evaluation and validation. By the end of this course, students will not only possess the skills to identify critical elements, develop prototypes, and conduct thorough assessments using appropriate UX research methodologies but also be able to apply this knowledge in real-world scenarios.

By the end of the course, the students will be able to:
Knowledge and understanding
understand the basic knowledge of Human Machine Interfaces (HMIs) in different application fields
understand the basic knowledge of human perception and cognition
know the advanced technologies and techniques for HMI in terms of visualisation, monitoring, and interaction
understand the fundamental aspects of HMI design and development
know the tools to design and prototype an HMI
understand the basic knowledge of Usability and User Experience
know the methods to acquire quantitative and qualitative data for HMI evaluation
Apply the acquired knowledge and understanding
apply the acquired knowledge to design an HMI for a specific application field
implement an HMI prototype for testing activities
apply the proper methods to evaluate the HMI in terms of Usability and User Experience
Further developed skills
develop analytical and research skills to frame the application field for the project
develop the ability to make decisions and solve problems
develop programming skills
develop collaboration abilities through practical group activities
develop communication skills through the final presentation and demonstration

Introduction to Human-Machine Interfaces: overview, significance in different domains, historical perspective and evolution
Human Factors in HMI Design: human perception, cognition, behaviour, usability, anthropometrics, and ergonomics
Advanced Visualization Technologies: Graphical user interfaces (GUIs), Augmented Reality (AR), Virtual Reality (VR), data visualisation, and information design
Interaction techniques: touchscreen interfaces, gesture-based interfaces, voice and natural language interfaces, and haptic feedback
Usability and User Experience (UX): basics; evaluation and measurements through user testing
Evaluation and validation: quantitative and qualitative research methods, usability testing and user feedback, analysis, and interpretation of the evaluation results
Prototyping and development: tools and software, prototyping techniques and rapid iteration, case studies and practical exercises
Real-world applications: case studies from various application fields, guest lectures from industry experts, group projects and hands-on applications

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course includes lectures, practice laboratory activities, and a collaborative project based on a case study from partner companies or research activities in PoliMI laboratories. Evaluation will be based on an individual final examination to assess overall knowledge and the assessment of the group project involving HMI prototype development and testing. Project outcomes must be reported in a document and presented through a practical demo.

Helen Sharp, Jennifer Preece, Yvonne Rogers, Interaction design: beyond human-computer interaction, Editore: John Wiley & Sons, Anno edizione: 2019, ISBN: 978-1-119-54725-9
Jakob Nielsen, Usability Engineering, Editore: Morgan Kaufmann, Anno edizione: 1994, ISBN: 978-0-12-518406-9
Donald A. Norman, The Design of Everyday Things: Revised and Expanded Edition, Editore: Hachette UK, Anno edizione: 2013, ISBN: 978-0-465-07299-6
Steve Krug, Don't Make Me Think, Revisited: A Common Sense Approach to Web Usability, Editore: New Riders, Anno edizione: 2013, ISBN: 978-0-13-359726-4
Dan Saffer, Designing for Interaction: Creating Innovative Applications and Devices, Editore: New Riders, Anno edizione: 2010, ISBN: 978-0-321-64339-1
Bill Moggridge, Designing Interactions, Editore: MIT Press, Anno edizione: 2007, ISBN: 978-0-262-13474-3

MATERIALI per la propulsione e l'energia
Il corso si concentra sulle correlazioni tra le prestazioni del servizio e la chimica dei materiali, la microstruttura e l'elaborazione dei materiali per le classi di materiali che, nel corso degli anni, sono diventati standard per applicazioni nel campo della propulsione e dell'energia. Per questi materiali, lo sviluppo continuo nella scienza dei materiali offre alternative o miglioramenti per prolungare la vita utile o ampliare le condizioni di servizio. Il corso offre anche una panoramica dei materiali utilizzati per i sistemi ausiliari. Il corso sarà organizzato in una serie di casi di studio in cui le lezioni saranno combinate con seminari, sessioni di laboratorio o analisi attiva di dati disponibili dalla letteratura tecnica o scientifica o ricerche su soluzioni innovative basate sui materiali.

The goal of the course is to provide students with the ability to design and implement a conventional process flow for the fabrication of simple electronic and spintronic devices. The course covers the fabrication of films and heterostructures using different deposition techniques, as well as device fabrication by conventional and advanced lithography, with reference to examples of scientific or industrial relevance. The lectures are supported by an experimental activity session carried out at the Polifab laboratory of Politecnico di Milano.

DdD1 - Knowledge and understanding
Upon passing the exam, the student will have a basic knowledge of surface thermodynamics and the epitaxy of films and heterostructures. The student will know the physical and technological principles of physical vapor deposition (PVD), chemical vapor deposition (CVD), lithographic and etching techniques, as well as the principles of vacuum technologies. The student will understand the differences among the main deposition, lithography, and etching techniques.
DdD2 - Applying knowledge and understanding
Upon passing the exam, the student will be able to predict the chemical and morphological properties and growth dynamics of a film or heterostructure. They will be able to design a simple vacuum system and a simple lithographic process flow. They will be able to select the most appropriate deposition, lithography, and etching techniques depending on the application.
DdD3 - Making judgements
Upon passing the exam, the student will be able to design and implement the process flow for fabricating simple electronic or spintronic devices.

Part I - Deposition
Introduction: objectives, examples.
Vacuum technology: pressure, gas transport, vacuum systems.
Surface thermodynamics: surface properties, nucleation, and film growth modes.
Film epitaxy: mechanisms and the effect of strain.
Thermal evaporation: vapour pressure, deposition rate, and uniformity; electrical and e-beam evaporation, molecular beam epitaxy, pulsed laser deposition.
Sputtering deposition: plasma physics and basic processes, including DC, RF, reactive and magnetron sputtering.
Chemical Vapor Deposition: physical and technological aspects, with examples of processes
Part II - Lithography
Introduction to lithography: device scaling and Moore’s law.
Optical lithography: process flow and technology.
Physics of optical exposure and resolution enhancement technologies: diffraction, numerical aperture, illuminations, masks, lenses, and resists.
Advanced photolithographic techniques: maskless optical lithography, extreme ultraviolet lithography, and X-ray lithography.
Electron beam lithography: physical principles, process flow, and technology.
Other advanced lithographic techniques: soft and nanoimprint lithography, focused ion beam and scanning probe lithography.
Pattern transfer: dry and wet etching
Examples of lithographic process flows.
Laboratory activities
An experimental activity will be carried out at Polifab, the micro- and nanotechnology centre of Politecnico di Milano. This activity will introduce the student to the design and implementation of a conventional process flow for the fabrication of a simple spintronic device, such as a Hall bar or a GMR sensor, involving some of the deposition and patterning techniques discussed in the course.
Schedule
The course will be held in the second half of the first semester, from November to December.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The final examination will consist of a written test, in English, with exercises and open-ended questions. To pass the exam, students are required to demonstrate knowledge and a deep understanding of the physical and technological topics covered in the course, as well as the ability to think critically and connect the various topics of the course. The final assessment allows the student to demonstrate their ability to:

• design a simple vacuum system
• understand and predict the growth dynamics and the structural/morphological properties of simple films and heterostructures;
• design and discuss a conventional process flow for the fabrication of simple electronic and spin-electronic devices, from heterostructure/film deposition to patterning of the final device
• understand, select, and determine the most common parameters used in standard photolithographic processes;
• understand, select, and determine the most appropriate deposition, lithographic, and etching techniques for device fabrication.

Milton Ohring, Materials Science of Thin Films 2nd Edition, Editore: Academic Press, Anno edizione: 2002, ISBN: 978-0125249751
Note: (Part I of the course)
Marc J. Madou, Fundamentals of Microfabrication and Nanotechnology - vol. 2, Editore: CRC Press, Anno edizione: 2011, ISBN: 978-0849331800
Note: (Part II of the course)

This course aims to provide a sound understanding of the fundamental scientific and engineering principles involved in motorsport.
The course will cover design, construction and operation of racing vehicles.
Fundamental information on vehicles focusing on limit vehicle behaviors with explanations and derivations from first principles, using simplified and complex physical models will be provided.
Experience on computer based simulation software will be provided to create an understanding of how to apply simulation techniques to the context of motorsport.

Dd 1 - knowledge and understanding
On successful completion of this course the student

• evaluate the performance limits of a competition vehicle and the sources of such limitations
• distinguish the complex relationships between competition vehicle design aspects and competition vehicle performance
• perform simulation and optimisation for improving design and performance
• through lab activities, applies the models developed within the course and analyse experimental data
  Dd 2 - ability to apply knowledge and understanding
  On successful completion of this course the student
• is able to develop a simplified model to simulate a competition vehicle behavior
• is able to use commercial simulation codes to simulate the race car behavior
• is able to process experimental telemetry data for evaluating the vehicle performance
• is able to organize and communicate the results of tests and simulations activities.
  Dd 3,4,5 - Making judments, Communications, Learning skills
  On successful completion of this course the student
• can model a competition vehicle and related subsystems
• is able to judge the vehicle performance
• is able to communicate the results of the modeling and the analysis in a technical report
• gains the capability to work in team for a specific project.
  The course aims to encourage the acquisition of skills in information gathering, information processing, analysis and communication and these skills will be evaluated and assessed by by written group assignment.

History of motorsport.
Competitions technical regulations.
Aerodynamic performance.
Racing vehicles subsystems (tyres, braking system, suspension system, powertrain,.....).
Materials and components design.
Racing vehicle performance assessment (simulation tools and model building).
Data analysis and processing.
Racing vehicles setup optimisation for maximum performance (minimum time optimisation).
Driving simulator technology applied to races.
Driverless racing vehicles.
Environmental and sustainability considerations where motorsport is concerned.

Prova scritta condizionata (a scelta del docente), senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully take an oral exam on theoretical questions including the discussion of the submitted report describing the solution of the case studies.
Oral Exam

• theoretical questions on the course topics
• simple design problems
  Report Discussion
• report presentation
• discussion on the methods
• discussion of the results
  Final Grading
  To pass the course, students must successfully pass the oral test and complete the report which describes the case studies results.
  The final mark is the non-weighted mean of the marks obtained answering the questions and discussing the report.

https://webeep.polimi.it/ Course Notes
Editors Gianpiero Mastinu, Manfred Ploechl, Road and Off-Road Vehicle System Dynamics Handbook, Editore: CRC Press, Anno edizione: 2014, ISBN: 9780429129810
Note: Chapters 14 & 15
Jorge Segers, Analysis Techniques for Racecar Data Acquisition, Editore: SAE International, Anno edizione: 2014, ISBN: 978-0-7680-6459-9
William F. Milliken, Douglas L. Milliken,, Race Car Vehicle Dynamics, Editore: SAE Internationa, Anno edizione: 1994, ISBN: 978-1-56091-526-3
James Balkwill, Performance Vehicle Dynamics Engineering and Applications, Editore: Elsevier, Anno edizione: 2017, ISBN: 9780128126936
Trzesniowski, Michael, Suspension System, Editore: Springer, Anno edizione: 2023, ISBN: 9783658398477
Note: E-book available
Lars Frömmig, Basic Course in Race Car Technology, Editore: Springer, Anno edizione: 2023
Note: DOI:10.1007/978-3-658-38470-8 Note:
E-book available

Il corso si propone di fornire allo studente la conoscenza di programmazione avanzata in C++ per il calcolo scientifico. Si considereranno: tecniche di programmazione ad oggetti e generica, metaprogrammazione ed expression template, la Standard Library, tecniche di design (design pattern). Si prendono a riferimento tipiche applicazioni al calcolo scientifico. Il corso fornisce inoltre elementi di calcolo parallelo basato su MPI e OpenMP, tecniche di profiling e debugging, librerie statiche e dinamiche. Si illustreranno anche le principali librerie open source per il calcolo scientifico. Durante la lezione si stimolerà la partecipazione degli studenti e si erogheranno dei test "on-the-fly" per verificare il livello di comprensione. Il materiale delle lezioni viene fornito in anticipo.

Il corso si propone di fornire allo studente la conoscenza di programmazione avanzata in C++ per il calcolo scientifico. Si considereranno: tecniche di programmazione ad oggetti e generica, metaprogrammazione ed expression template, la Standard Library, tecniche di design (design pattern). Si prendono a riferimento tipiche applicazioni al calcolo scientifico. Il corso fornisce inoltre elementi di calcolo parallelo basato su MPI e OpenMP, tecniche di profiling e debugging, librerie statiche e dinamiche. Si illustreranno anche le principali librerie open source per il calcolo scientifico. Durante la lezione si stimolerà la partecipazione degli studenti e si erogheranno dei test "on-the-fly" per verificare il livello di comprensione. Il materiale delle lezioni viene fornito in anticipo.

The course aims to give an insight into advanced aspects of tyre modelling and testing for automotive applications. The mechanism of tyre-road contact force transmission is deepened, together with aspects of increasing interest in the automotive field, such as rolling resistance, wear and NVH (Noise Vibration Harshness). Advanced empirical and physical models are introduced (MF-Swift, Megaride, etc.), including experimental tests and data processing needed for a proper fitting of their parameters. Finally, an overview of smart tyre technologies and their application to vehicle active control is provided.

Dd 1; knowledge and understanding
After passing the exam the student:
knows the main physical (e.g. brush model, Megaride) and empirical models (e.g. MF-Tyre, MF-Swift) for reproducing tyre-road contact forces, including the effect of temperature, pressure, etc.
knows the function of the main elements of a tyre: compound, tread pattern, etc.
knows the basic concepted about rolling resistance, wear and NVH (Noise Vibration Harshness)
understand how tyre behavior affects vehicle dynamics and performance of control systems
understand how to characterize tyre models through experimental indoor and outdoor tests
knows the basis of smart tyres
through lab activities, applies the models introduced within the course and fits the model parameters based on experimental tests
Dd 2; ability to apply knowledge and understanding
After passing the exam the student
is able to write a Matlab® or Simulink® code to simulate the coupled tyre and vehicle dynamic behavior
is able to use some commercial multibody codes (e.g. Megatide®) to simulate the behavior of the tyre
is able to process experimental data for evaluating a tyre performance and fitting model parameters (with reference to previous points)
is able to organize and communicate the results of laboratory tests and simulations activities.
Dd 3,4,5 (Making judments, Communications, Learning skills)
After passing the exam the student:
can model tyre-road contact forces
is able to process experimental data for analyzing a tyre behavior and fitting the tyre models introduced within the course
is able to communicate the results of the modeling and the analysis in a technical report
gains the capability to work in team for a project.

Tyre advanced models
Description of the main physical (e.g. brush model, Megaride) and empirical models (e.g. MF-Tyre, MF-Swift) reproducing tyre-road contact forces, including the effect of compound, temperature, pressure, wear, etc.
Tyre testing: indoor & outdoor methods, measuring devices
Methods for evaluating tyre performance through indoor and outdoor tests. Pros and cons of indoor and outdoor methodologies.
Identification of tyre model parameters
Identification methodologies for fitting experimental data.
Wear, NVH, comfort, rolling resistance
Basic concepts about tyre wear, rolling resistance and NVH (Noise Vibration Harshness): mechanism, main affecting parameters.
Smart tyre technologies
Introduction about the methods (accelerometers, strain gauges, optical sensors) used to turn the tyre into a sensor for gaining additional information about the tyre-road contact. Pros and cons, applications.
Impact of tyre behavior on vehicle dynamics and performance of active control systems
Evaluation of tyre behaviour and main characteristics on vehicle dynamics and most common active control systems, such ABS (Antilock Braking System).

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Altro
Students will pass the course after successfully take an oral exam on theoretical questions which includes the discussion of the submitted report describing the solution of the case studies.
Oral Exam (D 2,3,4,5)
theoretical questions on the course topics
simple modelling problems
Report Discussion (D 1,2,3,4,5)
report presentation
discussion of the results
Final Grading
To pass the course, students must successfully pass the oral test and complete the report which describes the case studies. results.
The final mark is the non-weighted mean of the marks obtained answering the open-ended questions and discussing the report.

Hans B. Pacejka, Tire and Vehicle Dynamics, Anno edizione: 2012
J.Y.Wong, Theory of Ground Vehicle, Editore: Wiley & Sons

Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment:
Master and understand design practices and making capabilities in accelerating innovation projects [Individual Written Exam].
Develop new ideas and solutions in business and industrial scenarios evolving over time:
Early prototype innovative concepts [Team Design Sprint Project].
Manage uncertainty of innovation projects adopting agile approaches [Team Design Sprint Project].

Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment:
Manage design practices and making capabilities in accelerating innovation projects [Individual Written Exam];
Develop new ideas and solutions in business and industrial scenarios evolving over time;
Early prototype innovative concepts [Team Design Sprint Project];
Manage uncertainty of innovation projects adopting agile approaches [Team Design Sprint Project];
Develop solutions that transform the current ecosystem by leveraging the collaboration and cooperation of stakeholders [Team Design Sprint Project].
Through these activities, students will learn:
Knowledge and understanding: By the end of the course, students will be able to demonstrate a clear understanding of the key concepts and methods related to agile innovation;
Applying knowledge and understanding: Students will apply their acquired knowledge and comprehension to analyse real-world cases and propose innovative agile solutions;
Communication skills: Students will effectively communicate their ideas, solutions and analyses both verbally and in writing, tailoring their message to different stakeholders.

Today’s world, where speed is gaining increasing relevance to make innovation happen, has called for the emergence of approaches that leverage continuous testing and iteration. After the introduction of the Agile Manifesto in 2001, a wide range of industries has experienced the massive diffusion of Agile approaches. These approaches leverage agility, flexibility, and the rapid development of new solutions. On the one hand, Agile emerges as a tool to change the development process; on the other, it emerges as a culture to embrace flexibility. Especially this cultural aspect is crucial in agile innovation approaches, to face emerging issues and have an impact on companies solutions. Design is recognized as a powerful approach to reduce uncertainty; more specifically several studies show that adopting a design mindset can help embracing ambiguity and foster innovation even when the problems are wicked and ill-defined. In discovering new technologies, knowledge and uncertainty are always high, and the search for the right application might require different and complex iteration and experimentation processes. Design Sprint represents a new approach deeply rooted on agile culture, design attitude and experimentation mindset. It aims at accelerating innovation by the adoption of sketching, testing and prototyping tools.
The course has been designed around the following main topics:
Agile Culture: Making innovation happen in a continuously changing environment where ambiguity, variability and complexity is raising requires new mindset and approaches. Thus, agile innovation is gaining traction as a culture to cope with these shortcomings, in promoting both a agile culture and tools to make innovation happen. Furthermore, lean development and lean startup are approaches that are getting more and more relevance in today’s panorama not only in hi-tech industries. Agile methodologies and specific approaches such as SCRUM are fundamental to properly manage innovation projects in turbulent environments;
Design Attitude: The emergence of new paradigms such as human-centered design, participatory design and design thinking, have marked the transforming role of design in the field of innovation management. Design is not only an aesthetic driver of innovation but represents a new set of innovation management practices. It is something practiced not only by designers but by everyone in organizations who seeks to innovate;
Experimentation Mindset: Innovation approaches, such as agile development, and lean startup, may differ on some principles and practices, but they have one key ingredient in common: experimentation. Recent approaches leverage experiments for exploratory learning. In particular, “quick & dirty” prototypes are used to search the most valuable innovation opportunities. The changing nature of experimentation in innovation is supported by the digitalization trend. The increasingly digital nature of products and services facilitates early, less expensive, higher-fidelity prototypes and the subsequent tests.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation modality is divided into two main activities: an individual written exam and a team project called Team Design Sprint Projects that students conduct in the semester with factories (activities led by external companies) and team-based reviews with the faculty. More details will follow below.
The final evaluation of the course is different for attending and not-attending students.
Attending Students
The evaluation is based on the following elements:
The evaluation is based on the following elements:
Individual Written Exam: open questions about case studies and theoretical contents; the written exam is based on the content included in the course slides, case studies, and class discussion.
Team Design Sprint Projects: teams are engaged in designing new solution for a specific brief presented in the first day of lecture. Presentations and video are due one day before the final presentation day, happaning on the last day of lecture.
Design Connoisseurship: each team presents in 10 minutes a case of a company or a product that leveraged a design mindset to evolve over time. It is a way to nurture team critical reflection.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Written Exam
Team
Design Sprint Project
Design Connoisseurship
Attending Students
9
18
5
In order to pass the exam:
Sum must be >= 18;
Individual Written Exam >= 5;
Team Design Sprint Project >=10
Design Connoisseurship 0-5
The Team Design Sprint Project is valid for the entire academic year, so for all the calls the students that attend the course will keep that mark for all the five exam calls.
Not-Attending Students
The evaluation is based on the following elements:
Individual Oral exam: open questions about case studies and theoretical contents; the individual oral exam is based on the content included in the course slides, case studies, textbooks, guest speakers’ presentations;
Individual Design Sprint Project: same brief as the attending studnets. Presentation are to be sent on the day of the exam and presented during the oral exam.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Oral Exam
Individual
Design Sprint Project
Not Attending Students
18
14
In order to pass the exam:
Sum must be >= 18;
Individual Oral Exam >= 11;
Individual Design Sprint Project >= 7.

Magistretti, S., Sanasi, S., Dell'Era, C., & Ghezzi, A., Entrepreneurship as design: A design process for the emergence and development of entrepreneurial opportunities, Anno edizione: 2023
Knapp J, Zeratsky J, and Kowitz B, Sprint: How to solve big problems and test new ideas in just five days, Editore: Simon and Schuster, Anno edizione: 2016
Thomke SH, Experimentation Works: The Surprising Power of Business Experiments, Editore: Harvard Business Press: Boston, Anno edizione: 2020
Cooper RG and Sommer AF, The Agile-StageGate Hybrid Model: A Promising New Approach and a New Research Opportunity, Editore: Journal of Product Innovation Management, Anno edizione: 2016
Magistretti S, Dell'Era C, and Verganti R, Look for New Opportunities in Existing Technologies: Leveraging Temporal and Spatial Dimensions to Power Discovery, Editore: Research-Technology Management, Anno edizione: 2020
Magistretti S, Dell'Era C and Doppio N, Design sprint for SMEs: an organizational taxonomy based on configuration theory, Editore: Management Decisions, Anno edizione: 2020
Magistretti S, Allo L, Verganti R, Dell'Era C, and Reutter F, The microfoundations of design sprint: how Johnson & Johnson cultivates innovation in a highly regulated market, Editore: Journal of Knowledge Management, Anno edizione: 2021
Magistretti S, Pham C, and Dell'Era C, Enlightening the dynamic capabilities of design thinking in fostering digital transformation, Editore: Industrial Marketing Management, Anno edizione: 2021
Pham C, Magistretti S, and Dell'Era C, The Role Of Design Thinking In Big Data Innovations, Editore: Innovation: Organization & Management, Anno edizione: 2021

This course is of 6 CFU and is associated with a version of 5 CFU named 097688 - ECONOMICS AND COMPUTATION (5 CFU). The current form specifies goals, program and expected learning results for both courses.
For both versions of the course (6 CFU and 5 CFU), the goal of the course is to provide the groundings of algorithmic microeconomics. More precisely, the course explores mathematical models, computational complexity, and algorithms for economic settings. The course focuses both on non-cooperative game theory, describing the models and the algorithms used in real-world applications in various settings (e.g., poker and security), and on mechanism design, describing economic mechanisms and algorithms used in auctioning settings (e.g., digital advertising and online auctions). The treatment of the topics will be both from a theoretical point of view, describing the models/algorithms and their properties, and from a practical point of view, discussing how the algorithms can be applied and applying them in practice during some laboratory sessions. Furthermore, the course aims at presenting some real-world applications of paramount importance. The difference between the two versions of the course (6 CFU and 5 CFU) is just in the depth with which some topics are discussed.

For both versions of the course (6 CFU and 5 CFU), we expect that the students learn:
how to model real-world applications by means of mathematical models from microeconomics,
how to identify the most suitable class of algorithms to solve a given problem,
how to use the tools already available to solve a given problem in practice,
how to design an algorithm to solve a given problem whenever no algorithm is known

We report the topics discussed in both versions of the course (6 CFU and 5 CFU). We use '(*)' for the topics that will not be discussed in the 5 CFU version.
PRELIMINARIES OF GAME THEORY
Definition of non-cooperative game
Representations of a game
ALGORITHMIC GAME THEORY
Solving maxmin/minmax problems
Computational complexity of finding a Nash equilibrium
Algorithms for finding a Nash equilibrium
Arrow-Debreu market model and equilibrium (*)
Algorithms for finding a Stackelberg equilibrium
Real-world application: security games
Congestion games
Price of Anarchy and Price of Stability
ECONOMIC MECHANISM DESIGN
Social choice function
Definition of economic mechanism
Gibbard-Satterthwaite theorem
Quasi-linear environment and linear environment
Implementation of a social choice function
Groves mechanisms
Green-Laffont characterization and Myerson characterization
Economic mechanisms for online advertising (real-world applications) (*)
ALGORITHMIC MECHANISM DESIGN
Non-scalability of Groves mechanisms (real-world examples: combinatorial auctions)
Developing computationally efficient mechanisms
Economic mechanisms for combinatorial auctions (real-world applications)
Economic mechanisms for double auctions (*)
Economic mechanisms for knapsack auctions
Automated mechanism design (*)

Prova scritta obbligatoria, con prove in itinere
Valutazione continua facoltativa (a scelta dello studente)
The exam is the same for both versions of the course (6 CFU and 5 CFU), except for the questions that, in the case of the 5 CFU version, may be different. More precisely, the exam can be of two forms:
standard: written exam (2.5 hours)
3 exercises (the first exercise is on noncooperative game theory models and on the adoption of operations research tools to solve a game, the second exercise is on algorithmic game theory or economic mechanism design, the third exercise is on economic mechanism design or algorithmic mechanism design) (max 27 points), --- here the students are required to solve exercises similar to those studied during the course or to answer some theoretical questions about topics discussed during the course; the capabilities the students must show are: modeling real-world applications by means of mathematical models from microeconomics, indentifying the most suitable class of algorithms to solve a given problem, using the tools already available to solve a given problem in practice ---;
1 question on advanced topics (on all the topics of the course) (max 5 points) --- here the students are required to answer a question that is beyond the topics discussed during the course; the capabilities the students must show are: generalizing the skills learned during the course to design an algorithm for a given problem that has not discussed during the course;
engaged: the course is divided into four parts (Part 1: noncooperative game theory models; Part 2: Maxmin and Nash equilibrium; Part 3: Stackelberg, Congestion games, social choice functions; Part 4: mechanism design and algorithm mechanism design), at the fourth week of each part of the course, students take part in a midterm exam (2.5 hours), composed as:
exercise/theory (1 exercise and 2 theory questions) (max 27 points) --- here the students are required to solve exercises similar to those studied during the course or to answer some theoretical questions about topics discussed during the course; the capabilities the students must show are: modeling real-world applications by means of mathematical models from microeconomics, identifying the most suitable class of algorithms to solve a given problem, using the tools already available to solve a given problem in practice ---;
challenge on scientific research problems (max 8 points); the challenge is carried on by teams, each of 2-3 students --- here the students are required to answer some questions that are beyond the topics discussed during the course; the capabilities the students must show are: generalizing the skills learned during the course to design an algorithm for a given problem that has not discussed during the course.
Each student can choose the form of the exam she/he prefers. If a student opts for the engaged form and she/he is not satisfied with the achieved grade, she/he can repeat the exam in the standard form.

Noam Nisan, Tim Roughgarden, Eva Tardos, V. Vazirani, Algorithmic Game Theory, Editore: Cambridge University Press
Kevin Leyton-Brown, Yoav Shoham, Essentials of Game Theory, Editore: Cambridge University Press

Il corso ha l'obiettivo di fornire approcci metodologici, tecniche e strumenti per la gestione dei progetti i contesti ad elevata incertezza e rapida evoluzione che richiedono notevole flessibilità sia a livello organizzativo sia a livello di singolo interprete (change driven approach). Al fine di una piena comprensione degli strumenti e dei contesti applicativi si consigliano pregresse competenze di base di gestione di progetti (plan driven approach). Grazie ad un progetto svolto a gruppi durate le attività di didattica frontale si approfondiranno i seguenti argomenti: agile project management, lean roject anagement, extreme planning, scrum planning, project review e project retrospective.

Nowadays, deep neural networks can outperform traditional hand-crafted algorithms, achieving human-level performance on many complex tasks, such as natural language processing, text modeling, gene expression modeling, and image recognition. The course provides a broad introduction to neural networks (NNs), ranging from traditional feedforward (FFNNs) and recurrent (RNNs) to the most successful deep learning models, such as convolutional neural networks (CNNs) and long short-term memory (LSTM).
The course's primary goal is to provide students with the theoretical background and practical skills to understand and use NN, and to become familiar with Deep Learning for solving complex engineering problems.
This goal is pursued in the course by
Presenting major theoretical results underpinning NN (e.g., universal approximation, vanishing/exploding gradient, etc.)
Describing the most important algorithms for NN training (e.g., backpropagation, adaptive gradient algorithms, etc.)
Illustrating the best practices on how to successfully train and use these models (e.g., dropout, data augmentation, etc.)
Providing an overview of the most successful Deep Learning architectures (e.g., convolutional networks, autoencoders for embedding, long-short term memories for sequence-to-sequence learning, etc.)
Providing an overview of the most successful applications with particular emphasis on models for solving visual recognition tasks.

Dublin Descriptors
Expected learning outcomes
Knowledge and understanding
Students will learn:
· What are neural networks and the fundamental methods and techniques used for neural networks training
· What are the fundamental architectures used in deep learning, such as convolutional neural networks and long-short term memories, and when to use them
· What are the neural network architectures used in the different visual recognition tasks
· What are the main differences between machine learning and deep learning
Applying knowledge and understanding
Given a specific data analysis problem, the student will be able to:
· Identify which paradigm better describes a given problem
· Identify which technique to start from with the analysis, apply it to model the data and evaluate its outcome
· Implement fundamental deep learning algorithms for image and text analysis autonomously
Making judgments
Given a complex data analysis problem, students will be able to:
· Identify the most relevant model to be applied in the specific problem
· Identify the occurrence of overfitting by the model under analysis
· Iteratively refine the selected model in order to balance performance, computational complexity and overfitting
· Compare and select different models for the problem under analysis
Communication
The student will learn to:
· Discuss in written form the pros and cons of different machine learning techniques for a specific problem
Lifelong learning skills
The student will learn to:
· Face a real-life data analysis problem with a sound and complete methodological approach
· Understand complex machine learning techniques beyond the fundamental ones presented during lectures
· Develop new machine learning pipelines adapting to the specific problem at hand

Neural networks are mature, flexible, and powerful non-linear data-driven models that have successfully been applied to solve complex tasks in science and engineering. The advent of the deep learning paradigm, i.e., the use of (neural) network to simultaneously learn an optimal data representation and the corresponding model, has further boosted neural networks and the data-driven paradigm. These topics will be described in the course according to the following detailed program:
From the Perceptron to Neural Networks and the Feedforward architecture
Backpropagation and Neural Networks training algorithms, e.g., Adagrad, Adam, etc.
Best practices in neural network training: overfitting and cross-validation, stopping criteria, weight decay, dropout, data resampling, and augmentation.
Image Classification Problem and Neural Networks
Recurrent Neural Networks and other relevant architectures, such as (Sparse) Neural Autoencoders
Theoretical results: Neural Networks as universal approximation tools, vanishing and exploding gradients, etc.
Introduction to the Deep Learning paradigm and its main differences with respect to classical Machine Learning
Convolutional Neural Networks (CNN) architecture
The breakthrough of CNN and its interpretation
CNN training and data-augmentation
Structural learning, Long-Short Term Memories, and their applications to text and speech
Autoencoders and data embedding, word2vec, variational autoencoders
Transfer Learning for pre-trained Deep models
Extended models, including Fully Convolutional CNN, networks for image segmentation (U-net) and object detection (e.g., R-CNN, YOLO )

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The course foresees a written exam and some homework assignments in the form of coding exercises/challenges. The written exam is aimed at verifying the acquisition of theoretical knowledge of the course subject, while the coding exercises aim at acquiring practical experience with the most widely used tools in the field.
The homework assignments contribute between 0 and 10 points to the final grade. The written exam is compulsory and will contribute between 0 and 22 points. The final grade is the sum of the grades for the homework assignments and the written exam.
Homework assignments need to be delivered during the course on fixed dates. The grade obtained on these assignments is valid for the entire academic year and can be combined with the written exam grade from any call in the same academic year.
Type of assessment
Description
Dublin descriptor
Written test
Solution of numerical problems
· Computation of simple backpropagation derivation
· Computation of simple sizing problems on CNN architectures
Answer to theoretical questions
· Formal derivation of learning techniques and models
· Comparison of models in terms of complexity, overfitting issues, and applicability in different cases of data analysis
1, 2
1, 2, 3, 4, 5
Assessment of practical homework
Execution of practical homework exercises
· Application of deep learning techniques to small dataset
· Application of model selection and validation techniques on simulated and real datasets
2, 3, 4, 5

Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning, Editore: MIT Press, ISBN: 978-0262035613 http://www.deeplearningbook.org/

L'insegnamento ha come obiettivo quello di introdurre, con una visione sistemica, lo studente alle problematiche della guida autonoma al fine di renderlo consapevole delle sfide tecnologiche che tale rivoluzione sta ponendo. In particolare, a valle di una panoramica sull'evoluzione dei sistemi ADAS che hanno portato, come naturale evoluzione, ai veicoli autonomi, il corso si articolerà in tre parti: la sensoristica necessaria alla guida autonoma, gli approcci controllistici e le sfide aperte, l'interazione del veicolo con l'ambiente circostante. Oltre alla parte di didattica frontale, grazie ai prototipi di veicoli autonomo sviluppati negli anni, lo studente avrà la possibilità di verificare praticamente gli aspetti principali del corso. Sono previsti interventi di esperti sia accademici che industriali del settore e, laddove possibile, visite guidate.

Autonomous vehicles and mobile robots require the integration of modelling, perception, planning, control, decision-making and software implementation. The course introduces the main theoretical and practical tools needed to understand and prototype autonomous vehicular and mobile robotic systems.
The course follows a modular autonomy-stack perspective, with emphasis on the see-think-act paradigm. After an introduction to autonomous and connected vehicles and mobile robots, the course covers vehicle and mobile-robot modelling, trajectory planning and tracking, motion planning, vehicular sensors, basic computer vision, localization and mapping, and decision logic.
A short overview will also be provided on how data-driven approaches can complement classical model-based methods in autonomous systems, for example in perception, prediction, decision support, model residual learning and learning-augmented control architectures.

Lectures, exercise sessions and project activities will allow students to:
understand the main components of the autonomy stack for autonomous vehicles and mobile robots, including modelling, perception, planning, control and decision logic;
model simple nonholonomic vehicular and mobile robotic systems and design basic trajectory planning, tracking and closed-loop control algorithms;
formulate and solve motion planning problems using graph-search and sampling-based methods;
understand the role of common vehicular and mobile robotic sensors, apply basic perception techniques, and interpret the use of data-driven methods as a complement to model-based pipelines;
critically analyze implementation choices, experimental results and system limitations, and communicate them through reports and project discussions

The topics dealt with in the course are:
Introduction to autonomous vehicles
Autonomous and connected vehicles and mobile robots
Automation, autonomy and levels of automation
Modular autonomy stack and see-think-act paradigm
Model-based and data-driven perspectives for autonomous systems
Modelling, planning and control
Vehicle and mobile robot kinematics
Trajectory generation, optimization and tracking
Open-loop and closed-loop motion control
Motion planning with graph-search and sampling-based methods
Sensors, perception and localization
Main sensors for autonomous vehicles and mobile robots
Introduction to computer vision and image processing
Feature extraction and basic object detection
Localization, mapping, occupancy grids and SLAM
Basic role of data-driven methods in perception and prediction
Decision logic and autonomous behaviour
Finite state machines
Event-based and signal-based decision logic
Hierarchical decision architectures
Software tools and laboratory activities
Project-based development of small autonomous systems

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
Students will be asked to develop assignments and a final project during the course.
The final examination will be based on an individual discussion including:
questions on the theoretical topics covered during the lectures;
discussion of the reports of at least 3 assignments out of 5 proposed during the course;
presentation and discussion of the final project.

R. Siegwart, I. R. Nourbakhsh, D. Scaramuzza, Introduction to Autonomous Mobile Robots
S. LaValle, Planning Algorithms
Note: The book can be freely downloaded from http://lavalle.pl/planning/
D. A. Forsyth, J. Ponce, Computer Vision: A Modern Approach
S. Thrun, W. Burgard, D. Fox, Probabilistic robotics
Note: Slides covering the topics of the book and additional material can be freely downloaded from http://www.probabilistic-robotics.org/
F. Gustafsson, Statistical Sensor Fusion
D. Simon, Optimal State Estimation: Kalman, Hinf, and Nonlinear Approaches
D. Bertsekas, Reinforcement Learning and Optimal Control
H.K. Khalil, Nonlinear Systems
Note: Slides covering the topics of the book can be freely downloaded from https://www.egr.msu.edu/khalil/NonlinearSystems/

The goal of the course is to enable students to understand and be familiar with model-based and simulation-based approaches to statistics. In particular, the course focuses on Bayesian learning, its tools and main classes of models. This will enhance students’ abilities to address the statistical analysis of complex systems for which transversal and multidisciplinary skills are required. The Bayesian approach tells us how to update prior beliefs about parameters and hypotheses of a probabilistic model in the light of data, to yield posterior beliefs. In particular, Bayes' Theorem quantifies the problem of how to learn from data. Bayesian learning hinges on simulation methods, typically MCMC algorithms, to compute the posterior distribution.
The course adopts innovative teaching methods:
a data analysis project, as a part of the student assessment, to enhance specific soft skills such as Making judgements, Communication skills and Ability in learning ( 3 rd, 4 th and 5 th elements of the so-called European “Dublin Descriptors” – DD )
collaborative activities among students, some in small groups, and with continuous assessment of learning. This type of activity is in presence.
This is a 10 ECTS course, course code # 052499. However, there is a version of it (code # 052502, Bayesian Statistics, 8 ECTS). The only difference between the two courses is that the topics of the 8-credits course do not include neither topic 6 nor models for areal and point-referenced data in topic 7 (see the list of topics below).
For the LM program in Mechanical Engineering, there is a 5 ECTS course in Bayesian Statistics. In this case, the topics are only 1-4 from the list below.

On successful completion of the course, students will be able to:
understand the fundamental principles, tools and models of Bayesian Statistics (DD 1 - knowledge and understanding )
model simple engineering problems in terms of statistical problems using the Bayesian approach to update prior belief in the light of new data (DD 2 - Ability in applying knowledge and understanding )
select appropriate Bayesian tools to give statistical answers and use appropriate software ( R packages, JAGS, Stan, Python) for the computation of posterior inference, or to build this software by themselves (DD 2)
operate and communicate the choices made, making independent judgments, when using Bayesian tools for dealing with statistical problems from the real world (DD 3, 4 and 5)
work effectively as part of a team.

The first part of the course (topic 1) will enable students to understand foundational aspects of Bayesian Statistics (the choice of the prior, for instance), while in the second part (topics 2-7), after the introduction of Markov Chain Monte Carlo techniques for simulation from the posterior, students will be able to use specific statistical models for estimation, prediction or clustering.
1. Basics of Bayesian inference. Likelihood principle, prior and posterior distribution. Bayes' Theorem for dominated models. Posterior summary values. Interpretation of scientific inference via the Bayesian approach. Simple univariate Bayesian models. The three main inferential problem: point estimation, hypothesis testing, interval estimation: comparison between the frequentist and the Bayesian approach. Prior distributions. The choice of a prior distribution, noninformative priors, conjugate priors and their mixtures, semi-conjugate priors. Robustness. Exchangeability and de Finetti's representation theorem for exchangeable sequences. Implications of de Finetti's theorem on the Bayesian approach. Predictive inference. Asymptotic results on the posterior distribution.
2. Simulation methods for Bayesian Statistics. A quick recap on the theory on general state space Markov chains. Markov chain Monte Carlo methods. Gibbs sampler and Metropolis-Hastings algorithms for computing posterior inference. Implementing Markov chain Monte Carlo: software for Markov chain Monte Carlo (BUGS/JAGS from R), assessing convergence and run-length.
3. Goodness-of-fit and model choice. AIC, BIC, DIC, Predictive Bayesian tail probabilities, log-pseudo marginal likelihood (LPML), WAIC; prior and posterior distributions for the model index, maximum a posteriori (MAP) model selection.
4. Bayesian linear models and generalized linear models. Hierarchical linear models with random effects. Parameter estimation and covariate selection.
5. Bayesian survival analysis / reliability with censored data. Regression models: accelerated failure time and proportional hazards models.
6. Bayesian nonparametric models. The Dirichlet process and generalizations. Bayesian nonparametric mixture models, with application to density estimation and clustering.
7. Introduction to models for longitudinal data, time series, spatial data (point-referenced and areal data).
Within the Innovative teaching activity, we include 2 classes (4h + 4 h) in presence, during which students will be required to do exercises for designing and implementing (using Python or R software) algorithms for simulation, supervised by tutors and the teaching assistant. This type of active learning will include continuous assessment of learning.
The oral exam consists in the presentation of the project (in groups), focusing on a statistical problem with data, using Bayesian models, to enhance students’ soft skills such as Making judgements, Communication skills and Ability in learning. There will be intermediate revisions of the projects (this is a group activity), where the groups will discuss with tutors, TA and instructors, in presence. This type of active learning will include continuous assessment of learning.
The list of topics for the course with code # 052502, 8 ECTS, do not include topic 6 nor models for areal and point-referenced data in topic 7.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists of two parts: a written exam and a project work (with a final oral presentation). It is compulsory to register for the written exam, which is scheduled twice in January-February, twice in June-July, and one in September.
The final project assessment is the presentation of the work on project, i.e. analyzing a statistical problem with data, using Bayesian tools and models. The projects will be developed in teams. The evaluation of the projects will be based on the revisions (activity in presence - at most two) the teams will undergo during the course and a conclusive presentation. During the conclusive presentation, each students’ team must hand over a project report (10-20 pages).
Participation in presence to the revisions and the final presentation is compulsory for all team members, but for Erasmus students.
If, at the beginning of the semester, the student understands he will not be able to actively participate in the group project during the semester for any reason, the student is allowed to discuss an individual project after passing the written test, instead of the group project. Because the student will not be tested on all the Expected Learning Outcomes (Risultati di apprendimento attesi), the final grading of the individual project cannot be larger than 26/30.
To obtain a positive final mark, the student should pass with a grade greater or equal than 18/30 for both parts of the exam.
Final grading: 40% written exam, 60% project work.
After the exam:
the student will know the fundamental principles, tools and models of Bayesian Statistics (DD1),
he/she will be able to apply the acquired knowledge to statistical problems from the real world (DD2),
making independent judgments, the student will operate and communicate the choices made, when using Bayesian tools to solve statistical problems from the real world (DD3,DD4,DD5).

Rosner, G. L., Laud, P. W., Johnson, W. O., Bayesian Thinking in Biostatistics, Editore: Chapman and Hall/CRC, Anno edizione: 2021
Guglielmi, Lecture Notes
Jackman, S., Bayesian analysis for the Social Sciences, Editore: Wiley, Anno edizione: 2009, ISBN: 978-0-470-01154-6
Andrew Gelman et al., Bayesian Workflow, Editore: Taylor and Francis
Lunn D., Jackson C., Best N., Thomas A., Spiegelhalter D., The BUGS book, Editore: CRC Press, Anno edizione: 2013, ISBN: 978-1-58488-849-9
Hoff, P., A first course in Bayesian Statistical Methods, Editore: Springer, Anno edizione: 2009, ISBN: 978-0-387-92299-7
Mueller, P., Quintana, F., Jara, A., Hanson, T., Bayesian Nonparametric Data Analysis, Editore: Springer, Anno edizione: 2015
Christensen, R., Johnson, W., Branscum, A., Hanson, T.E., Bayesian Ideas and Data Analysis, Editore: CRC Press, Anno edizione: 2011, ISBN: 978-1-4398-0354-7

Goals
The objective of the course is to present to the students, approaching the end of their M.Sc. educational carrier, an overview of the field of biochips and analytical lab-on-chip microsystems (whose recent advances are relevant both from the scientific and industrial point of view) with specific insights on the technological aspects of the interface between (micro)electronics and electrochemistry and biology, both at cellular and molecular levels. The content of the course reflects the multidisciplinarity of the nano-bio-tech field and is mainly focused on the different manipulation and detection approaches of biochemical target analytes on chip. The main goal is to provide the students with the fundamental theoretical tools for the design of active microfluidic systems (basics of fluid dynamics at the microscale), and of the engineering of the detection systems (optical and electrochemical transducers). At the same time, several practical examples are discussed in order to illustrate design choices and trade-offs. Starting from 2020, a part of the course will be taught by means of innovative learning techniques. The topics of microfabrication (hard and soft-lithography) will be addressed by means of MOOC videos recorded in actual clean-rooms and fabrication facilities. Finally, a "blended" and "flipped-classroom" approach will be adopted in the last part of the course including a project-based and a laboratory activities where student will fabricate real devices and boards: at first they will be grouped into small teams (3-4 persons max.), will design at home the layout of the microchannels and electrodes on a PCB including a transimpedance amplifiers, according to some design challenges posed by the teacher, and then will fabricate them in the lab with 3D printing and soft-lithography (PDMS elastomer by means of replica molding). A characterization with fluids, electrolytes. digital microscopes, pumps and virtual instrumentation (oscilloscope, network analyzer used for impedance measurements) will conclude this experimental activity. Prior to fabrication of the PCB, each team will present their design in the class and feedback from a general discussion will be collected.

Expected Learning Outcomes
Knowledge and understanding (Dublin Descriptor #1)
At the end of the course the students are expected to:
· possess a good understanding of lab-on-chip systems (needs, applications, advantages and limits) and bio-electronics convergence
· possess a basic knowledge of hard and soft lithographic microfabrication approaches
· possess a basic knowledge of the laws describing the flow of liquid in microchannels and the forces to actuate particles in liquid
· presses a good knowledge of the electrochemical interface and instrumentation for biosensing
· possess a good knowledge of the DNA macromolecule and the instrumentation for its analysis
· understand the potentials and challenges of CMOS/biochips integration
Applying knowledge and understanding (Dublin Descriptor #2)
At the end of the course the students are expected to:
· be able to analyze and design a microfluidic system in laminar regime (fluidic sizing, choice of components such as pumps/valves), starting from the sample preparation and manipulation
· be able to design an analytical assay (for instance for molecular recognition or DNA analysis)
· be able to design integrated detectors (both optical and electrochemical)
· be able to design current and impedance sensing circuits for biochips
Making judgements (Dublin Descriptor #3)
Students will be able to:
· evaluate the most appropriate approach (materials, fabrication) to address an analytical need
· apply the knowledge to different application areas
· apply the knowledge to design a novel micro-device
Communication (Dublin Descriptor #4)
During the work in teams for the experimental laboratory, students will be able to communicate among each other (in the first phase at home, when the microfluidic channels are designed upon technological specifications set in the classroom). Then, during the lab. and the oral exam their communication skills are deployed to motivate their design choices and comment the experimental results.

Topics
The course is articulated in theoretical lessons, combined with quantitative exercises and with case studies oriented to the analysis and design of microsystems. An experimental laboratory consisting of: a design phase at home in teams with a propor design software and two days of experimental activity in the lab. (fabrication and characterization of a PDMS microfluidic device). Experts in the biochip field are also invited during the course to lecture seminars on specific topics, such as micromagnetism and DNA analysis, or to present the point of view of companies carrying on R&D in the biochip field (STMicroelectronics, Flextronics, Dianax etc…). A visit to the renewed clean-room and microfabrication facility of Politecnico di Milano (PoliFab) concludes the course.
1. Introduction to biochips: architecture of lab-a-chip micro-analytical systems, motivations and impact, design paradigms, market projections, basic biological macromolecules used for as receptors in affinity biosensors.
2. Introduction to microfluidics: fluid dynamics, Reynolds number, electrical equivalent of hydraulic circuits (fluidic capacitance) and electro-osmotic flow. Actuation forces for particle manipulation within biochips: diffusion, electrophoresis, dielectrophoresis, electrowetting and droplet-based digital microfluidics. Active and passive microfluidic components: valves, mixers and pumps.
3. Introduction to microfabrication: review of Silicon CMOS-MEMS processes, lithography, thin film deposition and patterning, as compared to elastomer (PDMS) and plastic based soft lithography (replica molding).
4. Optical detection: fluorescence (strengths and limitations, Atomic Force Microscopy ), source-filter-detector architectures, integrated photonics for biosensing based on evanescent field (waveguides, Mach-Zehnder interferometers, ring resonators and contactless light monitors). Electrochemical detection: the electrochemical interface with physiological ionic solutions (charge transfer and induction).
5. Electrochemical instrumentation: analytical techniques (cyclic voltammetry, amperometry and impedance spectroscopy) and the potentiostatic workstations. Micro and nano-scale electrochemistry: effects of electrode scaling.
6. Low-noise current measurements: review of noise in electronic devices, the transimpedance amplifier (working principle, properties and limitations) and advanced circuit topologies (integrator-differentiator schemes with different CMOS-compatible bias resetting solutions).
7. Impedance measurements and instrumentation, comparison of sensing configurations: bridge, ratiometric, current sensing, lock-in detection, resonant circuits, FFT-based and time-domain approaches.
8. Detection of DNA: structure and properties, microarrays (spotting and probe synthesis), electrophoresis, amplification with Polymerase Chain Reaction and quantitative detection with real-time PCR and approaches for sequencing.
9. Biochips for molecular detection: resonating cantilevers for molecular weighing, amperometric detection of neurotransmitters, redox cycling, glucose sensors based on enzymatic mediators, and nanopores. Biochips for cellular detection: interface with electrogenic cells, equivalent model of passive cells, label-free impedance monitoring a cell colony dynamics and single cell counting and sizing with microfluidic impedance flow cytometry (design case study).
10. Sample preparation (cell lysis, sample mixing, concentration and purification). Microelectronics CMOS biochips: state of the art performance in CMOS detection, design criteria, advantages and limits, the critical role of the substrate, packaging and interfacing issues.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente) o condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Assessment
Exams are held at the end of the course (no intermediate tests). The exam consists of a written test (of a duration of 2 hours) followed by an oral exam. The written test (assessing Dublin Descriptors 1 and 2) encompasses the solution of numerical exercises focusing on 2 types. The first type concerns the microfabrication and the fluidics (and components) of micro-channels and devices. The second type mostly focuses on electrochemical detection. The students will be asked to analyze circuits and systems, as well as to design them. The maximum evaluation of the written test is 30. Two bonus points are added for those who attended the laboratory activity.
The outcome of the written tests is communicated to the students by email. Then, a meeting in the classroom is scheduled for the students to vision and discuss the correction of the written test. They can accept or refuse the evaluation, either by email or in-person communication. They can undertake the oral test in the following days, by agreeing a calendar with the teacher.
The oral discussion (assessing Dublin Descriptors 1,2,3,4) is mandatory for students achieving top marks in the ranking (> 27/30) in the written test and it is optional and open for all students with a mark above 17/30 in the written test. In the oral test (lasting 15 to 40 minutes) students will be asked discuss the ultimate limits of the different technologies, pros and cons, compare them, and to design complete systems to address novel design cases proposed during the oral exam. The maximum evaluation is 30 cum laude.

Patrick Tabeling, Introduction to Microfluidics, Editore: Oxford University Press, Anno edizione: 2010, ISBN: 9780199588169
Eugenio Iannone, Labs on Chip: Principles, Design and Technology, Editore: CRC Press, Anno edizione: 2014, ISBN: 978-1466560727
Albert Folch, Hidden in Plain Sight: The History, Science, and Engineering of Microfluidic Technology, Anno edizione: 2022

Il modulo "Bio-Inspired Design" offre competenze avanzate di progettazione interdisciplinare e pensiero critico, sfruttando le lezioni apprese dalla natura e dimostrando come questa conoscenza possa portare a soluzioni ingegneristiche più creative e sostenibili. Il modulo fornisce competenze teoriche ed applicative per realizzare il modello concettuale di un prodotto o di un processo seguendo un ragionamento sistemico, estrarre principi di progettazione dalle soluzioni naturali, applicare euristiche per stimolare la generazione di idee, guidare un processo di progettazione bio-ispirato problem-driven o solution-driven, nonché per cercare anteriorità brevettuali di una soluzione inventiva e proteggere la Proprietà Intellettuale generata.

The teaching gives an overview of non-conventional mechanical approaches in Nature and shows how this knowledge can lead to more creativity in robotics and to better (simpler, smaller, more robust) solutions than with conventional technology. The course discusses a large number of biological features that can be interesting in robotics and presents innovative ways to exploit them through technical examples and designs of bio-inspired machines and robots.

By the end of the course, the students will be able to:
Knowledge and understanding

• discuss how biological systems can work to solve engineering or design problems
• know the working principles of bioinspired design and biomimetic design
• discuss how biological fatures can be exploited in robotics
• know the state of the art of bioinspired technologies in robotics and future challenges in the field
  Apply the acquired knowledge and understanding
• extract design principles from natural solutions and adapt them to practical problems
• identify natural features useful in robotics
• adapt natural features to robotics
  Further developed skills
• develop familiarity with reasoning across disciplines to come up with novel solutions
• develop collaboration abilities through interaction with the team-mates
• develop communication skills through interaction with tutors
• develop learning abilities by autonomously acquiring information and data needed for the advancement of the project activities
• have a critical approach to technical solutions

• Introduction to bio-inspired robotics
• Drivers in Nature useful in robotics (energy saving, smart materials, green design, etc.)
• Locomotion on the ground (crawling, jumping, walking/running, digging, climbing)
• Locomotion in water (propulsion, oscillation, ondulation)
• Basics of locomotion in air (lighter than air systems, flapping)
• Clamping & Handling
• Maintenance and repair
• Future trends in bioinspired robotics (soft-robotics, growing robots, biobehaviours and group intelligence, etc.)
  Each topic will be developed showing different biological solutions, highlighting the most interesting features and operating principles and proposing technical solutions capable of adapting these functions to robotics
  During the course students have to develop a project in a team to put in practice what they learned.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The course consists of lectures and practice sessions, including a collaborative project.
The evaluation is based on a project work developed in team and on a discussion on course topics.
Evaluation is based on the review sessions along the semester and on the final presentation. The project work allows checking the achievement of expected results in terms of application abilities, learning and communication skills.

This course aims to equip students with the tools necessary to identify, understand, analyze, and integrate bio-inspired solutions for engineering problems related to the structural design of mechanical components. By investigating several examples of bio-inspired engineering solutions, the course will emphasize how to extract corresponding structural design principles and fundamental mechanisms. Significant attention will be paid to mechanical properties, mechanical design, and manufacturing approaches, essential for exploring these bio-inspired solutions.
The specific objectives of the course are:
To provide the ability to identify biomimetic structural design principles.
To explore the critical inspiring aspects in various structural categories and how they have been implemented in bio-inspired structural design.
To analyze how the principles of structural design and manufacturing tools can be used to implement bio-inspired solutions to tackle challenging structural problems.

At the end of the course, students are expected to have developed skills and competencies as established in the training objectives. In terms of knowledge and understanding, students will be able to:
Describe the principles of classic bioinspired structural designs.
Categorize bioinspired structural solutions based on their main source of inspiration, considering the three major classes: shape and morphology, structure and architecture, and surface features and texture.
Identify the fundamental biomimetic structural design concepts and the working principles for each main category.
Interpret and discuss the related materials-structure–property relationships for the categories covered during the course.
Analyze the implementation of such bioinspired structural principles from an engineering perspective.
Active participation in the proposed teaching activities is encouraged through an interactive teaching method, which combines lectures and practical group activities. These exercises aim to directly involve students in the definition, design, analysis, and implementation of bioinspired structural solutions, primarily through team projects developed during the exercise sessions. Brainstorming and critical discussions in teams will enhance and strengthen students' ability to identify and explore natural structural design strategies and develop innovative solutions. These activities will also help students develop problem-solving skills, improve teamwork abilities, and enhance presentation and communication skills. The following phases will be addressed during the exercise sessions:
Identification of architectural elements and geometrical aspects in natural systems that contribute to their advanced mechanical performance.
Definition of structural design concepts for the creative generation of periodic lattice structures inspired by the identified geometrical and structural features.
Evaluation of the structural integrity of the designed lattice structures through finite element analysis and possible experimental tests.
Practical implementation of theoretical solutions, report preparation, and presentation of the obtained results in the corresponding project.

The teaching activities are conducted through lectures and exercise sessions. The lectures cover topics that explore architecture, shape, and surface inspiration for enhanced structural performance, as briefly described below:
Introduction to Bioinspired Structural Design
Methodology in Bioinspired Structural Design
Structure and Architecture as Inspiration
Architected Lattice Structures
Heterogeneous Structures
Functions and Bioinspired Applications of Gradients
Kirigami- and Origami-Based Bioinspired Structural Solutions
Shape and Morphology as Inspiration
Surface and Texture as Inspiration
The exercise sessions aim to expand and consolidate the knowledge gained during the lectures by defining course projects to be developed in groups. Each group will define a distinct bioinspired solution to an engineering structural problem, design an adapted structure, and analyze its structural performance using commercial FEA software (e.g., ABAQUS). Students will receive brief training on how to design, model, and optimize such structures with CAD software and analyze them with FEA software. Possible experimental tests are also envisioned for some of the suggested solutions.
Additionally, some seminars are planned during the course. National and international experts from the relevant fields will be invited to provide insights into advanced bioinspired structural design solutions related to the topics covered in the course.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final evaluation consists of the development and presentation of a team project, followed by an oral exam. The oral exam can only be taken in the semester when the project evaluation has been successful. Students' project will be evaluated based on their contribution to the teamwork, their presentation, and whether their project has addressed the main defined goals.
The final grade is determined by combining the marks from the final project report and presentation (50%) and the oral exam (50%). To pass the course, students must achieve a total grade between 18/30 and 30/30.
Project Reporting and Presentation: Students will be divided into groups. During the exercise sessions, each group will work on the identification, design, implementation, and analysis of an individual bioinspired structural solution that can be studied in the form of periodic structures. The structure will be modeled and analyzed using finite element analysis. Possible experiments can be envisioned on some of the most promising designs developed by the students, which will be 3D-printed. Students are required to prepare a comprehensive written report on the project’s development phases and results.
Oral Exam: The student’s knowledge of the major principles of bioinspired structural design discussed during the course and their ability to apply these principles to engineering structural problems will be evaluated. The oral exam will consist of questions about the underlying mechanisms, physical phenomena, and theoretical implementation regarding the examples and design concepts covered during the course, both in lectures (theoretical nature) and exercises. Depending on specific organizational needs, the oral exam may require composing written answers, subject to discussion with the course instructor.

Zhenhai Xia, Biomimetic principles and design of advanced engineering materials, Editore: John Wiley & Sons, Ltd, Anno edizione: 2016

Questo insegnamento tratta le principali operazioni unitarie dell'industria di processo, con particolare attenzione al loro ruolo nei processi di trasformazione e impiego delle risorse energetiche. In particolare, applica i principi fondamentali degli equilibri di fase per progettare e gestire le principali unità di separazione, quali flash, colonne di distillazione binaria e multicomponente, unità di assorbimento e stripping, apparecchiature per l'estrazione con solvente e per l'adsorbimento.

Climate change, environmental pollution, resource scarcity are the contemporary challenges that call for urgent transition of the industry from the traditional paradigm of production and consumption towards circular economy and sustainable development. This course is designed to provide students with concepts and instruments necessary for analysing industrial practices in terms of their environmental performance, and for identification of relevant circular economy strategies for decoupling economic growth from environmental degradation, increasing resource efficiency and promoting sustainable lifestyles. The emphasis is given to the systemic perspective in examination of circular economy approaches at company and industrial system levels.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
Identify trends, technologies, key methodologies and stakeholder needs related to circular economy at company and industrial system levels
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and social environment

A student that has successfully attended the course is expected to:
Understand the role of circular economy in enabling the decoupling of economic activities from negative environmental impacts and fostering the transition towards sustainable development
Know and explain circular economy strategies and their limitations at company and industrial system levels
Identify and apply appropriate instruments for analyzing circularity and environmental impact of industrial operations
Critically analyse industrial practices and identify opportunities for improving their circularity

Basics of circular economy: industrial ecology, sustainable development, principles of circular economy, limitations of circular economy, circular economy strategies
Circular economy at the company level: circular product design, product/material end-of-life management: reuse, remanufacturing, recycling
Circular economy at the industrial system level: circular supply chain management, industrial symbiosis
Circularity and environmental impact analysis instruments: circularity indicators, environmental key performance indicators, material flow analysis, life cycle assessment
The course is organised in lectures (traditional and flipped classroom formats), seminars with guest speakers, exercises, business game sessions.
The lectrues will be streamlined online via Webex and recorded.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation of the course is based on a group assignment and an oral exam. The group assignment aims to evaluate student's ability to identify and apply appropriate instruments to develop a circular transition pathway in a specific industrial context. The oral exam aims to evaluate knowledge of the course materials, ability to indicate interconnections of discussed concepts and instruments and their limitations. During the semester, three self-assessment tests will be available for students to evaluate their understanding of the course content and preparation for the oral exam.

Slides and other classroom materials will be available on the WeBeep website of the course https://webeep.polimi.it/

Objective of the course is to introduce the basic principles and design instruments for collaborative robotic devices, when coupled with a human being, to assist, rehabilitate, or augment movement capabilities. The main steps of the design of collaborative robotics in the healthcare domain are the definition of functional and technical requirements following a user-centered approach, the identification of a proper mechatronic framework, the identification of a sensor network for proprioception, and the definition of low level and high-level collaborative control framework.
A technical and functional evaluation with tests on a testbench and human subjects are finally needed.
Specific objectives of the course are:
to learn the methodology to define user specifications and technical requirements;
to learn the knowledge needed to understand and design the mechatronics system;
to learn the knowledge needed to understand and design the cooperative control framework;
to learn the knowledge needed to understand and design the sensor network for user’s intention detection and proprioception layer;
to understand how to perform Verification and Validation (V&V) of the integrated system.
The course has a strong practical and laboratory-based approach.

Lectures will be delivered by the lecturers followed by practical guided examples and open discussions. This will allow students to (DdD 1):
Analyze and understand the goals, assumptions and requirements associated to a collaborative robot, and model them formally;
Define the architecture of a collaborative robot mechatronic and control framework, and model them formally;
Identify and define the verification and validation activities needed for a collaborative robot.
The laboratory activities and the project work will allow students to (DdD2 and DdD3):
Simulate in Matlab environment kinematic, dynamic and path planning of a collaborative robot;
Design, build and control a simple collaborative robot;
Learn how to solve problems not strictly faced within the Course.

Introduction to the collaborative robotics problem - what is a collaborative robot for human augmentation; typical applications and trend for collaborative robots in healthcare (e.g., assistive robots, rehabilitation robots, service robots); a Short History of collaborative robots; robot classification (interaction modalities, end-effectors/rigid exoskeletons/soft exoskeletons, active/passive, etc.); different types of joints.
Definition of technical and functional requirements following a user-centered approach.
Kinematics of collaborative robots - forward and inverse kinematic problem; position, velocity and acceleration, joints and task space description.
Dynamics of collaborative robots, specifically related to robots worn by human subjects.
Basics of hardware-level designs for compliance.
Basics of low-Level Robot-Assisted Control Strategies (e.g. impedance, admittance).
Introduction to high-Level interaction Modalities (e.g. passive, active-assisted, active-resisted, error-augmentation).
Trajectory/motion planning for a collaborative robot.
Overview of strategies for user’s intention detection, including the selection of proper sensors to detect user’s intention of movement (e.g. inertial sensors, EMG sensors, eye tracking, Brain-computer interface) and basics of signal processing of biological signals.
Verification and Validation process.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
During the course, the students will work in small teams under the supervision of a lecturer and of a tutor.
Each group will be assigned with a specific assignment involving the definition of the functional specifications of a collaborative robot for healthcare applications and the use of a dedicated hardware. Students will be required to define the technical requirements, design the mechatronic system, integrate the sensors needed to detect the user’s intention, develop the control system, and perform preliminary functional tests.
A one-degree-of-freedom exoskeleton for educational purposes will be used to to carry out the assignment (EduExo Pro, AUXIVO).
The two course modules share a single final assessment, consisting of the following components:
Interim project presentation (6%): each group will present the progress of the project according to the schedule introduced by the lecturers during the first class and published on the course WeBeep page.
Project submission and demonstration (25%): during the final class of the semester, each group will submit the project code and present a practical demonstration of the developed system, according to the schedule published on WeBeep.
Individual examination (69%): during the official examination sessions, each student will be assessed individually through:
a written exercise covering the course topics (19%);
an individual discussion of the project (37.5%);
an oral examination on the course content (12.5%).
Please note that the grade awarded for the project component cannot be rejected or repeated within the same academic year.

Etienne Burdet, David W. Franklin, Theodore E. Milner., Human Robotics: Neuromechanics and Motor Control., Editore: The MIT Press, Cambridge, Massachusetts, London (UK).
Books of industrial robotics

Questo insegnamento ha l'obiettivo di mettere l’allievo in condizione di comprendere le nozioni fondamentali dei processi di combustione. Partendo da concetti fondamentali di termochimica (stechiometria, temperatura adiabatica di fiamma, equilibrio chimico) il corso si sviluppa nell’analisi dei fenomeni dell’ignizione e dell’estinzione, dei limiti di infiammabilità, delle fiamme premiscelate e delle sue diverse modalità di propagazione (deflagrazione, detonazione). Concetti che sono alla base dei sistemi di produzione dell’energia, dei motori a combustione interna e delle turbine a gas, degli impianti di riscaldamento, e di numerosissimi processi industriali.Nel caso di combustioni accidentali si devono comprendere le conseguenze sulle persone e sulle cose e i principali metodi di prevenzione.

• Lo studente conosce i concetti di base della combustione, i modelli fisico/chimici necessari alla descrizione dei fenomeni di combustione e le principali proprietà di tali fenomeni;
• Lo studente è in grado di descrivere sia qualitativamente sia in forma matematica i principali fenomeni di combustione, quali ad esempio: detonazione e deflagrazione, accensione spontanea e forzata, propagazione della fiamma, limiti di propagazione, stabilizzazione della fiamma;
• Lo studente è in grado di descrivere qualitativamente le principali conseguenze di combustioni accidentali;
• Lo studente è capace di applicare le conoscenze sopra descritte per valutare le caratteristiche di processi di combustione (temperatura adiabatiche di fiamma, infiammabilità miscele, stabilizzazione di fiamme laminari) e l’influenza dei diversi parametri operativi (pressione, temperatura, composizione).
• Lo studente è capace di risolvere in modo autonomo problemi legati agli argomenti trattati disponendo di informazioni incomplete e reperendo le informazioni necessarie nella manualistica tecnico/scientifica.
• Lo studente è capace di applicare le conoscenze sopra descritte per valutare le caratteristiche di processi di combustione (temperatura adiabatiche di fiamma, infiammabilità miscele, stabilizzazione di fiamme laminari) e l’influenza dei diversi parametri operativi (pressione, temperatura, composizione).
• Lo studente è capace di risolvere in modo autonomo problemi legati agli argomenti trattati disponendo di informazioni incomplete e reperendo le informazioni necessarie nella manualistica tecnico/scientifica.
• Lo studente è capace di elaborare e interpretare dati sperimentali ottenuti mediante analisi di immagini di fiamme laminari.

Arg. 1. Richiami di cinetica chimica e di termochimica. Equazioni di bilancio (massa, quantità di moto ed energia).
Arg.2. Ignizione spontanea e forzata, temperatura di ignizione, flash point e fire point, energia di accensione, limiti di infiammabilità, temperature-limite.
Arg. 3. Struttura di fiamme omogenee. Modelli di propagazione di fiamme laminari omogenee. Fiamme di diffusione. Fiamme eterogenee. Combustione in atmosfere arricchite di ossigeno e in ossigeno puro. Tecniche sperimentali per la determinazione della velocità laminare di fiamma.
Arg. 4. Deflagrazione e detonazione. Deflagrazione in volume chiuso e parzialmente confinato. La legge cubica.
Arg. 5. Estinzione. Limiti di propagazione delle fiamme. Distanza di estinzione. Sostanze estinguenti.
Arg. 6. Stabilizzazione delle fiamme.
Arg. 7. Genesi e formazione di sostanze inquinanti (ossido di carbonio, ossidi di azoto). Tossicità dei gas combusti (ossido di carbonio).
Arg. 8. Prevenzione e sicurezza (sistemi di protezione di fiamma, aperture di ventilazione, ecc.).
E' prevista una breve attività laboratoriale focalizzata all'analisi di dati sperimentali (imaging, chemiluminecenza, temperature) raccolti su semplici fiamme laminari.
Per l'insegnamento di Combustione e Sicurezza da 5 CFU (codice insegnamento: 062318) per gli allievi di Ing. Meccanica gli argomenti trattati sono quelli indicati sopra ma limitatamente ai numeri 1, 2, 3, 4 e 8.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
L’esame consta di una prova scritta composta da domande di teoria a risposta aperta e chiusa e da problemi che richiedono uno svolgimento numerico. Condizione necessaria per il superamento dell’esame è lo svolgimento in modo corretto e completo di almeno la metà delle domande di teoria e di almeno la metà dei problemi numerici. Il voto terrà conto anche della chiarezza di esposizione.
Nel caso il docente lo ritenga necessario ai fini della valutazione, potrà essere richiesto un colloquio orale per discutere lo svolgimento della prova scritta.
La prova è volta ad accertare la capacità di:

• impostare, descrivere e analizzare sinteticamente i diversi modelli fisico chimici alla base dei principali fenomeni di oggetti del corso (temperatura adiabatica di fiamma, ignizione, deflagrazioni e detonazioni, propagazione della fiamma, stabilizzazione della fiamma, estinzione, limiti di infiammabilità)
• descrivere e analizzare qualitativamente gli effetti dei principali parametri operativi (pressione, temperatura, tipologia di ossidante, confinamento etc) sul processo di combustione.
• valutare le caratteristiche di processi di combustione attraverso la determinazione numerica della stechiometria di processi di combustione, della temperatura adiabatica di fiamma, delle caratteristiche di infiammabilità di miscele, delle condizioni critiche per l’accensione spontanea, delle condizioni di stabilità di fiamme premiscelate laminari.
• capacità di risolvere i problemi assegnati disponendo di informazioni incomplete e reperendo le informazioni necessarie nella manualistica tecnica.

C. Ortolani, Combustione, Editore: Maggioli Editore, Anno edizione: 2006, ISBN: 978-88-387-4189-1
S.R. Turns, An Introduction to Combustion: Concepts and Applications - Third Edition, Editore: McGraw-Hill Higher Education, Anno edizione: 2011, ISBN: 978-0073380193

The course will provide the students with the fundamentals of communication and networking, with particular reference to the technologies currently deployed on-field in industrial and vehicular systems, driving the transformation of Industry 4.0 and connected mobility.
It will first introduce the basic elements of computer networks and the Internet, their architectures, working principles and performances. The different protocols of the layered architecture will be presented according to a top-down approach, from the application to the physical layer, including wired and wireless technologies for network access.
Next, the course will delve into technological solutions for industrial use-cases, with focus on industrial automation, i.e., interconnection of devices in the Industrial Internet of Things (e.g., industrial Ethernet, Profinet), and automotive communication technologies, i.e., in-vehicle communication networks (e.g., CAN, FlexRay) and Vehicle-to-Everything (V2X) technologies (e.g., ITS-G5, C-V2X).

1 - Knowledge and understanding
Know the main communication technology used nowadays in industrial and vehicle engineering
Know the main performance metrics of a communication system
Analyze the most appropriate communication technology for the specific industrial and vehicular use case
Understand the requirements and limits of communication technology
Evaluate the need of improvements and implementations
2 - Applying knowledge and understanding
Evaluate the technical requirements of use cases for an optimal selection of the communication technology
Define the key features of an industrial/vehicular communication systems to be fulfilled for a correct functionality
3 - Making judgements
Identify the best technological solution for deploying a new communication system
Recognize the limits of a communication technology and define a roadmap for enhancements
Identify the technological barrier of current standards to prevent inefficient installation
Associate the correct communication technology to the specific engineering need
Select the optimal communication technology for the implementation of an industrial/vehicular application
Be able to understand the potentialities of new technologies
4 - Communication
Interact with technical experts about on-field deployment
Negotiate with technology providers by clearly defining the design need of a communication system

Numbers and history of the Internet
Basics of communication networks: definitions, architectures, requirements and performances, technologies
Application layer: client-server and peer-to-peer approaches, HTTP, FTP, SMTP, DNS
Transport layer: reliable (TCP) and unreliable (UDP) packet transport
Internet networking: structure of the network, Internet protocol specifications and information forwarding, addressing, routing
Link layer: logical link control (LLC) and medium access control (MAC)
Physical layer: features and challenges of wired and wireless technologies
Industrial communication technologies: FieldBUS, industrial Ethernet, Modbus, PROFIBUS, PROFINET
Industrial wireless: wirelessHART, IoT, 5G
Automotive communication technologies: in-vehicle communications (CAN, FlexRay)
Automotive communication technologies: V2X communications (ITS-G5, C-V2X) and their evolution
V2X services and evolution towards connected automated driving
Current trends in Industry 4.0 and mobility

Prova orale facoltativa (a scelta dello studente)
Valutazione continua facoltativa (a scelta dello studente)
The course adopts a continuous assessment scheme based on intermediate examinations. Each examination assesses the learning outcomes covered in the corresponding part of the course.
Students who do not participate in, do not pass, or wish to improve the outcome of the continuous assessment may take the regular final examination (oral exam) covering the entire course syllabus.

Slides available on WeBeep
Jim Kurose, Keith Ross, Computer Networking: a top down approach, Editore: Pearson, Anno edizione: 8
Richard Zurawski, Industrial Communication Technology Handbook, Editore: CRC Press, Anno edizione: 2, ISBN: 9781138071810
Bogdan M. Wilamowski, J. David Irwin, Industrial Communication Systems, Editore: CRC Press, ISBN: 9781138071803
Claudia Campolo, Antonella Molinaro, Riccardo Scopigno, Vehicular ad hoc Networks - Standards, Solutions, and Research, Editore: Springer, ISBN: 978-3-319-15497-8
Markus Dillinger, Mikael Fallgren, Toktam Mahmoodi, Tommy Svensson, Cellular V2X for Connected Automated Driving, Editore: Wiley, Anno edizione: 2021, ISBN: 978-1119692645

This course explores advanced topics in Computational Fluid Dynamics (CFD), focusing on the practical application of simulation techniques to the complex flow phenomena encountered across engineering. Students will learn to develop and implement CFD models for a broad range of flow processes, including compressible flows, chemically reacting flows, multiphase flows, moving boundaries and grids, and heat transfer. Building on the introductory course Computational Fluid Dynamics: Fundamentals, it emphasizes advanced simulation strategies rather than the detailed mathematical formulation of numerical methods. Throughout, students will work through real-world examples drawn from mechanical engineering and related fields, and dedicated sessions will address the development and integration of custom models for simulating complex physical phenomena.

Learning Outcomes
By the end of the course, students will be able to translate complex multiphysics fluid dynamics problems—typically described by partial differential equations (PDEs)—into discretized systems of equations and solve them using appropriate numerical techniques. This includes a solid understanding of numerical stability, convergence, and consistency, applied to a wide range of scenarios from single-phase to multiphase flows, incorporating heat transfer and moving grids.
Lectures and exercise sessions will enable students to:
Identify the most suitable modeling approach for complex, multiphysics problems.
Select the optimal simulation strategy and level of approximation for solving advanced flow scenarios.
Evaluate the impact of setup choices on CFD simulation results and effectively conduct post-processing.
Implement custom models within a CFD framework to extend the software’s capabilities.
The project laboratory will provide students with practical experience to:
Set up a well-posed compressible flow problem, selecting appropriate numerical schemes and solvers.
Generate computational grids for multi-region and multi-domain configurations.
Configure CFD simulations, including boundary and initial conditions, and define grid motion strategies.
Choose and apply the most appropriate multiphase modeling approach (e.g., Lagrangian, Eulerian, Eulerian dispersed, Eulerian VOF).
Post-process and analyze simulation results to extract meaningful insights.

Course Topics
CFD Simulation of Compressible Flows: Extension of pressure-based solution methods to compressible flow regimes. Density-based approach. Treatment of boundary conditions for subsonic and supersonic flows. Overview of available solvers for compressible flow simulations and techniques for effective post-processing.
Moving Grid Strategies: Approaches for handling small deformations, including mesh-to-mesh interpolation. Techniques for managing large deformations through mesh topology adaptation. Advanced methods for dynamic mesh handling, such as sliding interfaces, overset meshes, and immersed boundary techniques.
Multiphase Flow Simulations: Fundamentals of Eulerian–Eulerian approaches, diffused interface (pseudo fluid) and interface capturing (VoF) approaches. Simulation of dispersed phases using Lagrangian particle tracking. Introduction to liquid film modeling: tracking of wall film formation and phase change process.
Conjugate Heat Transfer: Multi-region modeling strategies for heat transfer problems involving multiple materials and fluid systems. Integration with structural analysis to assess mechanical stress and thermal effects.
Reacting Flows: Simulation methodologies for chemical reactions within fluid flows, including both homogeneous and heterogeneous processes. Introduction to combustion and catalytic reaction modeling in CFD environments.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam will consist of a project assessment which will be carried out in groups of three students. The project is the same for all the students and is valid for a single academic year. All the groups are required to submit the report about the project by two days before the official date of the exam. The development of the project will prove that the student has learned how to discretize a system of partial differential equations into a set of discretized equations and how to solve them checking consistency, stability and convergence.
All the students will be required to discuss the project in the frame of an oral group presentation, during which the teacher will ask questions related to modeling aspects learned during the course. Students will show that they can discuss the results obtained at the light of the approximations and choices they have done during the development of the project. The final mark will be the summation the two parts of the exam: project and oral presentation.

J. H. Ferziger, M. Peric, Computational Methods for Fluid Dynamics, Editore: Springer, Anno edizione: 2002
H. K. Versteeg, W. Malalasekera, An introduction to computational fluid dynamics: the finite volume method, Editore: Longman, Anno edizione: 1995
A. Onorati, G. Montenegro, 1D and Multi-D Modeling Techniques for IC Engine Simulation, Editore: SAE International, Anno edizione: 2020

Questo corso introduce l'uso di OpenFOAM come strumento per risolvere problemi di fluidodinamica computazionale (CFD) su un'architettura di calcolo ad alte prestazioni (HPC). Il corso fornisce una breve introduzione alla CFD e insegna come utilizzare il framework open source OpenFOAM in un ambiente Linux. L'obiettivo del corso è di essere in grado di sfruttare le funzionalità HPC per il calcolo scientifico.
Lo studente imparerà a utilizzare, programmare e personalizzare il software CFD OpenFOAM, con un'enfasi sulle prestazioni di calcolo parallelo.
Il corso consiste in un mix di lezioni e sessioni pratiche al computer in cui gli studenti implementeranno alcuni esempi sotto la guida del docente.
L'obiettivo complementare del corso è quello di promuovere capacità di problem-solving, lavoro di squadra e comunicazione dei risultati ottenuti.

The aim of the course is to provide the basic concepts of nonlinear mechanics to approach the modeling of materials at small length scales, even in multi-physics environments.
The main topics that will be illustrated in the lectures are:
Numerical methods, with particular reference to the finite element method for nonlinear problems.
Constitutive modeling of materials with examples for metals and metal alloys, polymers, ceramics, and composite materials. Constitutive formulation for elastic-plastic material response, brittle and ductile damaging, cohesive laws for fracture phenomena.
Nonlocal approaches to plasticity and damage mechanics.
Part of the lectures will be devoted to explaining how deep learning can be exploited, e.g. to understand the links between the microstructure and the material behavior.

Lectures and hands-on sessions will allow students to:
Analyze and understand the role of nonlinearities in a continuum mechanics frame. (DdD1)
Understand the assumptions and requirements associated with the development of a finite element code. (DdD1)
Define the proper strategy to solve the problem, either in statics or dynamics. (DdD2)
Set the proper identification and validation activities/benchmarks, needed to ascertain the correctness of the mathematical frame and of its implementation. (DdD2)
Workshops will allow the students to understand how artificial intelligence tools like machine learning and deep learning can be used in order to learn the overall effects of the microstructure on the statistics of the response of the materials.

In details, the following topics will be introduced:
Nonlinear continuum mechanics: analysis of motion, deformation gradient; measures of deformation (Green-Lagrange and rate of deformation tensors); relationship between Green-Lagrange and rate of deformation tensors; pull-back and push-forward operations; measures of stress (Cauchy, nominal, first and second Piola-Kirchhoff tensors); conservation laws.
Updated and Total Lagrangian approaches: governing equations, strong/weak forms.
Total Lagrangian approach: finite element formulation.
Time integration procedures.
X-FEM: the eXtended Finite Element Method
Linear and nonlinear elasticity and visco-elasticity; elasto-plasticity.
Thermo-elasticity and continuum thermodynamics.
Deep learning for materials mechanics.
During the workshops, illustrative examples on micro- and nano-structures (MEMS and NEMS, carbon nanotubes, graphene sheets) will be illustrated, dealing e.g. with:
Nonlocal continuum damage mechanics; coupled space-time multi-scale analysis of composite delamination.
Multi-scale analysis of quasi-brittle fracture in polycrystalline materials.
Coupled thermo-mechanical analyses.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
A teamwork will be provided based on the lessons learned during the workshops; the relative assignment will be given each year for a specific problem to solve with AI-based methodologies.
A final oral examination will be also possible, about the course topics. The student will be asked to propose on his/her own one specific topic to work on; upon agreement with the examiner, the student will have to critically organize the discussion into a presentation, to be publicly delivered.
The student has to critically discuss the proposed topic, highlighting the relevant hypotheses and assumptions, and their physical meaning.

Ted Belytschko, Wing Kam Liu, Brian Moran and Khalil Elkhodary, Nonlinear Finite Elements for Continua and Structures, Editore: Wiley, Anno edizione: 2013
Ellad B. Tadmor, Ronald E. Miller and Ryan S. Elliott., Continuum Mechanics and Thermodynamics, Editore: Cambridge University Press, Anno edizione: 2012, ISBN: 9781107008267
Iddo Drori, The Science of Deep Learning, Editore: Cambridge University Press, Anno edizione: 2022, ISBN: 1108835082
Shaofan Li and Gang Wang, Introduction to Micromechanics and Nanomechanics, Editore: World Scientific Pub., Anno edizione: 2008, ISBN: 109812814132
Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning, Editore: MIT Press, Anno edizione: 2016 https://www.deeplearningbook.org/

This is a course about exploring random systems using computer simulations. Indeed, almost every mathematical model describing systems or phenomena of interest is hampered by uncertainties, although very often uncertain features or inputs are not accounted for.
The goal of the course is to introduce computational tools aiming at: (i) describing uncertainty sources in general systems, with special emphasis on differential models, and (ii) analyzing the impact of uncertainty on systems ’ outcomes, in terms of both uncertainty propagation from inputs to outputs, and input parameter estimation from noisy observations. A wide range of additional techniques enabling uncertainty quantification for complex problems will also be considered such as, e.g., surrogate models, reduced-order models for differential problems, multi-fidelity and neural network-based strategies, data-driven dynamical systems, thus providing also a general introduction to recent paradigms in scientific machine learning.

Both versions of the course have the following common learning goals:

• At the end of the course students are expected to be able to simulate statistical models - and run with Python - computational experiments aimed at: describing possible sources of uncertainty, quantifying the impact of uncertainty on numerical models, sampling from distributions of quantities of interest involving the simulation of physics-based models, applying Monte Carlo methods and their extensions, performing parameter estimation, building surrogate or reduced-order models by handling neural network-based or GP regression models.
• Leveraging on their engineering forma mentis and on the skills in computational statistics acquired in the course, students are expected to be able to evaluate the practical and statistical significance of the outcome of their numerical simulations, to quantify its uncertainty, and to propose efficient and reliable strategy to reduce computational complexity.
• Students are expected to be able to communicate and transfer the results and interpretations of their computational experiments using effective graphical or analytical means, suitable for the problem at hand and the findings of the analysis.
  Moreover, the students of the 8 CFU version of the course are expected to have a basic understanding of further topics related with data assimilation, sensitivity analysis, and data-driven dynamical systems.

The course is organized in a series of lectures that also include practical lab sessions. Lectures will provide the theoretical background; practical Lab sessions will provide algorithms' implementation and examples of application of the considered methodologies by using Python codes.
Part 1. Monte Carlo methods & Stochastic Simulation
Generating random samples from simple distributions (inversion method, transformations), acceptance-rejection sampling.
Generating random fields. Karhunen-Loève expansion.
Monte Carlo methods
Variance reduction techniques: antithetic variables, importance sampling, control variates, stratification, latin hypercube sampling.
Quasi Monte Carlo methods
Part 2. Surrogate models & Scientific Machine Learning
Dimensionality reduction: singular value decomposition
Gaussian processes & GP regression
Neural Networks (e.g., autoencoders & variational autoencoders)
Projection-based & deep learning-based Reduced Order Models
Data-driven Dynamical Systems: dynamic mode decomposition, sparse identification of nonlinear dynamics, extensions
Part 3. Sensitivity analysis & forward Uncertainty Quantification
Sensitivity analysis of multiple parameters: one-at-a-time, elementary effect methods, variance-based methods. Nonparametric methods.
Uncertainty propagation through Monte Carlo methods. Application to differential models.
Multi-level Monte Carlo and multi-fidelity Monte Carlo methods
Part 4. Data assimilation & inverse Uncertainty Quantification
Statistical inverse problems: a Bayesian setting for parameter estimation.
Monte Carlo Markov Chain methods. Application to differential models.
Data assimilation: Gaussian Filtering (Kalman filters, extensions, particle filters). Application to differential models.
Dynamic Bayesian Networks. Predictive Digital Twins

Prova orale obbligatoria
The oral exam covers the content of both theoretical lectures and practical Lab sessions, according to the sizing (5CFU/8CFU) of the course.
During the exam, students are required to present the detailed solution of two selected assignments (among a list of assignments proposed during the practical Lab sessions), commenting both the numerical results obtained and the computational procedures employed, and to answer to theoretical questions related with the topics of the course.
Assignments will require students to apply, adapt, or extend some of the methods presented during the course to selected case studies. The assignments will be evaluated during the oral examination and must be submitted to the examiners by the deadline communicated during the classes.
Theoretical questions will assess students' knowledge of the methodologies covered throughout the course. During the examination, students will first be required to sketch written answers to the theoretical questions, before presenting and discussing them with the examiners.
In the 5+3CFU form, a n additional assignment has to be carried out, which might also take the form of a critical analysis of a recent scientific paper related to the course's topics.
The course will be based on a selection of chapters of the following books, class notes, and some selected scientific papers provided:

Ralph C Smith, Uncertainty Quantification: Theory, Implementation, and Applications, Editore: SIAM, Anno edizione: 2013
Steven L. Brunton, J. Nathan Kutz, Data-driven Science and Engineering. Machine Learning, Dynamical Systems, and Control, Editore: Cambridge University Press, Anno edizione: 2022
Jochen Voss, An Introduction to Statistical Computing. A Simulation-based Approach, Editore: John Wiley & Sons, Anno edizione: 2014
Andreas Krause, Jonas Hubotter, Probabilistic Artificial Intelligence arXiv:2502.05244
Mark Asch, Marc Bocquet, Maelle Nodet, Data Assimilation. Methods, Algorithms, and Applications, Editore: SIAM, Anno edizione: 2016
Kevin P. Murphy, Probabilistic Machine Learning: An introduction, Editore: MIT Press, Anno edizione: 2022 http://probml.github.io/book1

Modern computer systems routinely process high-value information, including financial and personal data, economic transactions, and intellectual property. At the same time, they are increasingly pervasive, continuously available, and interconnected, making information security a major engineering challenge.
Security engineering is the discipline of designing and building secure systems. It is inherently interdisciplinary, combining cryptography, software engineering, network security, and political and social considerations.
This course provides a broad introduction to cybersecurity and to the methods used to design, validate, and ethically test security mechanisms. Lectures examine the main components of computer and information systems, with particular attention to their security subsystems. Students will analyze vulnerabilities, understand how they can be exploited, and learn how to prevent similar design and implementation errors.

Expected learning outcomes
Knowledge and understanding
Students will acquire broad knowledge of fundamental security technologies, their limitations, and common vulnerabilities and exploitation techniques.
Applying knowledge and understanding
Students will be able to identify and assess basic security issues in systems, networks, and applications; evaluate and improve proposed solutions; design high-level solutions to security problems; exploit simple application vulnerabilities in controlled environments; and develop basic patches.
Making judgements
Students will be able to comparatively evaluate security threats, vulnerabilities, mitigation mechanisms, and alternative solutions; reason about trade-offs; and assess risks in realistic scenarios.
Communication
Students will use appropriate terminology to explain security issues and justify security choices clearly.
Lifelong learning skills
Students will be able to update their knowledge independently and apply risk and security assessment principles to complex systems, including non-digital contexts.

1. Introduction to Information System Security

• Security properties (confidentiality, integrity, and availability), threats, attacker models, and security-engineering methodology.
  2. Fundamentals of cryptography
• Overview of cryptographic primitives (symmetric and asymmetric ciphers, signature schemes, message authentication codes, cryptographic hashes) and summary of their functionality
  3. Authentication, authorization, and access control
• Authentication and authorization mechanisms; discretionary (DAC), mandatory (MAC), and role-based (RBAC) access-control models.
  4. Application and web security
• Software exploitation: buffer overflows (in-depth) and other memory-corruption vulnerabilities (concepts, e.g. format string bugs, Return-Oriented Programming, Return to Lib C), stack protections, and mitigations (*)
• Web application security: major OWASP vulnerability classes, including injection and broken access control, with their exploitation and mitigation (*)
  5. Network security
• Stateful and stateless packet filtering
• Software-Defined Networking (SDN) and its security implications
  6. Malware
• The evolution of malware
• Botnets and the underground economy (essential concepts)
• Malware analysis
• Anti-analysis techniques
• Rootkits
• Mobile malware (essential concepts only)
  The course follows a strong hands-on approach. Practical exercises are provided for all topics marked with (*) in the syllabus. A virtual hacking lab allows students to practise exploiting and securing computer applications in a controlled environment.
  The course complements, rather than replaces, dedicated cryptography courses such as “095947 - CRYPTOGRAPHY AND ARCHITECTURES FOR COMPUTER SECURITY”. The overlap with these courses is minimal.
  The course also provides the foundation for the more advanced security courses “056896 - OFFENSIVE AND DEFENSIVE CYBERSECURITY” and “062113 - HUMAN AND PHYSICAL ASPECTS OF SECURITY”.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The assessment consists of a mandatory written test, graded out of 34 points, and, at the instructor’s discretion, a confirmatory oral test.
The written test consists of open questions and exercises that require students to apply theory and reasoning to use cases, code samples, network diagrams, and similar material. Students may answer in English or Italian. A large collection of past exams, many with solutions, is available on WeBeep.
The written test is graded on a 34-point scale. A score below 12 points is a failing grade («riprovato») under the exam regulations, and the student is not admitted to the following exam call. When required, the oral test is confirmatory and is used to verify the written-test result.
Optional homework and challenges, including activities in the virtual hacking lab, are intended solely for practice and self-assessment. They do not contribute additional points to the final grade. The maximum grade, including cum laude, can be obtained from the written test alone.
The written test is closed-book. Students may not consult course materials, notes, or other aids, and electronic devices are prohibited. Using or accessing unauthorized materials or devices, or communicating with other students, results in immediate removal from the exam and exclusion from the following exam call.
Type of assessment
Description
Dublin descriptor
Written test
Exercises requiring the analysis or design of security solutions for proposed use cases, including the exploitation of specific vulnerabilities. Graded out of 34 points; a score below 12 is a failing grade («riprovato») under the exam regulations.
1, 2, 3, 4, 5
Oral test (confirmatory)
Held at the instructor’s discretion to verify and confirm the result of the written test.
1, 2, 3, 4, 5

Dieter Gollmann, Computer Security - 3rd edition, Editore: Wiley, Anno edizione: 2011, ISBN: 978-0-470-74115-3
Note: It is vital that you get the 3rd edition if you choose this book!
William Stallings, Lawrie Brown, Computer Security: Principles and Practice, Editore: Pearson
Ross Anderson, Security Engineering, Editore: Wiley, ISBN: 0-471-38922-6 http://www.cl.cam.ac.uk/~rja14/book.html
The Joy of Cryptography by Mike Rosulek https://joyofcryptography.com/
Note: An introductory cryptography textbook (freely available)
C. Anley, J. Heasman, F. Linder, G. Richarte, The Shellcoder's Handbook, Editore: Wiley
M. Howard, D. LeBlanc, Writing Secure Code, Editore: Microsoft Press
M. Mitchell, J. Oldham, A. Samuel, Advanced Linux Programming
Note: Chapter 10

063452 - CONTROL VALVES TECHNOLOGY
Control valves are a crucial component in fluid management for industrial systems. By the end of the course, students will be able to:
Understand the fundamental role of control valves in the management of fluids within complex industrial systems.
Analyse the principles of fluid mechanics as applied to control valves, with a focus on different configurations and industrial applications.
Characterize valves from a fluid dynamic perspective, identifying and interpreting critical phenomena such as cavitation and noise generation.
Apply theoretical knowledge through laboratory work and practical simulations to effectively select and size devices for the design and management of pressurized industrial systems.
Develop design and decision-making skills in selecting control valves for fluid systems, integrating the multidisciplinary aspects that contribute to the selection of control valves.
These objectives will be achieved through the strong and proactive collaboration with key INDUSTRIAL PARTNERS that actively support the course:

• ATV-Advanced Technology Valve S.p.A. ( www.atvspa.com );
• PIBIVIESSE S.r.l. ( www.pibiviesse.it );
• PROCONTROL S.r.l. ( www.procontrolsrl.com );
• SAMSON S.r.l. ( www.samsongroup.com )
• WOOD PLC ( www.woodplc.com )
• GALLI&CASSINA S.p.A. ( www.gallicassina.com )
  The course is projected using innovative didactic strategy (“Didattica Innovativa corso in co-tutela con aziende”). The Academic staff and industrial partners will share their expertise with the students and they will be engaged during the development of the students’ activity. In this way, the theoretical approach by the teacher, is combined directly with activities supported by Managers, Engineers and External technicians by partners.

Knowledge and ability in understanding:
recognize and define the basic features of control valves
know a variety of approaches to quantify and control the performace of control flow devices
understand the role of design and management of a control valve
Ability in applying knowledge and understanding:
Use engineering tools for data analysis aimed at the selection and optimization of control valves;
Apply a semplify models for the simulation and analysis of fluid dynamic processes.
Perform analyses of key and critical processes in the control of fluid dynamic processes.
Making judgments:
In selecting appropriate models and assumptions for the effective management and control of fluid dynamic processes;
In evaluating the characteristics of control valves to support their proper selection;
In assessing the reliability of experimental tests for evaluating both normal and critical operating conditions of control devices.
Communication skills:
managing and restitution of project/experimental activity
Learning ability:
managing group work

This course offers an in-depth overview of control valves and their application in fluid dynamics and process control. It begins with fundamental concepts and a classification of valve types, distinguishing between linear and rotary designs.
Students learn basic sizing techniques for both liquids and gases, using key equations and interactive sizing software. The course also explores valve flow characteristics, system interaction, and valve positioning.
Advanced topics include cavitation and flashing, noise prediction (hydrodynamic and aerodynamic), and actuator types and principles. The connection between valves and process dynamics —such as control loops and optimization—is also examined.
Hands-on laboratory sessions allow students to characterize valves, observe cavitation and flashing, and perform advanced analyses of control processes. Practical exercises focus on valve sizing for various flow conditions and mapping performance curves.
Overall, the course blends theoretical knowledge with practical experience, enhanced by the involvement of industrial partners from the valve sector, to equip students for real-world challenges in valve selection, design, and process integration.

Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will present the laboratory activities carried out during the course, followed by an oral exam assessing their work and understanding of the course material

The course aims at describing the main corrosion phenomena on metals in contact with natural (soil, atmosphere, water) and industrial environments. The students will be able to make a corrosion assessment, evaluating the maximum expected corrosion rate and making a proper material selection for a specific application as a function the environmental aggressiveness and operation condition. Among the several available protection techniques, cathodic protection will be described in details.
During the course, a corrosion real case will be proposed. Students, divided into groups of maximum 10 persons, will be asked to make a corrosion assessment, define the cause of corrosion or indicate a proper protection system to assure a safe use in operating condition. At the end of the course, any group has to write a technical report on the proposed subject. In the last day of lessons, some groups (maximum 6) will be asked to present their work in classroom.

Lectures, numerical exercises and practical examples will allow the student to (DdD1 - DdD2):

• define, for each environment, the parameters necessary to evaluate the corrosion rate
• know the possible forms of corrosion of a metal in contact with a specific environment
• make a corrosion assessment, discussing on the possible cause of corrosion, estimating the corrosion rate
• discuss and select a proper metal or a proper protection technique for a specific application
• know the cathodic protection systems and select a proper plant for a real structure
  The project work will allow students to (DdD2 - DdD3):
• discuss in a team on a real corrosion problem, stimulating the student's ability to develop autonomous knowledge of the subject
• address and critically discuss problems and situations also other than those faced during the lessons
• find a suitable remedy to the damage, using applicable technical standards
• write an organised technical report, in which the cause of corrosion and/or the application of a protection system are described

The course is taught in the first emi-semester and it deals with the following topics.
Basic principles of corrosion (outline). Electrochemical mechanism. Thermodynamic and kinetic aspects.
Corrosion and protection of metals in natural environments (related issues: main forms of corrosion, causes of corrosion, evaluation of corrosion rate, use of corrosion prevention systems, metals most used and specific corrosion issues). Atmosphere: effect of pollutant, RH, temperature. Soil: soil composition, stray current, differential aeration, SRB. Fresh water and seawater: indexes, scaling power, hardness, conductivity.
Corrosion and protection of metal in Oil & Gas industry. Off-shore and on-shore, oil and gas production and transportations, CO2 corrosion, H2S corrosion, erosion-corrosion. Corrosion in industrial boiler.
Cathodic protection. Galvanic and impressed current systems, anodic materials, feeding system, design and monitoring.
A project is integral part of the course. The aim of projects is to help students in using the approaches and principles tough during the course. Projects will be assigned in the first weeks of the emi-semester. The final report is expected to be released at a fixed deadline. Some intermediate revison processes will be scheduled. Some groups will present and discuss their report in classroom at the end of the emi-semester.

Prova scritta obbligatoria, con prove in itinere
Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation will be carried out by a written exam.
An intermediate written exam will be scheduled at the end of the emi-semester of lessons, during the week of lesson suspension according to the official academic calendar.
The written exam consists of multiple choice questions, open questions and numerical exercises. Aim of the written exam is to verify the student ability to know the corrosion issues of metals in real working conditions and to verify if the student is able to make a proper corrosion assessment, estimating the corrosion rate, evaluating the residual service life or applying cathodic protection as main preventative or protection methods. Exams during the official dates are organized in the same way.
The maximum score of the written exam of the module "Corrosion Engineering" is 28/30. The written exam is passed even if the obtained score is 14/30.
The project laboratory report will be evaluated based on the proper corrosion assessment, the definition of the cause of corrosion and the proposal of a correct remedy. Structure of the report and clarity of exposition will be considered, too. The maximum score of the project laboratory report is 4/30. This score is sum up to the written exam score.
The oral exam is optional and can be scheduled only after a successful written exam. With the oral, a maximum increase of 3 points can be obtained. If the oral is not satisfactory, the score can be reduced.

Pietro Pedeferri, Corrosion Science and Engineering, Editore: L. Lazzari, M. Pedeferri, Anno edizione: 2018, ISBN: 978-3-319-97625-9
Dispense del corso
L. Lazzari, P. Pedeferri, M. Ormellese, Cathodic Protection, Editore: PoliPress, Anno edizione: 2008

This course aims at providing the fundamentals of creative thinking and its stimulation in order to optimize the use of natural resources (raw materials and energy) in design and decision making activities. To this purpose, the course includes the execution of exercises and other design activities that require the application of methods, tools and techniques for the analysis of technical problems and the synthesis of solutions. These will be generated by means of a holistic approach that considers the relationship between the technical solution and other social/biological/technical systems and aims at minimizing the potentially harmful effects on the environment during the whole life cycle of the solution.

Theoretical and practice lectures will make it possible to:
Remember and Understand:
The creativity metrics;
The constructs of modelling techniques for the representation of products and processes in their life cycle;
The phases of a Life Cycle Assessment;
The approaches for problem reformulation and the identification of design solution opportunities;
Heuristics for the creative solution to technical problems of sustainability;
The primary sources of creative stimulation and their intrinsic organization
Apply, Analyse, Evaluate and Create:
Analyse an industrial context of reference to define challenges and objectives for environmental sustainability;
Evaluate their own design processes to estimate the effectiveness and the efficiency of creative thinking;
Analyse existing/competing solutions' environmental impact along their life cycle for the identification of problems of environmental sustainability that require creative solutions;
Analyse technical problems and create alternative formulations of the same for the identification of more convenient and environmentally sustainable solving strategies;
Evaluate the relevance of multiple sources of inspiration to stimulate the creative generation of original solutions;
Apply problem-solving heuristics to create solutions that overcome the analysed problems of environmental sustainability.

Approaches to highlight problems of environmental sustainability (Definition of sustainability, sustainable development goals and related targets; Linear to Circular economy transition – Identification of supply chain development opportunities; Life Cycle Assessment (LCA) for the identification of environmental problems; Life Cycle Assessment (LCA) to compare competing solutions)
Technological opportunities (materials and processes) for the development of more sustainable solutions (Eco-profiles of raw materials of industrial relevance; Sources of information and selection criteria for raw materials; Manufacturing processes and related environmental impacts; Sources of information and selection criteria for manufacturing processes)

Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The course is organized into theoretical and practice lectures that also include co-creative sessions to address simple design topics of industrial relevance. The theoretical lectures present all the topics of the course. The practice lectures enable the application of the contents taught during the theoretical lecture to practical problems of industrial relevance for in-class activities, both individually and in teams. The evaluation of the achievement of the intended learning outcomes will require the execution of a group project, where the team members will need to play a variety of design roles.

M. F. Ashby, Materials and the Environment. Eco-informed material Choice, Editore: Elsevier, Anno edizione: 2021, ISBN: 978-0-12-821521-0

Il corso fornisce una formazione sistematica sui moderni meccanismi crittografici utilizzati per le comunicazioni e la memorizzazione dei dati. Il corso si focalizza sugli algoritmi e le relative implementazioni efficienti in Software e Hardware, non trascurando l'indicazione di nuovi approcci e critto-sistemi innovativi. Saranno presentati gli aspetti matematici della crittografia moderna, preceduti dalle nozioni essenziali della teoria dei campi di Galois. La sicurezza dei più importanti critto-sistemi sarà analizzata anche dal punto di vista della loro realizzazione, presentando le vulnerabilità a cui i dispositivi Hardware e Software possono essere soggetti. Infine, verranno presentati i protocolli di comunicazione sicura più comuni (SSL/TLS, SSH, PGP, Kerberos, Onion Routing) e i protocolli per la memorizzazione di dati cifrati.

Cyber-physical systems support manufacturing companies in strategic decisions. Digital models (as Digital Twins, or Digital Shadows) of production systems represent an important component of cyber-physical manufacturing systems since they are the digital counterparts of physical manufacturing systems. Moreover, they follow the life cycle and provide a kernel to be used for decision support in operational, tactical and strategical decisions involving the inter-relations among quality, maintenance and production logistics aspects. The course provides a framework, quantitative methods and relevant competencies to support the design, implementation and use of cyber-physical manufacturing systems according to available information sources, actual production data and identified objectives. Digital methodologies including hybrid modelling, data analysis, data formalization will be studied and applied according to the characteristics of manufacturing systems and relevant assumptions. The course has a strong industrial focus by means of analysis of real cases from various manufacturing applications.

The main expected learning outcomes of this course are:
Students will understand and be able to integrate information from various sources and of various type to model a manufacturing system with the correct digital model
Students will be able to demonstrate how to address and solve different types of manufacturing problems related to operational, tactical and strategical decisions
Students will be able to analyze real industrial cases with respect to identified problems, target objectives and selected methodologies.

Introduction
Introduction to the concept: product, process and system Digital Twins/Shadows
Scope of cyber-physical manufacturing systems: objectives and manufacturing problems
Methodologies
Part a: Digital methodologies for cyber-physical manufacturing systems
Requirements on production data and data modelling
Model-based generation of system models integrating data and company knowledge
Overview of methodologies for system-level Digital Twins
Management of Digital Twins in the context of extreme data
Virtual commissioning and rapid ramp-up of manufacturing systems
Part b: Cyber-physical manufacturing systems using the Digital Twin
Integrating resource-based Digital Twins in cyber-physical manufacturing systems
Cyber-physical systems for integrated quality, maintenance and logistics decisions
Optimization of strategic decisions on system reconfiguration and operations
Other (inter-disciplinary) aspects
Challenges from the integration of information sources. Hints of information repositories (PLM, MES, ERP)
Challenges on versioning and updates of the DT
Practical activities
Analysis of real industrial cases
Development of model-based Digital Twins from available data
Lab activities on using Digital Twins for developing cyber-physical systems for quality, maintenance and logistics

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The evaluation is based on a team project (50% of the final grade), to be done during the course, and on an oral exam (50% of the final grade). The project consists in the design and implementation of the architecture of a cyber-physical manufacturing system: the students will be provided a system-level Digital Twin, a real manufacturing system as continuous data source and they will focus on the decision support system to operate the manufacturing system.

Cyber-physical systems support manufacturing companies in strategic decisions. Digital models (as Digital Twins, or Digital Shadows) of production systems represent an important component of cyber-physical manufacturing systems since they are the digital counterparts of physical manufacturing systems. Moreover, they follow the life cycle and provide a kernel to be used for decision support in operational, tactical and strategical decisions involving the inter-relations among quality, maintenance and production logistics aspects. The course provides a framework, quantitative methods and relevant competencies to support the design, implementation and use of cyber-physical manufacturing systems according to available information sources, actual production data and identified objectives. Digital methodologies including hybrid modelling, data analysis, data formalization will be studied and applied according to the characteristics of manufacturing systems and relevant assumptions. The course has a strong industrial focus by means of analysis of real cases from various manufacturing applications.

The main expected learning outcomes of this course are:
Students will understand and be able to integrate information from various sources and of various type to model a manufacturing system with the correct digital model
Students will be able to demonstrate how to address and solve different types of manufacturing problems related to operational, tactical and strategical decisions
Students will be able to analyze real industrial cases with respect to identified problems, target objectives and selected methodologies.

Introduction
Introduction to the concept: product, process and system Digital Twins/Shadows
Scope of cyber-physical manufacturing systems: objectives and manufacturing problems
Methodologies
Part a: Digital methodologies for cyber-physical manufacturing systems
Requirements on production data and data modelling
Model-based generation of system models integrating data and company knowledge
Overview of methodologies for system-level Digital Twins
Management of Digital Twins in the context of extreme data
Virtual commissioning and rapid ramp-up of manufacturing systems
Part b: Cyber-physical manufacturing systems using the Digital Twin
Integrating resource-based Digital Twins in cyber-physical manufacturing systems
Cyber-physical systems for integrated quality, maintenance and logistics decisions
Optimization of strategic decisions on system reconfiguration and operations
Other (inter-disciplinary) aspects
Challenges from the integration of information sources. Hints of information repositories (PLM, MES, ERP)
Challenges on versioning and updates of the DT
Practical activities
Analysis of real industrial cases
Development of model-based Digital Twins from available data
Lab activities on using Digital Twins for developing cyber-physical systems for quality, maintenance and logistics

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The evaluation is based on a team project (50% of the final grade), to be done during the course, and on an oral exam (50% of the final grade). The project consists in the design and implementation of the architecture of a cyber-physical manufacturing system: the students will be provided a system-level Digital Twin, a real manufacturing system as continuous data source and they will focus on the decision support system to operate the manufacturing system.

The course aims at providing all of the basic skills and knowledge required to effectively design and construct an electric motor. The objectives are highly interdisciplinary because they deal with a number of different physical and engineering aspects, namely, defining the magnetic circuit and magnetic field sources, defining the mechanical architecture referring to strength, compliance, thermal aspects and basic feasibility. The engineering aspects are made rigorous by deriving the optimal solutions in the Pareto sense. Particular attention is devoted to the design and construction of automotive motors. The course aims at highlighting an ever-occurring paradigm within automotive engineering that a single component requires almost all of the competences that are needed to design the whole vehicle. The course aims also to show to the students the importance of competences pertaining to other specialized courses, either electrical or mechanical, addressing the design and construction of electric motors.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
The students will acquire knowledge and understanding on
-how electric motors are conceived
-how windings and/or magnets are placed into an electric motor
-the importance of an efficient magnetic circuit
-winding a stator
-how performing a preliminary design of an electric motor
-how dealing with strength problems
-how dealing with compliance problems
-how dealing with basic construction engineering problems
-how dealing with thermal problems
-how dealing with noise problems
-how optimizing the whole motor by means of multi-objective programming
Concerning the ability to apply the acquired knowledge and understanding, students will be able to
-choose the proper electric motor as function of the required mission (traction, brake actuation, servo-actuators...)
-complete and analyse the design of an electric motor
-apply multi-objective optimization to find optimal solutions for electric motors with respect to a given mission
Through a real design case study, the students will also acquire the skills to formulate a judgment, meaning to define a technical specification, find autonomously the problem input data, apply proper models, perform a critical analysis of the obtained results and explain them. They will also acquire the ability to discuss in a team the proposed design.
Furthermore, through the assigned case study, students will gain the ability to autonomously
-define models of different complexity, with the objective of obtaining a suitable trade off between the accuracy of the solution and the required computational cost
-evaluate the benefits of the design optimisation and propose new solutions
-critically discuss their project and propose improvements that they assume necessary to limit the effect of the simplifications introduced for didactic constraints
Finally, students will improve their communication skills, being able to write reports presenting the developed projects. In particular, the students are requested to prepare their reports addressing the following issues
define a design specification
describe the theoretical background of the applied methods
explain the assumptions, approximations introduced and their impact on the results
show the relevant results
highlight the impact of the optimisation methods learned in the course on the final design, with respect to a traditional design approach.

The course contents are delivered through lectures and exercises.
The course covers the following topics divided in modules
1 Electric motors
General aspects: sizing equations, magnetic topologies and torque components
Windings for a.c. rotating machines.
PM modelling and design criteria.
Cage rotor induction machines: design criteria and performance evaluation.
Synchronous machines: wound rotor types, surface mounted and interior PM dispositions: performances, field weakening, efficiency.
Optimal design
Basic principles of multi-objective optimisation.
Definition of objective functions and design variables for electric motors design.
Pareto sets in both the design variables and objective functions domains.
Optimisation methods.
Construction phase (basics).
Optimal design and construction of automotive electric motors
Design for strength: materials and related mechanical properties for structural health, Design for compliance: FEM models of stator and rotor, effects of rotation, Design for thermal efficiency, basic applications, Design for noise emission, basic schemes for airborne and structure-borne harshness.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully take an oral exam on theoretical questions which includes the discussion of the submitted report describing the solution of the case study.
Number of questions
3 questions (1 on electric motors, 1 on mechanical design of electric motors, 1 on the case study)
Duration
half hour
Final Grading
To pass the course, students must successfully pass the oral test and complete the report which describes their results.
The final mark is the non-weighted mean of the marks obtained answering the questions.
Specific knowledge and skills that are checked during the exam
Knowledge on the basics of electric and magnetic circuits. Motor types. Mechanical modeling of electric motors (strength, compliance, thermal, noise problems).
Always the teacher tries to
-check whether the project has been made by the student, asking detailed questions that are easily answered if a direct involvement has occurred
-check whether the student has simply learned or understood the topics of the course
The skills that are assessed are
-ability to choose the type of an electric motor for automotive applications
-ability to design an electric motor considering at the same time electrical and mechanical issues
-ability to make judgement, referring to the performance of an electric motor
-ability to learn by combining practical and theoretical experiences

Course notes and slides https://beep.metid.polimi.it/
F. Correggiari, A. Di Gerlando, G.M. Foglia, Construction and Design of Electrical Machines (Lectures notes)
Mastinu, G., Gobbi, M., Miano, C., Optimal Design of Mechanical Systems, with application to automotive engineering, Editore: Springer, Anno edizione: 2006, ISBN: 978-3-540-34355-4 https://link.springer.com/content/pdf/10.1007%2F978-3-540-34355-4.pdf

The course provides guidelines for functional mechanical design, focusing on key issues related to industrial automatic machines.
The main objectives of the course are:
To provide knowledge of the basics of motion planning (how to design motion curves and optimize them according to different applications).
To develop an understanding of mechanisms (linkages and cams) used to transform motion.
To introduce methodologies for analyzing and synthesizing planar and spatial mechanical devices.
To provide knowledge of industrial actuators and methodologies for sizing them according to the required performance.
To introduce tools and methods for modeling complex machines and carrying out their synthesis according to application requirements.
To present criteria for evaluating the correctness of design choices.
To bring students closer to the industrial world, some topics will be addressed in collaboration with leading companies in the field.

** Knowledge and understanding
The student:

• knows the problems associated with the motion of a machine
• knows the most common mechanisms used in the industrial field for the transformation of motion and the realization of complex movements
• knows the most widespread industrial actuators and knows how to select them
  ** Ability to apply knowledge and understanding
  The student:
• can design a motion law in accordance with the requirements of the application
• can perform analysis and synthesis of the main mechanisms used in industry (cams and linkages)
• can size an actuation system for moving a machine
  ** Autonomy of judgment
  The student:
• can independently evaluate the correctness of the design choices
• can find alternative design solutions to a complex problem
• can discuss and critically support his design choices

The functional design of a mechanical system. Introduction to motion law design, motion laws, mechanisms and actuation system classification.
Motion curve. Motion curve definition for the automation industry and properties of the acceleration diagram. Motion curve adimensionalization and characteristic coefficient definition (velocity coefficient, acceleration coefficient, jerk coefficient, etc). Analysis of the principal requirements in motion curve design (maximum acceleration limit, maximum velocity limit, ecc) with reference to the basic motion curve. The improvement of motion curve (basic motion law modified and polynomial motion law). Limits to the improvement attainable.
Cam Mechanisms. Description and analysis of cam mechanisms used in the industrial automation with particular reference to the manufacturing environment by means of a selection of industrial case studies. Pressure angle definition and undercutting analysis. Kinematic analysis of cam mechanisms through the inversion of motion and equivalent mechanisms. Cam profile determination for radial cam with translating roller follower, translating flat-faced follower and with oscillating roller follower. Methodologies to reduce the cam dimensions. Contact typologies between cam and follower: force close cam joint, form close cam joint and joint with “clearance ramps”. Reference to devices capable of modifying the movements of cam mechanisms.
Linkage Mechanisms: Definition and classification of linkage mechanisms based on the number of the links (four bars mechanisms, five bars mechanisms, etc.). Kinetostatic analysis and kinetostatic duality: transmission angle and generalized transmission ratio. Kinematic analysis of a linkage mechanism by means of vector closure equation and the Newton-Raphson method (coupler curve plotting for a four bar mechanism). Introduction to methods for direct and indirect kinematic synthesis of linkage mechanisms. Reference to kinematic optimisation. Quick return mechanisms and mechanisms with delays (superimposition of the dead centres method) and force multiplier mechanisms. Introduction to compliant mehanisms.
Actuators: Electrical motors used in automation: catalogue reading and typical problems in choosing electrical motors. Motor-reducer sizing methodology: accelerating factor and load factor, transmission ratio choosing and check of motor-reduce choice. Pneumatic actuators for industrial machines: devices and design of elementary circuits.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The course consists of lectures and practical sessions, including a collaborative project.
The evaluation is based on an oral exam, which includes the presentation of a team-developed project and a discussion of theoretical topics.
The project evaluation is based on review sessions throughout the semester and the final presentation. The project work is intended to assess the achievement of the expected outcomes in terms of practical skills, learning progress, and communication abilities.

P.L. Magnani, G. Ruggieri, MECCANISMI PER MACCHINE AUTOMATICHE, Editore: Utet, Anno edizione: 1986, ISBN: 9788802040240

Il corso fornisce le competenze fondamentali per il progetto a l'analisi prestazionale della macchine a fluido per la produzione di potenza da fonti rinnovabili, con particolare riferimento alle turbine eoliche e alle macchine idrauliche. Generalità sui profili aerodinamici per macchine a fluido. Forze aerodinamiche. Triangoli di velocità per pale rotanti. Effetto dell'angolo di incidenza. Stallo. Effetto del numero di Reynolds e della rugosità. Effetti 3D. Solidità. Approcci 1D e 3D: modelli di Betz e Glauert e loro limiti. Sviluppo di due codici 3D di tipo BEM (Blade Element Momentum) per il progetto, la regolazione e l'analisi di performance di aerogeneratori ad asse orizzontale e verticale (Double Multiple Stream Tube).
(A seguire solo per 8 CFU)Estrazione di potenza dal moto ondoso: le OWC e la turbina Wells, principio di funzionamento e dimensionamento preliminare.: Le turbine idrauliche di piccola potenza. Similitudine idraulica. Turbine assiali mono e bi-regolanti, turbine ad elica e a bulbo: funzionamento a giri variabili. Diagrammi collinari. Progetto preliminare di una macchina assiale.

Main objective of the teaching are:

• To have a knowledge of most used machine in food processing, from agriculture to secondary packaging
• To understand most important drivers in the synthesis of machines for food processing
• To have basic knowledge of functional mechanical design of machines
• To know how to synthesis motion and how to transform it according to different tasks and applications
• To have a knowledge of most common actuators and drive systems in food & beverage applications

In terms of acquired knowledge and understanding, students will be able to:

• know main problems associated with machines for food production
• know the most used machines in food and beverage industrial field
• know how to obtain a working flow from raw materials to a final product, by highlighting main operations to carry out
  Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
• design the working flow from raw materials to a final product, by highlighting main operations to carry out
• design simple functional systems
• size an actuation system for moving a machine.
  Through practical design activities, students will also acquire the skills to formulate a judgment, meaning to:
• independently evaluate the correctness of the design choices
• find alternative design solutions to a complex problem
• discuss and critically support their design choices

Main topics of the teaching are:
Overview on Food Processing Machines
-Production of raw materials (agriculture, meat, dairy, …)
-Food Preparation Equipment by Unit Operation (cleaning, grading, peeling/skinning, sorting)
-Mechanical Processing Equipment for size transformation (mills, crushers, grinders, cutters, extruders, forming machines, mixers)
-Packaging machines (fillers, sealers & secondary packaging)
-Auxiliary machines (conveyors, cartoners, palletizers, etc.)
Basics of Functional mechanical design
-Task identification and definition of functional groups
-From task to motion design
-Mechanisms to transform motion
-Pneumatics and electrics motors
Basics of regulations in machine design
-EU Machinery directive
-Food & Beverage regulatory compliance
Emerging technologies in machines for food processing
-Precision farming, food robotics, domestic food production
To bring students closer to the industrial world, some themes will be treated in collaboration with industrial companies leaders in the field.
During the course, students have to develop a project in a team focused on the design of a production line.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students’ acquired knowledge and understanding will be tested during an oral test that covers all the topics of the course.
During the exam students have to present their project of an industrial production line, explaining it in a critical way.

G. Saravacos, A. E. Kostaropoulos, Handbook of Food Processing Equipment, ISBN: 978-3-319-25020-5

Digital technologies are increasingly used to support the design, operation and control of manufacturing systems. In industrial environments, effective decision-making requires models that represent the current state of the system, account for variability and uncertainty, and incorporate the interaction between human operators and digital technologies.
The course introduces methods and tools for developing and using digital models of manufacturing systems, with particular emphasis on Digital Twins and human-centred production environments. Students will learn how to represent manufacturing resources, processes, products and human activities, and how to use these representations to support monitoring, analysis and short-term operational decisions.
Within the Management Engineering curriculum, the course contributes to the development of the ability to:
analyse the functions, processes and interactions of business and industrial systems, considering their economic, environmental and social implications;
formulate and solve industrial problems using scientific and engineering methods;
integrate data, models and digital technologies to support decisions in complex manufacturing environments;
evaluate the role of human operators in digitally enabled production systems.
The course supports these programme-level capabilities through the modelling, analysis and control of human-centred manufacturing systems.

By the end of the course, students will be able to:
model the main elements and behaviour of a manufacturing system using Digital Twin concepts;
select and apply appropriate digital and AI-based methods to a manufacturing problem;
integrate models, data and software tools into a coherent application;
analyse results and assess the assumptions, limitations and industrial value of the proposed solution;
communicate the methodology and results of a technical project.
Each student will complete an individual project on one of the topics covered in the course.
The specific knowledge and technical skills developed will therefore depend partly on the selected project.
Students may exchange general methodological information and use shared software components or datasets when authorised by the instructor, but the submitted analysis, implementation, results and report must be individual.

1. Digital representations of manufacturing systems
Digital Factory, Digital Twin and AI-enabled manufacturing concepts.
Digital representation of resources, processes, products and their interactions.
Manufacturing data models, standards, ontologies and Digital Twin architectures.
Behavioural modelling, data integration and AI-supported model updating.
Use of machine learning and immersive technologies for system analysis, visualisation and operator support.
2. Modelling and monitoring human activities
Representation of human operators, human–machine interactions and manually executed processes.
Computer-vision and deep-learning methods for pose estimation, object detection and activity recognition.
Modelling and monitoring of manual operations using multimodal data.
Detection of deviations, errors and unsafe conditions in human-executed tasks.
Technical, organisational, ethical and privacy aspects of AI-based human monitoring.
3. Digital Twin-based analysis and operational control
Synchronisation between physical systems, Digital Twins and AI models.
State estimation, prediction and monitoring of manufacturing operations.
Use of Digital Twins and machine learning for simulation, forecasting and what-if analysis.
AI-supported planning, scheduling and operational decision-making.
Validation and assessment of robustness, uncertainty, explainability and industrial applicability.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, con presentazione/discussione finale
Assessment is based on:
an individual project developed throughout the semester;
a written project report and the related software or digital models;
an oral presentation and discussion of the project;
a written test covering the theoretical and methodological topics of the course.
The project will be evaluated on the basis of:
correctness and coherence of the proposed methodology;
quality of modeling hypotheses and implementation;
appropriate use and integration of digital tools;
quality of the experimental analysis and interpretation of results;
awareness of assumptions and limitations;
clarity and reproducibility of the submitted work;
quality of the oral presentation and discussion.
Weighting:
project, implementation and report: 55%;
oral presentation and discussion: 20%;
written theoretical test: 25%.

Il cybercrime è una delle minacce più significative alle infrastrutture digitali della nostra società. In questo corso analizzeremo i meccanismi, le caratteristiche e le spinte propulsive del cybercrime (inclusa l'esistenza di un'economia underground). Analizzeremo in seguito le tecniche per l'analisi forense dei dispositivi digitali (con una specifica attenzione al contesto legale italiano e due casi di studio specifici, ma con un'ampia analisi di metodologie applicabili in modo internazionale). L'analisi forense di rete e nell'ambiente cloud sarà presentata brevemente. Infine, dal momento che molti cybercriminali sono motivati dal guadagno monetario, saranno affrontate le tecnologie di individuazione delle frodi e di tracciamento dei movimenti nelle criptovalute.

This course provides the competence for designing and implementing a manufacturing digital workflow according to the Industry 4.0 principles, with specific focus on machining operations. Giving a proper theoretical background on machine tools, CAM (Computer-Aided Manufacturing) software, simulation and part verification, and applying state-of-the-art methods and tools to real machining operations is the object of this course. Industrial partners provide their hardware and software products (machine tool, tool holders, tools, fixtures, software, instruments, etc.) and their know-how to assure a perfect alignment with the industrial good practice.
The course is focused on chip removal processes (milling, turning, drilling) that are relevant for the digital approach application because of their impact, diffusion and complexity. For this reason, the presented approach can be then extended to other manufacturing processes pursuing the same objective of increased productivity, high quality and reduced consumption of resources.

In terms of acquired knowledge and understanding, by the end of the course students:
Identify each component of an industrial and digital machining workflow, describing its basic principles, standards, functions, constraints and performance
Know how to create a digital machining architecture to meet productivity, quality and sustainability constraints in industry
Concerning the ability to apply the acquired knowledge and understanding, by the end of the course students can:
Select the suitable resources (e.g. machines and tools) and process parameters to accomplish a simple/standard machining task making use of digital tools
Select the proper software tool to accomplish a certain task along the digital workflow as tool selection, machining strategy design, machine simulation
Calculate the representative quantities of the milling process applied to a specific case (e.g. force, power, material removal rate, surface finish, etc.), also using relevant software
Through the mandatory Lab Work, the students divided in groups acquire the skills concerning activity planning, problem setting, problem solving, and analytical thinking. The lab activities allow the students to apply the acquired theoretical knowledge to autonomously assess and solve manufacturing tasks. In this way, they acquire applied knowledge of Digital Machining and how to communicate the results of a manufacturing activity.

The course contents are delivered through lectures, exercise classes and lab activities. The course covers the following topics as per the description below:
Introduction of grounding concepts: machine tools, their components (axes, spindles, Computer Numerical Control (CNC), etc.) and performance (accuracy, precision, rigidity, working field). Tool holders and tools (brief classification and performance). Preliminary digital workflow definitions and functions (CAM, post-processor, G-code, etc.). Blank and fixture selection (basic principles). Examples are provided on machining centers, lathes, sliding headstock lathes and multi-tasking machines. Examples of tool selection through available industrial software will be given.
Cutting force simulation through mechanistic models and its application in process optimization for improved performance in terms of productivity, stability, quality and sustainability.
Computer-Aided Manufacturing (CAM): fundamental principles and application.
Machine simulation: fundamental principles and examples of application for the tool path verification (anti-collision), part quality prediction, feed/force optimization. Digital twin.
Process monitoring: relevant physical quantities, sensors, bandwidth, resolution and purpose.
Metrology and part verification: GD&T (Geometric Dimensioning and Tolerancing), PMI (Product Manufacturing Information), instruments, microscopes and Coordinate-Measuring Machines (CMMs). Application of optical 3D measurements to part verification, comparison with the nominal CAD model and comparison with the final part modelpredicted by simulation.
Workflow from the CAD model to CAM, post-processor, G-code, simulation, execution, monitoring, part verification.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Students pass the course after successfully passing a mandatory Lab Work and a mandatory oral exam.
Via the oral exam, it is possible to test students’ ability to autonomously form judgements and the ability to communicate learnt contents. Students should answer two main questions formulated by the professor. The oral exam gives a grade 18/30 <= Go <= 28/30. If Go < 18/30, the student fails the exam and goes to the next call.
The mandatory Lab Work can yield up to 4 additional points (Lw). Since the Lab Work is mandatory, every student is required to do it to pass the exam. The Lab Work must be submitted at the end of the course and before the first exam call according to the date declared by the professor during the course. If the Lab Work is not sufficient, the group cannot attend the first exam call and receives indications by the professor on how to fix it.
In case of absence from certain laboratory sessions, the student can retrieve the related material through the other group colleagues and/or via WeBeep. The professor considers the number of absences from the laboratories and, after consulting all group members, will decide whether to consider the requirement for the repeatedly absent student to complete the Lab Work satisfied.
The final grading formula is: Gf = Go + Lw.
Only by successfully passing the Lab Work, the maximum grade of 30 and 30 and praise can be achieved.

Lecture notes https://webeep.polimi.it/login/index.php
Note: WeBeep course website

This course provides the competence for designing and implementing a manufacturing digital workflow according to the Industry 4.0 principles, with specific focus on machining operations. Giving a proper theoretical background on machine tools, CAM (Computer-Aided Manufacturing) software, simulation and part verification, and applying state-of-the-art methods and tools to real machining operations is the object of this course. Industrial partners provide their hardware and software products (machine tool, tool holders, tools, fixtures, software, instruments, etc.) and their know-how to assure a perfect alignment with the industrial good practice.
The course is focused on chip removal processes (milling, turning, drilling) that are relevant for the digital approach application because of their impact, diffusion and complexity. For this reason, the presented approach can be then extended to other manufacturing processes pursuing the same objective of increased productivity, high quality and reduced consumption of resources.

In terms of acquired knowledge and understanding, by the end of the course students:
Identify each component of an industrial and digital machining workflow, describing its basic principles, standards, functions, constraints and performance
Know how to create a digital machining architecture to meet productivity, quality and sustainability constraints in industry
Concerning the ability to apply the acquired knowledge and understanding, by the end of the course students can:
Select the suitable resources (e.g. machines and tools) and process parameters to accomplish a simple/standard machining task making use of digital tools
Select the proper software tool to accomplish a certain task along the digital workflow as tool selection, machining strategy design, machine simulation
Calculate the representative quantities of the milling process applied to a specific case (e.g. force, power, material removal rate, surface finish, etc.), also using relevant software
Through the mandatory Lab Work, the students divided in groups acquire the skills concerning activity planning, problem setting, problem solving, and analytical thinking. The lab activities allow the students to apply the acquired theoretical knowledge to autonomously assess and solve manufacturing tasks. In this way, they acquire applied knowledge of Digital Machining and how to communicate the results of a manufacturing activity.

The course contents are delivered through lectures, exercise classes and lab activities. The course covers the following topics as per the description below:
Introduction of grounding concepts: machine tools, their components (axes, spindles, Computer Numerical Control (CNC), etc.) and performance (accuracy, precision, rigidity, working field). Tool holders and tools (brief classification and performance). Preliminary digital workflow definitions and functions (CAM, post-processor, G-code, etc.). Blank and fixture selection (basic principles). Examples are provided on machining centers, lathes, sliding headstock lathes and multi-tasking machines. Examples of tool selection through available industrial software will be given.
Cutting force simulation through mechanistic models and its application in process optimization for improved performance in terms of productivity, stability, quality and sustainability.
Computer-Aided Manufacturing (CAM): fundamental principles and application.
Machine simulation: fundamental principles and examples of application for the tool path verification (anti-collision), part quality prediction, feed/force optimization. Digital twin.
Process monitoring: relevant physical quantities, sensors, bandwidth, resolution and purpose.
Metrology and part verification: GD&T (Geometric Dimensioning and Tolerancing), PMI (Product Manufacturing Information), instruments, microscopes and Coordinate-Measuring Machines (CMMs). Application of optical 3D measurements to part verification, comparison with the nominal CAD model and comparison with the final part modelpredicted by simulation.
Workflow from the CAD model to CAM, post-processor, G-code, simulation, execution, monitoring, part verification.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Students pass the course after successfully passing a mandatory Lab Work and a mandatory oral exam.
Via the oral exam, it is possible to test students’ ability to autonomously form judgements and the ability to communicate learnt contents. Students should answer two main questions formulated by the professor. The oral exam gives a grade 18/30 <= Go <= 28/30. If Go < 18/30, the student fails the exam and goes to the next call.
The mandatory Lab Work can yield up to 4 additional points (Lw). Since the Lab Work is mandatory, every student is required to do it to pass the exam. The Lab Work must be submitted at the end of the course and before the first exam call according to the date declared by the professor during the course. If the Lab Work is not sufficient, the group cannot attend the first exam call and receives indications by the professor on how to fix it.
In case of absence from certain laboratory sessions, the student can retrieve the related material through the other group colleagues and/or via WeBeep. The professor considers the number of absences from the laboratories and, after consulting all group members, will decide whether to consider the requirement for the repeatedly absent student to complete the Lab Work satisfied.
The final grading formula is: Gf = Go + Lw.
Only by successfully passing the Lab Work, the maximum grade of 30 and 30 and praise can be achieved.

Lecture notes https://webeep.polimi.it/login/index.php
Note: WeBeep course website

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

The main expected learning outcomes for each of the following capabilities are:
1. Understand: the students will learn how the automation and digital technolgoies (i.e. Industry 4.0) are effecting the future manufacturing systems, both in the process industry as well as in the discrete manufacturing systems;
2. Identify: the students will learn how to select (i.e. identify) the best technology and the best application scenario;
3. Design: designing a manufacturing systems is a complex process which requires to deal with the hard, soft and organisational dimensions of the design of the system. Quantitative and qualitative techniques will be explained. The impact evaluation will also be assessed in order to give students the know-how on how to understand the impact of their decisions.

Part I – Advanced and Sustainable Manufacturing Strategies (9 hours)
1.1. Sustainable development: social, environmental, and economic megatrends — 3 hours
Examines the global trends reshaping industry and society, and how sustainability considerations are embedded into manufacturing strategy.
1.2. The role of manufacturing in the regional, national, and global economy — 3 hours
Analyzes how manufacturing drives economic growth, employment, and competitiveness across different geographic scales.
1.3. Manufacturing as a key enabler of Europe's societal challenges — 3 hours
Explores how manufacturing contributes to addressing major European priorities such as climate action, resource efficiency, and industrial resilience.
Part II – Digital Manufacturing in the Process Industry (9 hours)
2.1. Process control — 4 hours
Introduces the principles and tools used to monitor and regulate continuous production processes.
2.2. Control architecture typologies: monitoring, direct digital control, and supervisory control — 5 hours
Compares different levels of automation and control system architecture used in process industries.
Part III – Digital Manufacturing in the Discrete Manufacturing Industry (32 hours)
3.1. Design and management of Advanced Manufacturing Systems (AMS) — 6 hours
Covers the design principles and operational management of flexible, technology-driven production systems.
3.2. Real-time control systems: loading and dispatching approaches — 5 hours
Examines methods for scheduling and coordinating production activities in real time on the shop floor.
3.3. Introduction to industrial robots and humanoid applications in manufacturing — 5 hours
Provides an overview of robotic technologies, including humanoid robots, and their growing role in production environments.
3.4. Artificial Intelligence (AI) in manufacturing — 6 hours
Explores how AI techniques are applied to optimize processes, predict outcomes, and support decision-making in manufacturing.
3.5. Human-machine interaction — 4 hours
Studies how humans and machines collaborate effectively and safely within modern manufacturing systems.
3.6. Business case analysis (class work, seminars, etc.) — 6 hours
Applies course concepts to real-world industry cases through hands-on classroom activities and seminar discussions.

Prova orale obbligatoria
The final exam will be conducted orally. Each student will be asked a series of questions covering the topics addressed throughout the course, and will be expected to answer clearly and demonstrate a solid understanding of the material, including the ability to connect concepts across different parts of the syllabus. The exam typically lasts between 30 and 45 minutes per student, depending on the depth of the answers given. Students should be prepared to discuss theoretical concepts, provide examples, and, where relevant, work through problems or reasoning aloud. The final grade will reflect not only the accuracy of the answers but also the clarity of exposition and the ability to reason critically about the subject matter.

This course aims to equip students with the knowledge and practical skills necessary to leverage Extended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), in various engineering domains.
Through a combination of theoretical instruction and hands-on projects, students will explore how XR can enhance engineering processes, improve engineering design accuracy, and foster innovation in product development, and how XR can facilitate the creation and manipulation of Digital Twins for real-time data visualization and analysis.

After completing the course, students will have acquired a thorough understanding of XR technologies, knowledge of the hardware and software components required for developing XR applications, skills in integrating XR technologies into engineering workflows to enhance design, visualization, and simulation processes, experience in applying learned concepts, methods and techniques to hands-on projects addressing engineering challenges, fostering teamwork and problem-solving abilities.

Understand XR Technologies: Gain a thorough understanding of XR technologies, including VR, AR, MR, and virtual worlds, and their potential applications in engineering. Explore the hardware and software components required for developing XR applications.
Integrate XR with Engineering Workflows: Learn how to incorporate XR technologies into engineering workflows to improve design, visualisation, and simulation. Analyse the impact of XR on enhancing collaboration and communication among engineering teams.
Apply XR in Product Development: Explore the role of XR in the lifecycle of product development, from conceptual design and prototyping to testing and maintenance.
Develop XR Applications: Acquire practical skills in developing XR applications tailored to specific engineering needs, for example, Virtual Commissioning. Use XR development tools and platforms such as Unity and Vuforia/MARSS.
Engage in Hands-On Projects: Participate in hands-on projects that involve the creation of XR applications for real-world engineering challenges, in collaboration with other students.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The assessment will be based on a project agreed with the Lecturer, which the student will develop in a group (or independently, if agreed with the Lecturer) and present at the end of the course. The project will consist of an XR application developed using the methodologies and technologies learned in the class.

P. Coiffet, G.C. Burdea, Virtual Reality Technology (3rd ed.), Editore: Wiley-IEEE Press, Anno edizione: 2024, ISBN: 978-1118014806

The course will give students methods for building fast and adaptive Digital-Twins in a unique and coherent statistical framework for health and usage monitoring. Practical experiences will allow students to apply the concepts learned during the course to real-case scenarios. Students will analyze mechanical systems, modelling components in their operative scenario, including degradation and failure mechanisms typical of system operation, then applying algorithms to statistically identify the health condition of a system and use the updated Digital-Twin to statistically predict the system future evolution. More specifically:

• The course is aimed at providing the Students with practical concepts and instruments for modelling complex systems in their operative environment or asset, including degradation phenomena through the Digital-Twin.
• The course will merge multidisciplinary inputs from different sectors (mechanical, materials, data science, management engineering, etc.) in a unique and coherent virtual framework that can be used for design, operation and monitoring optimizations.
• The course will introduce students to the field of health and usage monitoring of structures and systems, specifically focusing on the role of models (and Digital-Twins) in the diagnosis and prognosis of mechanical (and, in general, industrial) systems and components, exploiting statistical pattern recognition and machine learning to interpret changes in their measured features.

In terms of acquired knowledge and understanding, students will be able to:
Examine scenarios where Digital-Twin models can bring benefits
Predict benefits and drawbacks of modelling methods in the framework of mechanical (and, in general, industrial) system design, operation and monitoring optimization
Interpret existing application studies in the literature and implement methodologies appropriate for solving complex problems, both systematically and creatively.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
Apply the methods covered during the course on realistic scenarios
Demonstrate the pros and cons of the modelling strategy in relation to the application scenario
Critically, independently and creatively solve problems with some originality in new or unfamiliar environments within the multidisciplinary context of Digital-Twins
Through a schedule of hands-on practices, students will also acquire the skills to formulate a judgment, meaning to
Analyse the modelling framework
Formulate subjective expectations on the results
Judge the results as a comparison with prior expectations
Provide a sound judgments even on the basis of incomplete or restricted information
Through the reporting activity, students will gain the ability to synthetize and present their work in the form of report and/or presentations, also improving their communication skills.

In the era of digitalization, Digital-Twins have been proposed as a mean to mimic the system life cycles in a virtual scenario. Specifically, a Digital-Twin is a virtual replica that mirrors the real system condition, resulting from the combination of a master model (typically developed during design) with real-time data (digital shadow) potentially captured during system operation. In this context, the digital-twin, constantly updated and refined during operation, can include information about potential damage/faulty scenarios and, thus, be used to simulate new information that is necessary for real-time assessment of the actual system condition (e.g. for structural damage identification) and for predictive asset optimization (e.g. for operation and maintenance optimization). This makes the Digital-Twin a crucial element in the development of any health and usage monitoring system.
To this aim, the following topics are treated throughout the course:
Introduction: the role of the Digital-Twin within system operation. Evolution of design and maintenance criteria (from safe life to damage tolerant design, from fault driven to predictive maintenance). Introduction of Health and Usage Monitoring Systems as a means toward predictive maintenance. Application of Digital-Twins for system health and usage monitoring as input to the operation and maintenance optimization.
Operational evaluation: review of different degradation processes affecting mechanical components in their operative environment. Models for prediction of damage progression and failures (fatigue, fracture, corrosion, creep, etc.) and general system performance degradation (e.g. fouling, battery state of life/charge, etc.). Motivation to the development of Digital-Twins for health and usage monitoring.
Digital master model creation. In this practical module the student will model continuous degradation processes and discrete system failures into the physical model of the component/system (within the Matlab Simulink/Simscape/Simevents framework). Realistic application scenarios will be considered, with final goal to simulate either changes in signal features captured by potential sensors or, in general, system performance degradation.
Improve simulation speed. In this module the students will learn how to use machine learning (specifically artificial neural networks) to approximate input-output relationships simulated with a detailed model. The resulting surrogate model is a requirement enabling the stochastic adaptiveness within the following Monte-Carlo sampling framework.
Development of an adaptive and stochastic Digital-Twin. In this module the student will use Bayesian inference to fuse the information from models with the continuous stream of information by sensors, resulting in a real-time statistical adaptation of model parameters to fit the real component or system subject to degradation. The Bayesian Model Updating will also offer a natural framework for combination of prior knowledge on the system parameters (including potential damage) with the new information from sensors.
Overview of conditional probability distributions and Bayes theorem
Monte-Carlo sampling strategy for approximated Bayesian inference in multiple-parameter updating. The need for an efficient sampling strategy: forced sampling.
Metropolis-Hastings Markov Chain Monte-Carlo methods for statistical pattern recognition
Sequential Importance Sampling/Resampling (particle filter) for tracking and prognosis of non-linear non-Gaussian systems subject to degradation

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Students will pass the course after delivering a report of the practices developed together with a tutor and an oral examination intended to assess the understanding of the theory and the concepts delivered through the reports.
[Report]
Via this exam, it will be possible to test students’ acquired knowledge and understanding, their capability to apply the acquired knowledge and understanding, and their capacity to synthetize them through short reports. A max 4-pages report is required for some specific practices and laboratories, including a short summary of the topic goal, the method used with boundary hypothesis for its application to the case study, the results and comments on the results. Groups of 2 students are allowed in making the reports.
[Oral exam]
Via an oral examination, it will be possible to test students’ contribute in the reporting, asking to provide comments on particular aspects, decisions, hypothesis, etc. made in the context of the practices. Additional theory questions will also allow to test the student command on the main aspects treated during the course.
Final Grading
To pass the course, students must successfully pass the oral test (grade higher or equal to 18/30). Reports will be assessed based on a +3 to -5 grade.

...
Note: Slides and additional material will be timely provided before each lecture and practice

The course deals with digital twins of production and logistics systems. At the end of the course, the student will be able to design and develop a digital twin with its main services such as prediction, prognosis, optimization, and control, including their business proposition.
Module 1 Digital Twin architecture and models. (all versions)
Students will learn the main concepts of digital twins for production and discrete event systems, including reference architectures, models, and techniques for their operational phases, design criteria, and main use case applications.
Module 2 Formal and digital representations of production systems. (all versions)
Students will learn how to model into formal and digital representations the base elements of production systems as well as their performance measures, abstraction levels, and design criteria.
Module 3 Simulation modelling and analysis of production systems. (all versions)
Students will learn discrete event simulation techniques for estimating the performance indicators critical in the design and management of production and, more generally, discrete event systems.
Module 4 Digital Laboratory. (all versions)
Students will receive the essential theoretical and practical elements for creating and executing, in a dedicated software environment, valid discrete event simulation models representing production systems.
Module 5 Process Mining. (only 10 CFU version)
Students will receive the essential theoretical and practical elements for discovering process structure from data logs collected from discrete event systems.
Module 6 Reinforcement Learning. (only 10 CFU version)
Students will receive the essential theoretical and practical elements for developing control agents based for production dispatching and scheduling.

Knowledge and Understanding
By the end of the course, students will have acquired comprehensive knowledge and understanding through lecture sessions, enabling them to:
Identify and explain the main elements of the production system and their interrelationships.
Identify and explain the main components of digital twins and their interrelationships.
Describe the fundamental principles of discrete event simulation.
Discuss the basic methodologies for analysis within the context of stochastic simulation.
Applying Knowledge and Understanding
Through classwork, students will develop the capability to apply their knowledge and understanding to:
Model various production systems using discrete event simulation software, including manufacturing lines, assembly lines, job shops, and flexible manufacturing systems.
Set up simulation models incorporating data input analysis techniques.
Analyze system behavior using data output analysis techniques.
Evaluate and compare alternative manufacturing systems based on simulation outputs.
Making Judgments
Through group project work, students will enhance their ability to manage the complexity of manufacturing systems, integrate knowledge from other courses related to production systems and industrial plants, and make informed judgments even with incomplete and uncertain data. Specifically, they will be able to:
Autonomously analyze and design a production system with partial information.
Obtain data and derive knowledge from experiments conducted in a physical laboratory.
Select the appropriate level of modeling detail from physical systems to conceptual models.
Choose suitable coding strategies for building simulation models within a digital twin platform.
Support their choices and conclusions with evidence.
Communication Skills
Students will enhance their communication skills, enabling them to:
Summarize and present results through technical documents.
Deliver oral presentations to specialist audiences effectively.
Learning Skills
The course will foster the development of learning skills, encouraging students to study in a largely self-directed and autonomous manner.

The course consists of lectures and classwork modules on presence. A classwork module will be delivered in the Digital Lab to allow students to use state-of-the-art software for digital twins of production and discrete event systems. In the Physical Lab students will be required to conduct experiments oriented to accomplish problem-solving activities in a team.
The course covers the following topics divided into modules as per the description below:
Module 1 Digital Twins architecture and models.
List of contents - Introduction to digital twins. Five-dimensional model: physical, virtual, connection, data, services. Architecture layers. Internal services including synchronization physical to/from digital, online validation, process mining for data-driven model generation and enhancement, process mining for data analysis, and reinforcement learning for policy selection. Provided services: monitoring, prediction, scenario analysis, optimization & control, analysis. Applications of digital twins.
Module 2 Formal and digital representations of production systems.
List of contents - Formal representations methods of discrete event production systems: State-based models, Entity Relationships Graphs, Petri Nets. Main elements of production systems: stations, buffers, transporters, tools, fixtures, and pallets. Flexible and Cellular Manufacturing Systems. Machining lines. Assembly lines. Job shops. Performance indicators. Overall Equipment Efficiency. Relevant design variables.
Module 3 Simulation modelling and analysis of production systems.
List of contents – Discrete Event Simulation. Simulation projects. Conceptual models. Random number generation. Random variate generation. Input modelling analysis. Output analysis. Verification, validation, and calibration of simulation models. Variance reduction.
Module 4 Digital Laboratory.
List of contents – Discrete event simulation software environment. Process-oriented modeling concepts. Controlling pseudo-random numbers in simulation experiments. Collecting simulation statistics. Reading/writing from external sources. Integrating simulation model in digital twin architectures. Project & Physical Lab. The objective of the project is to help students in applying the approaches and principles we teach in class. The project will be assigned throughout the semester. Project results are expected to be released within the first exam session; the specific deadline will be defined by the time the project is assigned. The evaluation of the project will be based on the produced Project Report and on a presentation. The project laboratory will require Experimental Lab sessions on a physical miniaturized lab-scale production system.
Module 5 Process Mining. (only 10 CFU version)
List of contents – Overview of process mining techniques. Data log structure. Alpha mining algorithm. Conformance checking techniques and measures. Process enhancement techniques. Use cases analyzed in the laboratory.
Module 6 Reinforcement Learning. (only 10 CFU version)
List of contents – Discrete Markov chains. Markov decision processes. Dynamic programming algorithms. Overview of reinforcement learning techniques. Model-free prediction techniques. Model-free control techniques. Basic algorithms: SARSA, Monte Carlo, Q-learning. Overview of deep reinforcement learning techniques. Use cases analyzed in the laboratory.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course after successfully giving an oral presentation of the delivered project report.
Project Report
Students (in groups of three members) will analyze and improve a production system. They will be required to study an existing production system in the Physical Lab, understand the main problems, and propose a plan for improvement using digital twin experiments (application of knowledge, making judgments, handling complexity). A Project Report will document how they have developed their work and what results they have achieved.
Students must describe in the report:
Problem identification
System Models
Input data analysis
Model validation
Digital twin setting
Experimental design (one or more)
Identification and comparison of alternatives
Comparison of alternatives.
In some activities, students will be completely autonomous (e.g., selecting the methods and procedures to find a limited set of good solution alternatives) in choosing the approach to adopt (learning skills). The ability to communicate technical information will be assessed based on the clarity of the Project Report and the effectiveness of a slide presentation with 10 minutes of duration (communication).
Each project presented by a team receives a grade in the intermediate and final project reviews. All team members must participate in project reviews. The team members' grades can differ based on their contribution to the project report. A minimum value of 18/30 is required to pass the project activities. Students with a “not pass” assessment are required to repeat the Project and the Physical Lab when available, perhaps jumping to the following year, depending on the availability of the Physical Laboratory.
30 cum laude (con lode) will be assigned to only students who have a distinguished level of knowledge acquired, critical analysis, and communication.

Andrea Matta, Giovanni Lugaresi, Digital Twins: Features, Models, and Services, Editore: IEEE, Anno edizione: 2023 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10407260
Averill M. Law, Simulation Modeling and Analysis, Editore: Mc Graw Hill, Anno edizione: 2013, ISBN: 978-0-07-340132-4
Barry L. Nelson, Foundations and Methods of Stochastic Simulation, Editore: Springer, Anno edizione: 2013, ISBN: 978-1-4614-6159-3
Stewart Robinson, Simulation. The Practice of Model Development and Use, Editore: Palgrave MacMillan, Anno edizione: 2014, ISBN: 978-1-137-32802-1
Wil M. P. van der Aalst, Process Mining: Data Science in Action, Editore: Springer, Anno edizione: 2018
Richard S. Sutton, Andrew G. Barto, Reinforcement Learning, Editore: Bradford Books, Anno edizione: 2018

Il corso si concentra sui gemelli digitali dei sistemi di produzione, che sono repliche digitali di sistemi fisici utilizzati per supportare la presa di decisioni durante le fasi di progettazione, produzione e operazione degli impianti industriali. L'aspetto centrale del corso è la modellazione e le tecniche di analisi della simulazione ad eventi discreti che costituiscono il nucleo della tecnologia dei gemelli digitali.

Lo scopo del corso è rendere gli studenti consapevoli delle responsabilità penali connesse alla progettazione e conduzione degli impianti industriali.
L'insegnamento - mediante l'analisi di casi aziendali e di sentenze in materia antinfortunistica - fornirà una descrizione dei più diffusi problemi tecnici, organizzativi, comportamentali che interessano i contesti produttivi, soffermandosi in particolare sulle criticità attinenti la relazione uomo - macchina.
Verranno quindi illustrate alcune soluzioni tecnico/organizzative - conformi agli attuali standard giurisprudenziali - per risolvere dette criticità e prevenire così efficacemente infortuni e reati negli stabilimenti industriali.
Sarà infine offerto un dettagliato quadro degli strumenti difensivi che le aziende possono utilizzare in caso di contestazioni da parte dell'Autorità Giudiziaria.

Questo corso mira a discutere la tecnologia degli edge-device e dell'IIoT (Internet Industriale delle Cose) per supportare la sensorizzazione delle macchine operanti a livello di shopfloor. Ai partecipanti verrà insegnato come selezionare i sensori appropriati e i sistemi integrati su misura per specifiche applicazioni industriali. Concetti come le capacità dinamiche dei dispositivi, la linearità, la stabilità rispetto a input interferenti/modificanti (ad esempio, temperatura, vibrazioni, ecc.) saranno affrontati con lo scopo di fornire consapevolezza nell'utente per la progettazione di sistemi di misurazione basati su soluzioni integrate. Verranno discussi la principale tecnologia di comunicazione (BLE smart, WiFi, LoRa, ecc.) e i protocolli (MQTT, Opc-UA, ecc.), così come le principali architetture che gestiscono il trasferimento di dati e informazioni dal livello OT al livello IT (ad esempio, sensori-gateway-cloud). Questi concetti dovrebbero aumentare la consapevolezza nei partecipanti su come progettare, distribuire e implementare soluzioni IIoT.

The course gives the students the basic dictionary of the electrical drive. Thanks to the knowledge gained during the course, students will learn to compare the functional performances in relation with the different market segment, and to choose different components from manufacturer catalogues. In order to reach this goal the operating condition and the control algorith for different electrical drive will be analyzed, underlining the main constituting elements: the electrical motor, the power converter, the control algorithm and the power supply system. Furthermore different applications will be analyzed both in industrial and in transport field.

Lectures will provide the basis for electrical machine modeling, for electrical machine control and for power electronic understanding ( Knowledge and understanding ).
During practical exercises students will tacke some engineering problem: a resolution approach is proposed to the students who are asked the to execute it individually or in small groups (2-3 person). The proposed problems are typically related to the choose of devices from industrial catalogues (motors/inverter/batteries) or the the definition of the operational diagram from the nameplate data. ( Applying Knowledge and understanding )
The achievemnts of both the above mentioned results will be verified during the final oral exam ( Communication ).

General structure of an electrical drive. Identification of the nameplate data for the drive and for its main components. Criteria to choose the components for an electrical drive, thermal operating point. Calculation and meaning of the RMS torque. Case studies in the field of both industrial and transportation application.
Static power conversion. Description of the main power semiconductor devices. Analysis of different power converter and of the different way for power conversion; rectifier (AC/DC conversion), inverter (DC/AC conversion), chopper (DC/DC conversion). Analysis of the control techniques and modulation for the proposed converters. Energy analysis in industrial and transportation drive.
DC motors. The DC isotropic machine. Real structure. Operating characteristic, operating field (variable voltage), the commutator, the dynamical model.
Synchronous motors. The rotating magnetic field for bi-phase and three-phase systems. The synchronous isotropic machine: general structure and operating characteristic. Operating field with variable supply voltage (through inverter). Isotropic synchronous machine with permanent magnets: dynamical model. Difference in construction of Permanent Magnet Synchronous Motor (PMSM) with respect to Rotor Wound Synchronous Motor.
Induction motors. The induction motor: model and equivalent circuit calculation. Output torque characteristic: remarkable point (starting torque, maximum torque, small slip torque). Operating field both with fixed and variable supply voltage.
Control of electrical machines. Control scheme for DC motor. Closed loop control for current/speed/position regulation. Use of chopper for DC motor control. Permanent Magnet Synchronous Motor (PMSM): Field Oriented Control (FOC). Induction Motor (IM): voltage/frequency scalar control Vs Field Oriented Control.
Electronics. Basic electronic circuit: power suppliers (Zener regulator, Linear Voltage Regulators and switching regulator) and Operational Amplifier (inverting, non-inverting, summing and differential configuration). Applications.
Case studies: application of electrical drives and industrial controllers. Electrical drive for hybrid/full electric vehicle application. Configuration of electrical drive for railways application. Industrial application: servomotors and bi-directional converters.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
The final assessment of the course consists in an oral test.
The aim of the oral discussion is to verify that students:

• have acquired a sufficient level of knowledge and understanding of the course topics;
• are able to apply knowledge in solving engineering problem with specific reference to the practical exercises;
• are able to communicate with a proper technical language.

W. Leonhard, Control Of Electrical Drives
Manigrasso R., Mapelli F., Mauri M., Azionamenti elettrici: Generalità e macchine rotanti
Manigrasso R., Mapelli F., Mauri M., Azionamenti elettrici: convertitori e controllo

This course aims to provide the basics of low-voltage electrical safety by exposing, discussing and understanding safety issues with reference to electrical industry regulations. Electrical safety is a very important section of electrical installations, because it must contextually protect electrical equipment/systems under any operating condition (transient, steady state, abnormal or fault conditions) and human beings. The course will mainly cover the safety of people from electrical systems, understood as the set of protection systems suitable for preserving the health and safety of human beings interacting with electrical systems. Bearing in mind that low-voltage may involve environments frequented even by people untrained in the selection and use of electrical materials and components, a key role in safety lies with the type of electrical system implemented and the competence of the designer and performer of the system itself.
The course will first recall the legal norms that elect safety against hazards as a right of all citizens and workers, as well as indicate the means and institutions that should guarantee this right.
Some definitions of general terms such as safety and risk will then be given and the methodology for identifying the acceptable level of safety, which, as is well known, is never absolute, will be discussed.
Finally, methods of protecting people from the hazards of electricity suitable for different low-voltage distribution systems will be addressed.
The course will consist of theoretical class lectures and seminars and exercises given by professionals in the field in order to also present the critical issues that may be encountered during the design and implementation of the system as well as the interaction with other branches of engineering with which the systems must coexist.

Upon passing the exam, the student will have achieved:
Knowledge of the legal norms that elect safety against injuries as a right of all citizens and workers and indicate the means and institutions that should guarantee this right.
Ability to recognize and interpret the purpose, structure and operation of low-voltage systems under normal and faulty conditions.
Knowledge of the effects on the human body resulting from the flow of an electric current.
Knowledge of basic concepts related to the problems of interrupting electric current and choosing protection against electrocution.
Ability to interpret and apply concepts regarding safety for people and related regulatory requirements.
Knowledge of protection systems for people to avoid hazards from direct contact with active parts of electrical power systems.
Knowledge of protection systems for people to avoid hazards from indirect contact with grounded parts of electrical power systems.
Ability to assess lightning-related risks to people and/or economic or cultural heritage.
Knowledge and understanding of the main interactions with other branches of engineering to ensure adequate protection of people.

Topic 1: Introduction to electrical safety. General principles of safety. Technical legislation on electrical safety. Electrical risk analysis.
Topic 2: Effects of current in the human body and allowable voltages. The ground as an electrical conductor.
Topic 3: Classification of electrical systems.
Topic 4: Criteria for protection against indirect contacts, in TT, TN, IT systems.
Topic 5: Protection from direct contacts.
Topic 6: Extra-low voltage systems.
Topic 7: Protection against lightnings. Fire protection measures.
Topic 8: Grounding systems.

Prova scritta obbligatoria, senza prove in itinere
A written test is planned to check the adequate achievement of the main expected learning outcomes. In particular, knowledge of correct terminology, the main industry regulations and the characteristics of different power systems for the purpose of their protection will be assessed.
The exam is written and consists of:
T/F questions (1 point for each correct answer, 0 if no answer, -0.5 points if incorrect)
multiple-choice questions (1 point for each correct answer, 0 if not answered or incorrect)
written questions (up to 7 points for each question)
The maximum final score is 33 points; those who have scored >= 32 are eligible for honors (laude)

Massimo Mitolo, Electrical Safety of Low-Voltage Systems, Editore: The McGraw-Hill Companies, Inc., Anno edizione: 2009, ISBN: 9780071508186

The course builds on basic principles and concepts (in the field of electric circuit analysis, signals and systems, electronics, and electromagnetic fields) to provide an introduction to Electromagnetic Compatibility (EMC). The course is designed to help students develop a deeper understanding of electromagnetic interference and the prevention of it through suitable design strategies. The addressed subjects cover: nonideal behavior of components, transmission line circuit models for EMC, conducted emissions and susceptibility, radiated emissions and susceptibility, antennas (basic principles, test and measurement antennas for EMC), crosstalk, shielding, grounding, measurement instrumentation, setups and facilities for EMC testing, governmental and functional requirements, system design for EMC. Practical applications considered in this course concern EMC aspects in complex electrical and electronic systems and environments, such as those found in aerospace, automotive, electric power generation, transmission/delivery, and railway industry sectors.

The course aims at providing a picture of the electronic probe microscopy techniques as general as possible, starting from the basics of the major techniques and examples of prototypical applications up to state of the art scientific cases. The main goal is to provide the student with the ability of assessing the feasibility and effectiveness of microscopic measurements to tackle a given problem. The course will focus on the information that can be obtained (morphology, chemical contrast, short-and long-range structure, spectroscopy) and on the choice of the microscopic techniques that can be effectively employed to investigate a system in a given environment. Experimental and numerical modeling tutorials will give hands on experience of selected concepts.

DdD1 - Knowledge and understanding
Upon passing the exam, the student knows the fundamentals of electron and scanning probe microscopies: she/he is able to draw the layout of a microscope and to comment its main assembly in terms of fundamental Physics (main phenomena and their order of magnitude).
DdD2 - Applying knowledge and understanding
Upon passing the exam, the student is able to select the most appropriate microscopical approach, within the range of techniques discussed, to address a standard problem in material microscopy and to discuss its advantages and disadvantages with respect to the other techniques. The student has a basic understanding of the numerical approaches used to model selected microscopic technique and phenomena.
DdD3 - Making judgements, Communication, Lifelong learning skills
Upon passing the exam, the student is able to read critically scientific literature on microscopy: she/he is able to explain and discuss the techniques adopted by researchers and the evidences supporting their conclusions, eventually proposing a different approach to attain the same or and improved result.

Topics

• Probes with high spatial resolution and state of the art in research and applications.
• Interaction of free electrons and bound electrons with matter.
• Information obtained by using electronic probes.
• Numerical modeling of electron transport in beams and electron -matter interaction.
  a) Far field electron microscopy
• Introduction to electron microscopy (EM)
• Diffraction limit and ray optics
• The scanning electron microscope (SEM)
• Interaction between electron and matter
• Secondary electron contrast
• Depth of field
• Charging and other imaging artifacts
• Back-scattered electron contrast
• Basics of the transmission electron microscope (TEM)
• Sample preparation
• Bright and dark field imaging
• The mass-thickness contrast
• Direct and reciprocal space imaging
• The diffraction contrast (basic aspects)
• The phase contrast (basic aspects)
• The scanning transmission electron microscope (STEM)
• Spectroscopic and time resolved microscopy (basic aspects)
  b) Scanning probe microscopies
• Introduction to scanning probe microscopy (SPM)
• Elements of a scanning-probe microscope
• Tip-sample forces
• Atomic Force Microscopy (AFM) static operation: constant height and constant force
• Shift in the natural frequency of a harmonic oscillator under a force gradient
• Amplitude-modulation dynamic AFM operation
• Dynamic AFM operation: sensitivity in amplitude modulation, frequency-modulation techniques
• Noise and resolution in AFM
• Image analysis in AFM
• Electrostatic and Magnetic Force Microscopy (EFM and MFM)
• Imaging artifacts in SPM
• Scanning near-field optical microscopy (SNOM)
• Introduction to scanning tunneling microscopy (STM)
• Atomic resolution with STM
  Laboratory visits
  Students will attend hands on numerical modeling tutorials about selected features.
  Students will attend experimental laboratory tutorials in image analysis and practical use of research instrumentation, with possibly support of video tutorials.
  Schedule
  The course will be held in the first half of the first term, from mid-September to the beginning of November.
  Notes
  The range and detail of the course will be adapted to the level of the class during the course and may change significantly.

Prova orale obbligatoria
The exam consists of an oral test in two parts of about half an hour each, one about Electron Microscopy and the other about Scanning Probe microscopy.
In each part:

• The student asked to present selected topics of the course, starting from the fundamentals through increasing level of detail and difficulty.
• The student will be asked to select its microscopic technique of choice to address a scientific case and to comment about the limits of application, advantages, and disadvantages.
• The student will be required to briefly present a scientific paper, chosen in agreement with the teacher, where electron or SPM microscopies is the main investigation techniques. The presentation will be focused on the information attained by the use of microscopy and the technical approach adopted to obtain it. As an alternative to one of the two scientific papers, students may choose to incrementally develop and discuss a numerical model discussed within the numerical modeling tutorial.

R. F. Egerton, Physical Principles of Electron Microscopy: An Introduction to TEM, SEM, AEM, Editore: Springer, Anno edizione: 2008, ISBN: 978-0-387-25800-3
Note: textbook for the TEM and SEM section
C. Colliex, La microscopie éléctronique, Editore: Presses universitaires de France, Anno edizione: 1998, ISBN: 978-2-1304-8665-7 http://www.stem.lps.u-psud.fr/la-microscopie-electronique
Note: Introductory reading on TEM, in French.
I. M. Watt, The principles and Practice of Electron Microscopy, Editore: Cambridge University Press, Anno edizione: 1997, ISBN: 0-521-43591-9
Note: Advanced text on Electron Microscopy
Unknown, A practical guide to Scanning Probe Microscopy, Editore: VEECO, Anno edizione: 2005 http://www.veeco.com/pdfs/library/SPM_Guide_0829_05_166.pdf
Note: Introduction to Scanning Probe Microscopy by a well-known manufacturer
E. Meyer, H. J. Hug, R. Bennewitz, Scanning Probe Microscopy: The Lab on a Tip, Editore: Springer, Anno edizione: 2003, ISBN: 3-540-43180-2
Note: Examples of applications

The course aims at providing an overview of state-of-the-art and of novel technologies for the production of electric, heating and cooling power. The course will also cover the key methods and tools to evaluate the energy, environmental and economic performance of energy conversion systems.

Students are expected to acquire knowledge and understanding in:
Main methods and tools to analyze and design energy conversion systems (i.e. mass and energy balances, emissions, economic analysis);
Working principles and main design criteria of conventional and novel energy conversion systems for the generation of electric, heating and cooling power;
Technical and economic challenges associated to the transition towards renewable energy sources.
Students are expected to develop the capability of applying the above described knowledge to:
Develop numerical models and carry out a preliminary engineering design of the main equipment units and conversion processes of energy systems;
Perform first law analysis of conventional energy conversion systems for the production of electricity, heat and refrigeration power (i.e. writing and solving mass and energy balance equations, evaluate the key performance indicators, discuss design and operational principles also with the support of schemes and diagrams);
Make judgements on their techno-environmental-economic feasibility and performance.

Introduction to the course and Energy outlook: units for power and energy (refresher); mass and energy balances; thermodynamic properties of fluids (refresher); primary energy sources; energy demand and supply evolution.
Heat exchangers: design and off-design calculation methods.
Combustion processes: basic properties of fuels and combustion processes; mass and energy balances of chemical reactions; overview of the emission of pollutants from combustion processes.
Power generation with thermodynamic cycles: steam and Rankine cycles, gas cycles and gas turbines, combined cycles.
Refrigeration cycles and Heat Pumps: reverse Rankine cycles components and design principles; configurations and preliminary design of key cycle components; working fluids (refrigerants); performances of heat pumps and refrigeration cycles; applications.
Renewable energy technologies: solar, wind, biomass.
Economic analysis: overview on the methodology for the calculation of the cost of electricity.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Students will pass the course after successfully taking a written exam divided into two sections (taken on the same day).
Written test on numerical problems – mandatory
This test aims at evaluating students’ ability to apply the acquired knowledge and understanding to simple problems, the ability to independently form judgements and the ability to use the acquired knowledge for further professional development.
The exam consists of numerical problems. Consulting books or lecture notes is allowed. The topics covered in the exam span the whole course program (including the exercise lessons).
Written test on theory – mandatory
This test aims at evaluating students’ acquired knowledge and understanding, the ability to communicate learnt contents, the ability to use the acquired knowledge for further professional development.
The test consists of theory questions. Consulting books or lecture notes is NOT allowed. The topics covered in the exam span the whole course program (including the exercise lessons/real-world project).
Final grading
To pass the course, students must successfully complete the two written tests (on the same day) with a minimum score of 16/30 on both parts.
Optional oral test
An oral test is required in two scenarios:

• If the final grade of the written exam is greater or equal than 16 and below 18, to reach sufficiency. In case the student refuses the oral exam, a "FAIL" is going to be automatically registered.
• If the final grade of the written exam is greater or equal than 28. In case the student refuses the oral exam, a "27" will be automatically registered.

A. Bejan, Advanced Engineering Thermodynamics, Editore: Wiley, Anno edizione: 2006
Kuo K. K., Principles of Combustion, 2nd edition, Editore: Wiley-Interscience, Anno edizione: 2005
R. Kehlhofer, F. Hannemann, F. Stirnimann, B. Rukes, Combined Cycle Gas & Steam Turbine Power Plants, 3rd ed, Editore: PennWell, Anno edizione: 2009
H. Spliethoff,, Power Generation from Solid Fuels, Editore: Springer, Anno edizione: 2010
G. Boyle, Renewable Energy, Editore: Oxford, Anno edizione: 2014
Nader Anani, Renewable Energy Technologies and Resources, Editore: Artech house, Anno edizione: 2019

The primary objective of this course is to ensure that all incoming students acquire a solid and comparable foundation in energy systems. It aims to equip them with the essential knowledge required to successfully engage with more advanced courses in subsequent semesters. The course provides core theoretical concepts, methodologies, and analytical tools to understand the operating principles and design fundamentals of key components and energy conversion systems used in power generation and heat production.

Knowledge and Understanding
Through lectures and problem-solving sessions, students will develop the ability—upon passing the exam—to understand and describe the components and systems studied in the course using an engineering approach. This includes the use of equations, diagrams, numerical calculations and basic software applications.
Applying Knowledge and Understanding
Lectures and exercises will enable students—once they have passed the exam—to:

• Formulate mass and energy balances to describe thermodynamic processes in fluid machines and heat exchangers;
• Critically analyze the thermodynamic and technological aspects, operating principles, and processes of the components and energy systems covered in the course, and make technical comparisons among different alternatives;
• Select and apply the most appropriate methods for designing, sizing, and evaluating the performance of key equipment and energy conversion systems for power generation and heat production.

Heat Exchangers and Cooling Towers
Heat transfer on finned surfaces. Types of heat exchangers and global heat transfer coefficients. Sizing and performance verification of heat exchangers. Log-mean temperature difference and the ε-NTU method. Properties of humid air and use of psychrometric charts. Definitions of characteristic temperatures. Mass and heat transfer between air and water flows. Principles and operation of evaporative cooling towers.
Mass and Energy Balance Analysis of Energy Systems
Application of the First Law of Thermodynamics to basic processes. Reactive systems and combustion. Physical and chemical properties of hydrocarbons. Atomic, mass, and energy balances in combustion reactions. Fundamentals of thermochemistry: elemental species, enthalpy of formation, heat of reaction. Diffusive and premixed flames. Formation mechanisms of major combustion pollutants. Hydrocarbon combustion and strategies for emission control. Greenhouse gas emissions.
Second Law Analysis
Entropy production; definition of exergy and reversible work; second law efficiency. Application of second law analysis to energy systems. Identification of major sources of irreversibility in turbomachinery, heat exchangers, and chemical reactions. Exergy-based evaluation of power cycles.
Steam Cycles
Thermodynamic and technological characteristics of Rankine cycles. Regeneration and reheat processes. Optimization of key operating parameters. Steam generators: types, construction, heat transfer challenges, combustion features, losses, and efficiency. Technologies for reducing environmental impact. Fundamentals of steam cycle control. Heat rejection systems: once-through water cooling, evaporative towers, and air-cooled condensers.
Gas Cycles
Thermodynamics of ideal and real Brayton cycles. Turbine blade cooling techniques. Influence of key design parameters on cycle performance. Industrial and aeronautical applications. Main variants of the simple gas turbine cycle. Compressor–turbine matching and determination of the operating point for single-shaft gas turbines. Principles of gas turbine control.
Combined Gas–Steam Cycles
Motivations for using binary cycles. Thermodynamics of cycles with variable temperature sources. Combined cycle plant configurations. Single- and multi-pressure heat recovery steam generator (HRSG) arrangements. Performance analysis and control strategies for combined cycles. Start-up of combined cycles.
Fundamentals of Economic Evaluation of Energy Systems
The time value of money. Discounted cash flow analysis. Net present value and internal rate of return. Investment and operational cost estimation. Methods for estimating the cost of electricity generation.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Assessment methods for students in Energy Engineering
The exam consists of a compulsory written examination and an optional oral examination.
The written examination consists of two numerical problems related to all topics covered in the course, together with some multiple-choice or graphical-response questions. The test is designed to assess students’ ability to:

• Assess the performance of energy conversion plants, or sections thereof, at the design point by carrying out mass, chemical species, and energy balance calculations.
• Validate the operating conditions of energy conversion plants, or sections thereof, under off-design conditions, using the operating principles of the system components.
• Evaluate the Levelized Cost of Electricity (LCOE) and CO2 emissions of energy conversion plants.
  There are five written exam sessions in each academic year:
• Two at the end of the first semester
• Two at the end of the second semester
• One in September
  The written test is assessed on the basis of the formal and numerical solutions provided by the student, as well as the correctness of the answers to the questions. Examinees may consult any printed material; however, the use of phones, tablets, or personal computers is not permitted. After the test, the solutions are distributed, and each student may request to withdraw from the exam. In this case, the test will not be corrected and will not affect the student’s record, resulting in a “postponed” outcome. If the student requests grading, the possible outcomes of the written test are as follows:
• The maximum score achievable in the written test is 32 out of 30.
• Scores of 8 or lower result in a “rejected” outcome. A “rejected” outcome prevents the student from registering for second sitting in the same exam session. This restriction applies only to the first of the two sittings following the end of the semesters.
• Scores between 9 and 17 result in a “postponed” outcome.
• With a score between 18 and 32 allows the student passes the written examination.
  After passing the written examination, students may choose between two options:
  They may complete the examination by accepting the grade obtained in the written test, up to a maximum final grade of 24. Accordingly, students who obtain a written-test score higher than 24 but decide not to take the oral examination will have a final grade of 24 recorded.
  Alternatively, they may take the oral examination, which may be held on a different date within the same examination session. The oral examination is intended to confirm and, where appropriate, modify the final grade; the grade may therefore be increased or decreased.
  The oral exam assesses the student’s understanding of the fundamental aspects of the course and examines cause-and-effect relationships affecting plant operation when design parameters and boundary conditions change. One or more questions will concern topics covered during the course exercises.
  Students who decline the grade awarded at the end of the oral exam must repeat the written examination.
  The professor nevertheless reserves the right to conduct an additional oral examination to verify the results emerging from the written test.
  Assessment methods for students in Mechanical Engineering
  The exam consists only of a compulsory written examination. The written test is exactly the same as that taken by Energy Engineering students, but the maximum score is set to 32 out of 30.
  The professor nevertheless reserves the right to conduct an additional oral examination to verify the results emerging from the written test.

Lecture notes about some topics of the course available on the Webeep site
Michael J. Moran, Howard N. Shapiro, Daisie D. Boettner, Margaret B. Bailey, Principles of Engineering Thermodynamics, 8th Edition, SI Version, Editore: John Wiley, Anno edizione: 2015, ISBN: 978-1-118-96088-2
Lienhard J. H., A Heat Transfer Textbook, 6th edition, Editore: Phlogiston Press, Anno edizione: 2024, ISBN: 9780486837352 https://ahtt.mit.edu/
Frank P. Incropera et al., Fundamentals of Heat and Mass Transfer 6th edition, Editore: Wiley, Anno edizione: 2007, ISBN: 9780471457282 https://opac.biblio.polimi.it/SebinaOpac/resource/fundamentals-of-heat-and-mass-transfer/PMI00479117
Steven G. Penoncello, Thermal Energy Systems Design and Analysis, Second Edition., Editore: CRC Press, Anno edizione: 2018 https://doi.org/10.1201/b22141
Kam W. Li, A. Paul Priddy, Power plant system design, Editore: Wiley, Anno edizione: 1985, ISBN: 978-04-7188-847-5 https://www.bibliosearch.polimi.it/permalink/39PMI_INST/1nvvje2/alma99607258508776
H.I.H. Saravanamuttoo et al., Gas turbine theory 6th ed., Editore: Prentice Hall, Anno edizione: 2008, ISBN: 9780132224376 https://opac.biblio.polimi.it/SebinaOpac/resource/gas-turbine-theory/PMI00524498?tabDoc=tabcata
J.H. Horlock, Advanced Gas Turbine Cycles, Editore: Pergamon, Anno edizione: 2003, ISBN: 978-0-08-044273-0 https://doi.org/10.1016/B978-0-08-044273-0.X5000-7
R. Kehlhofer, F. Hannemann, F. Stirnimann, B. Rukes, Combined Cycle Gas & Steam Turbine Power Plants, Editore: PennWell, Anno edizione: 2009, ISBN: 101-59370-168-3

Obiettivo del corso è quello di approfondire e, in qualche caso, sviluppare ex-novo le nozioni legate ai fenomeni di cedimento e di degrado in esercizio di componenti, macchine e impianti in ambito industriale ( Failure Analysis ), nonchè di introdurre alcune tematiche di natura legale ed assicurativa che hanno implicazione nella gestione delle suddette problematiche d'esercizio ( Ingegneria Forense ).
Ciascuna tematica trattata (cedimenti duttili, sovraccarichi, cedimenti fragili, infragilimenti, scoppi, esplosioni, incendi, fatica, corrosione, usura, creep) è integrata e completata dallo studio di alcuni casi esemplificativi ( Case Histories ).
Le tematiche verranno svolte considerando sia le caratteristiche meccaniche/metallurgiche dei semilavorati (materiali, trattamenti, rivestimenti, ecc.), sia gli aspetti progettuali e di fabbricazione, sia le condizioni di esercizio.
Una parte importante dell'insegnamento è legata alla descrizione delle problematiche e delle ricadute di natura legale ed assicurativa che i fenomeni di Failure Analysis hanno in ambito industriale.

Lo studente approfondisce le conoscenze dei fenomeni di Failure Analysis di componenti, macchine e impianti, realizzati con materiali metallici tradizionali ed innovativi. Lo studente acquisice le conoscenze di base dell'Ingegneria Forense ( conoscenza e capacità di comprensione ).
Lo studente impara a consultare la letteratura specifica della Failure Analysis e dell'Ingegneria Forense per trarne le informazioni pertinenti - dati, normative, dettagli tecnici - volte alla risoluzione dei casi che possono verificarsi in esercizio ( conoscenza e capacità di comprensione applicate ).
Lo studente sviluppa la capacità di individuare e comprendere i fenomeni di Failure Analysi s di componenti, macchine ed impianti, nonchè di valutarne le ricadutte in ambito legale ed assicurativo ( conoscenza e capacità di comprensione applicate ).
Lo studente impara a formulare specifiche azioni correttive, volte alla risoluzione dei problemi di Failure manifestatisi su componenti, macchine e impianti, nonchè a decidere in merito alle azioni da intraprendere in ambito legale e assicurativo ( autonomia di giudizio ).

Argomento 1 – Failure Analysis e metodi di indagine: tecniche di indagine, microscopia ottica ed esami visivi, microscopia elettronica, frattografie, analisi quantitative, studio di alcuni casi pratici di failure analysis. Failure Analysis e Root Cause Analysis. Ingegneria forense. Introduzione agli aspetti legali ed assicurativi dei fenomeni di Failure Analysis.
Argomento 2 – Failure Analysi s di componenti, macchine e sistemi meccanici: meccanismi di frattura duttile e di frattura fragile e di sovraccarico, cenni alla meccanica della frattura. Fenomeni di infragilimento dei materiali metallici. Aspetti microscopici e frattografici. Case Histories.
Argomento 3 – Failure Analysis di componenti, macchine e sistemi meccanici: fenomeni di scoppio e di esplosione. Cenni ai fenomeni di combustione (deflagrazioni e detonazioni), combustioni da gas, da liquidi e da polveri. Bleve. Aspetti microscopici e frattografici. Case Histories.
Argomento 4 – Failure Analysis di componenti, macchine e sistemi meccanici: fenomeni di fatica. Fatica ad alto e a basso numero di cicli (cenni sui criteri per la determinazione della resistenza a fatica: Infinite Life Criterion, Finite Life Criterion, Damage Tolerant Criterion ). Morfologia dei cedimenti per fatica: aspetti macroscopici, microscopici e frattografici. I fenomeni di fatica e il trattamento superficiale dei materiali metallici. Case Histories.
Argomento 5 – Failure Analysis di componenti, macchine e sistemi meccanici: fenomeni di corrosione. Elettrochimica della corrosione: aspetti termodinamici e cinetici; le curve di polarizzazione anodica-catodica. Morfologia dei fenomeni di corrosione: corrosione generalizzata e corrosione localizzata. La protezione dalla corrosione: intervento sul materiale, sull'ambiente, sull'interfaccia. Case Historie s.
Argomento 6 – Failure Analysis di componenti macchine e impianti: fenomeni di usura e danneggiamento delle superfici. Usura adesiva, tribossidativa, abrasiva, erosiva. Aspetti microscopici e frattografici. Trattamenti termici e termochimici, placcatura ed elettrodeposizione, rivestimenti. Case Histories.
Argomento 7 – Failure Analysis di componenti macchine e impianti: cenni sui fenomeni di scorrimento viscoso di metalli, leghe e superleghe per alte temperature. Morfologia del danneggiamento. Case Histories.
Argomento 8 – Ingegneria forense: aspetti tecnico-legali dei fenomeni di cedimento in esercizio di componenti macchine e impiant. Aspetti di natura civilistica (cos'è il contratto, elementi essenziali ed accidentali del contratto, inadempimenti, risoluzione e recesso del contratto, contratto di compravendita e contratto d'appalto, vizi, difetti e garanzie, prescrizione e decadenza). Aspetti di natura penalistica (cos'è un reato, colpa generica e colpa specifica, aspetti penalistici degli infortuni sul lavoro, misure cautelari). Gli ingegneri nel processo civile e nel processo penale: imputati, periti e consulenti tecnici.

Prova orale obbligatoria
Il corso sarà organizzato in un unico modulo al termine del quale è prevista una prova finale orale, volta a valutare il livello di conoscenza delle tematiche affrontate durante il corso.
Durante la prova finale, allo studente verranno proposti dei problemi che mirano a verificare le sue capacità di:

• schematizzare e descrivere i fenomeni di Failure Analysis del caso di studio assegnato, individuandone cause ed effetti;
• scegliere, in relazione alla problematica individuata, il materiale/processo tecnologico più adeguato per arrivare a risolvere il problema lamentato, eventualmente traendo le informazioni mancanti da apparati bibliografici allegati;
• decidere in merito alle azioni da intraprendere in ambito legale e assicurativo.
  Le domande sono tese ad accertare il grado di comprensione e approfondimento dei fenomeni di Failure Analysis (meccanismi di danneggiamento e cedimento in esercizio di componenti, macchine e impianti) nonchè a valutare le competenze acquisite nell'ambito dell'Ingegneria Forense (aspetti legali e assicurativi).

M. Boniardi, A. Casaroli, Fenomeni di danneggiamento dei materiali metallici dovuti all'esercizio - Failure Analysis (sta in Le prove non distruttive), Editore: Associazione Italiana di Metallurgia, Anno edizione: 2013, ISBN: 888529894X
Note: Oltre ai testi consigliati verrà reso disponibile materiale didattico a cura del docente.
Autori vari, Failure Analysis and Prevention, Vol. 11 (sta in ASM Handbook), Editore: ASM - American Society for Materials, Anno edizione: 2002, ISBN: 978-0-87170-704-8
Note: Oltre ai testi consigliati verrà reso disponibile materiale didattico a cura del docente.

The course Ferroic materials explores the scientific principles, material classes, synthesis, characterization, and engineering applications of piezoelectric, ferroelectric, ferromagnetic and multiferroic materials, from bulk to thin and ultrathin films.

Knowledge and understanding (DD1)
Students will understand the properties of ferroic materials and their microscopic physical origin within the existing classical and modern theories. They will be able to comprehend cutting-edge technological and scientific advances in the field.
Applying knowledge and understanding (DD2)
Students can transfer these physical concepts to applications requiring ferroic materials for sensing, mechanical actuation, information storage and electronic processing.
Students will be able to experimentally access the basic properties of known and unknown ferroic materials.
Make judgements (DD3)
Students will be able to identify the suitability of ferroic materials for each specific application/project making reasoned decisions.
Communication Skills (DD4)
Students can communicate information, ideas, problems and solutions regarding the characterization and exploitation of ferroic materials.
Learning skills (DD5)
Students will have developed those learning skills that are necessary for them to continue to undertake further study with a high degree of autonomy.

Introduction to ferroic materials
Definition, classification, and examples
Key properties of piezoelectric, ferroelectric and ferromagnets
Structure-property relationships
Synthesis of bulk material and thin films
Piezoelectric materials
History, basic concepts and principles
Physics of piezoelectricity for the response to mechanical and electrical stimuli
Classes of materials (piezoelectric ceramics, polymers, and lead-free alternatives to standard piezo materials)
Characterization techniques
Examples, applications, and integration
Ferroelectric materials
The classical theory of polarization
Switching and hysteresis loops in ferroelectrics
Material classes (perovskites, LiNbO 3, layered and other families, ferroelectric semiconductors, non-bulk ferroelectrics, ultrathin ferroelectrics, 2D materials)
The role of hafnium-oxide in electronics
Macroscopic characterization techniques (Sawyer-Tower method, displacive currents methods (PUND))
Microscopic characterization (piezo-response force microscopy)
Beyond the classical approach: the theory of polarization as an adiabatic flow of currents
Ferromagnetic materials
Overview of magnetic materials (diamagnetic, paramagnetic, and ferromagnetic)
Magnetic hysteresis, coercivity, and remanence
Characterization of magnetic materials
Soft and hard materials, permanent magnets
Integration in electronics and mechanical systems
Multiferroics
Bulk and layered multiferroics
The physical reasons behind their rareness
Applications, Future Trends and Challenges
Pyroelectric devices
Piezoelectric actuators (e.g. MEMS)
Ferroic memories (e.g. FeRAM, ferroelectric tunnelling junctions) and field-effect devices (e.g. FeFET transistors)
Magneto-electric spin-orbit devices beyond CMOS transistors
Neuromorphic computing with ferroelectrics
Actuators and sensors at the microscale in microelectromechanical systems
Laboratory activities (hands-on)
The course will include a hands-on session/laboratory that will show the students the tools used for the investigation of magnetic (magneto-optical Kerr effect and microscopy, vibrating sample magnetometry) and ferroelectric (Sawyer-Tower versus displacive current methods (PUND)) materials.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, senza revisioni periodiche, con presentazione/discussione finale
The exam will consist of an oral examination designed to assess the student’s understanding of the course material. Both theoretical and experimental aspects will be given equal weight.
Students may begin the examination with a topic of their choice. They are also encouraged to present an in-depth study of a specific topic, supported by a short written report demonstrating their ability to apply the acquired knowledge to address a problem of interest in the field of ferroic materials (not mandatory, though appreciated).

Ashim Kumar Bain and Prem Chand, Ferroelectrics: Principles and Applications, Editore: Wiley, Anno edizione: 2017, ISBN: 978-3527342143 https://www.wiley.com/en-ae/Ferroelectrics%3A+Principles+and+Applications-p-9783527342143
K. Rabe, Ch. H. Ahn, J.-M. Triscone, Physics of ferroelectrics: a modern perspective, Editore: Springer, Anno edizione: 2007, ISBN: 978-3-540-34591-6 https://link.springer.com/book/10.1007/978-3-540-34591-6
S. Blundell, Magnetism in condensed matter, Editore: Oxford University Press, Anno edizione: 2001, ISBN: 978-0198505914 https://global.oup.com/ukhe/product/magnetism-in-condensed-matter-9780198505914?cc=it&lang=en&

_____________________________________________________________________________
Course Delivery Format
The course is delivered entirely online, allowing students of Bovisa and Lecco campuses the flexibility to choose their mode of participation. Students can attend:
In-person: At the Lecco campus, for those who prefer an on-campus learning environment.
Remotely: Through Webex, ensuring full access to course materials, lectures, and discussions for remote participants.
______________________________________________________________________________________________________
Course Objectives
This course provides a practical, hands-on approach to optimizing material forming processes using finite element simulation tools. Emphasizing application over theory, the course equips students with the skills to integrate metamodeling and optimization techniques into manufacturing process design.
Specifically, the course aims to:
Develop Proficiency in Process Optimization: Teach students to build and apply optimization models for manufacturing processes, focusing on achieving objectives such as cost efficiency, product quality improvement, and environmental sustainability.
Introduce Metamodeling Techniques: Explore tools such as Gaussian Process Regression and Response Surface Modeling to approximate and analyze complex simulation data for informed decision-making.
Apply Design of Experiments (DoE) Principles: Guide students in planning and executing their own DoE, enabling efficient exploration of design spaces and targeted data collection for optimization.
Foster Practical Learning: Engage students in building and refining their own optimization workflows using finite element simulations, providing direct experience in applying learned methods.
Demonstrate Real-World Applications: Showcase how manufacturing processes can be designed to achieve non-conflicting goals of economic and environmental efficiency

By the end of this course, students will:
Master Finite Element Model Preparation for Optimization: Learn to efficiently prepare finite element models tailored for optimization problems, ensuring accurate results while minimizing setup and computational time
Gain Proficiency in Industry-Standard Software Tools: Acquire hands-on experience with widely used commercial software packages in the industry, including Forge 3D, Inspire Form, and JMP, to simulate, analyze, and optimize material forming processes.
Apply Metamodeling and Optimization Techniques: Develop the ability to use metamodeling approaches, such as Gaussian Process Regression and Response Surface Modeling, to approximate complex simulation results and guide optimization.
Design and Execute Optimization Workflows: Build and implement optimization models for manufacturing processes, focusing on balancing objectives such as cost efficiency, product quality, and environmental impact.
Utilize Time-Efficient Design of Computer Experiments (DaCE): Learn to plan and execute DoE strategies to explore design spaces effectively, ensuring comprehensive data collection for optimization within practical time constraints.
Adapt to Practical Industrial Challenges: Understand the practical challenges and constraints of industrial applications, and learn to apply simulation and optimization techniques in real-world manufacturing scenarios.
Collaborate and Communicate Effectively: Develop the ability to work collaboratively on optimization projects and present findings clearly to both technical and non-technical stakeholders

1. Introduction to Digital Manufacturing and Finite Element Simulation
The role of simulation in modern manufacturing
Overview of digital manufacturing technologies: FEM, metamodeling, and optimization
Key concepts: models, phenomena, and their descriptions
Types of models: physical, logical, and mathematical
2. Basics of FEM for Materials Forming
Fundamentals of FEM:
Strong vs. weak form
Element size selection and mesh refinement
Stress and strain formulations: Von Mises stress, effective strain, and flow stress
Modeling fracture and failure in FEM:
Fracture detection methods (FLD, FLSD, and combined approaches)
Forming limit diagrams (FLDs)
3. Commercial FEM Software Training
Overview of industry-standard FEM tools: Forge 3D, Inspire Form, and JMP
Practical sessions: Mesh generation, boundary conditions, and solver configurations
Validation and troubleshooting
4. FEM-Based Optimization for Sustainable Manufacturing
Introduction to optimization principles: Objective functions and constraints: cost, material usage, and quality
Design of Experiments (DoE): Full factorial designs, Latin hypercube sampling, and space-filling approaches
Metamodeling techniques: Gaussian Process Regression, Radial Basis Functions, and Polynomial Regression
Sustainable forming strategies: Minimization of material usage and inverse analysis
5. Case Studies and Applications
Sheet metal forming optimization: Reducing spring-back and improving dimensional accuracy
Bulk metal forming: Material flow prediction and failure prevention
Fracture prediction using advanced criteria: FLDs and Cockroft-Latham models
Real-world challenges in economic and environmental trade-offs
6. Hands-On Project
Designing and executing a DoE for a forming process
Developing and validating an FEM optimization model
Comparing results from different commercial FEM packages

Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation for this course is based on the completion of two FEM-based optimization problems, which students will solve in small groups. The assessment structure is designed to encourage collaboration, practical application of course concepts, and clear communication of results.
Evaluation Components:
Project Work:
Each group will be tasked with solving two optimization problems using FEM tools and techniques covered in the course.
Students will apply industry-standard software (e.g., Forge 3D, Inspire Form, JMP) to build models, conduct simulations, and optimize manufacturing processes.
The optimization problems will focus on achieving specific objectives, such as minimizing material usage, improving product quality, or balancing economic and environmental goals.
Written Reports:
Each group will submit a detailed written report for each project, including:
A description of the problem and methodology.
The setup and execution of the FEM model.
The optimization strategy and design of experiments (DoE) used.
A clear summary of the results, including tables of numerical data and relevant visualizations (e.g., plots, diagrams).
Oral Presentation:
The final exam will consist of an oral presentation delivered by the group.
Each group will:
Present their project results.
Explain the methods used, decisions made, and insights gained from their work.
Respond to questions about their approach and results, demonstrating a deep understanding of the concepts.
Key Evaluation Criteria:
Technical Accuracy: Correct application of FEM methods, optimization techniques, and software tools.
Problem-Solving Skills: Creativity and effectiveness in addressing the optimization problems.
Clarity of Communication: Quality of the written reports and oral presentation, including the use of visual aids.
Team Collaboration: Evidence of effective teamwork and equitable contributions by all group members.
Deliverables:
Two written reports summarizing the results of the optimization problems.
Tables of numerical results for each project.
Oral presentation of the results during the final exam.

The course aims to teach the correct use of the Finite Element Method as a tool for mechanical design, focusing therefore on the more practical aspects required by industry today, without, however, neglecting the theory.
The aim is to convey the need for sound critical analysis of the results obtained from any calculation code, to be compared with first-order approximate manual calculations.
All possible sources of error will be highlighted: from the use of an element type unsuitable for a particular phenomenon to be simulated, to mesh density; from boundary conditions to numerical errors produced by poorly conditioned matrices; and the consistency of the units of measurement used.
The importance of interpreting the results will be emphasised, as well as how to use the figures obtained from the computational models in relation to the various standards for the design of connection elements (e.g. welds)
Tools will be provided for verifying structural integrity and fatigue life using the results produced by the computational models

By the end of the course, students should be able to develop moderately complex computational models containing several interconnected components, and should have a good degree of confidence that the model is correct.
They should have the necessary skills to develop independently and progress, should they find themselves (or strongly wish to) working as structural engineers at a professional level.

PART I - FEM principles and linear elastic calculations
Structural linear elastic calculation recalls
The stress-strain relationship
The strain-displacement equations
The indefinite equilibrium equations
The plane stress state
The plane strain state
The axisymmetric stress state
Finite Element discretization
Elements, nodes and DOFs
Modeling with 2D elements
Plane stress
Plane strain
Axisymmetric stress
Modeling with 3D elements
Modeling with shell elements
Considerations about connections between parts
Welded connections
Rivet connections
Screw connections
Bonded connections
One-dimensional elements
Zero-dimensional elements
Non-structural elements: Multi Point Constraints
Membrane elements
Exercises: hand calculations whenever possible
plane stress of a gear tooth calculated by hand and compared with FE; Kt estimation and usage to get more realistic stress values
thin walled pressure vessel solved by hand and checked with axisymmetric elements
Ring with circumferential moment distribution with axisymmetric elements
Finite Elements as simple domains where to solve the structural problem
Shape functions for the plane stress triangular element
Shape functions for the plane stress quadrangular element
Shape functions for the linear tetrahedral element
Exercises: "playing" with the shape function of the quadrangular element to find strain and stresses for given sets of nodal displacements
Comparison with the results given by Abaqus
The stiffness matrix
The derivation of the stiffness matrix for the CST element
Assembling the global stiffness matrix [K]
Boundary conditions
Loads: point, distributed, thermal, inertial, body loads (the {F} vector)
Constraints: point constraints, symmetry and antisymmetry, imposed displacements
The {F}=[K]{u} matrix equation
Exercises: a practical example with 2 CST elements model
Same example with a 4 node quadrilateral element
Same example with 4 quadrilateral elements
Results comparison with Abaqus
Interpreting the results
Reaction forces
Averaged and un-averaged plot contours
The reference system: local or global
Shell elements: Top, Bottom e Middle, intersections among elements located on different planes, discontinuous joints, continuous joints (weldings)
Solid elements: discontinuous joints, continuous joints
One-dimensional elements
Non-structural elements
Graphics post-processing considerations: the flow lines, the funnel effect, strain energy, Gauss points and nodes
Exercises: Shell I beam in shear and bending: stress calculation (by hand and by FE)
Solid I beam in shear and bending: comparison with the shell model
Riveted plates: rivet forces calculation (by hand and by FE)
Welded joint calculations
The eigenvalue and eigenvector problem: modal and instability analyses
The dynamic problem, free-free modal analysis, constrained modal analysis, the importance of discretization, effective modal mass and modal participation factor, load stiffening.
The stability problem: Eulerian buckling of a beam; the numerical approach
Exercises: Modal analyses on a simple structure using different mesh size
Checking what happens with symmetry boundary conditions
Side buckling of a cantilever beam
Torsional buckling of a thin cylinder
Errors in Finite Element calculation
User errors: input, Unit System
Discretization errors: mesh density (two cases to show the concept); element type (two cases to show the concept); hexahedra versus tetrahedra; quadrangles versus triangles; C-section beam; Z-section beam; large-curvature beam; the skinning technique to overcome a non planar stress state on the surface of solid bodies
Modeling errors
"Distraction" errors
Conceptual errors: cantilever beam modelled in different ways; brick/beam interface; interface between other element types
Numerical errors: the condition number for the stiffness matrix; eigenvalues and eigenvectors of the stiffness matrix (example on an increasingly distorted element)
Pre-processing errors
Exercises: model with inconsistent Unit system
Surface stress comparison with and without the skinning technique
Finite element model validation methods
Numerical validation: applied loads and reaction forces; index "EPSILON"; index "MAXRATIO"; Rigid mode check index; strain energy check; visual checks
Experimental validation: load application without stress measurement; load application with strain gauge measurements
Photoelasticity
Exercises: calculate the "EPSILON" index by hand using the two CST elements model
application of the rigid body check
application of the strain energy check
application of the visual check
Strength assessments
Static assessment for homogeneous and isotropic materials: continuous structure parts; connection systems (screws, rivets, holes and eyelets), welding
Fatigue assessment for homogeneous and isotropic materials; continuous structure parts (classic method, the Gough-Pollard criterion, UIC (Union International des Chemins de Fer) method, the Von Mises criterion, the b2 coefficient (surface finishing), the b3 coefficient (dimensional effect), notching coefficients Kt and Kf, connection systems
Exercises: fatigue assessment of a shaft under constant torque
PART II - FEM in real practice: the Motorsport world
The role of Structural Design in Motorsport and the increasing simulation requirements; mass reduction, importance of stiffness, regulation compliance
Forces acting on the vehicle: inertial loads (acceleration, braking, cornering); aerodynamic loads
Forces at tire contact patch calculation (structurally indeterminate problem)
Forces in suspension members: multilink suspension, double wishbone suspension
Exercises: simplified model of a complete car (rigid and rod/beam elements)
suspension stick model (rod elements) to calculate member forces
suspension stick model (beam elements) to compare with the previous one
Sizing suspension members: tension/compression strength; instability
Sizing attachments: brackets, bolts, pins, lugs
The failure chain (the most economic/easiest to build part has to fail first)
Exercises: choosing one member from the previous exercises and perform all the checks
Wheels, Hubs, Uprights, Wheel Bearings, Brake Calipers: how can Structural Design help suppliers to produce the best parts
Topological, size and shape optimization: basic concepts
Exercises: topological optimization of an Upright
size optimization of a different Upright
Sizing a monocoque: stiffness-to-mass requirements, crash tests, roll over structures static tests
Carbon composite structure optimization: general concepts
Nose push of test: FIA regulations, FEM approach
Primary (Roll Hoop) and secondary (Halo) roll over structures: FIA regulations, FEM approach
Sizing a crashbox: the energy approach
Sizing a wing: FIA regulations about deflections (aeroelasticity)
CFD pressure mapping over the wing surface; loops with CFD to converge to a solution; fluid-strcture interaction
Exercises: mapping a CFD pressure file over a structural mesh

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
A simple problem will be provided; this has to be solved first analytically and individually
The same problem has to be solved with the help of a Finite Element Model; for this a sketch in Abaqus from where to start building the model will be provided and it will be possible to ask for help to the Professor or to the other students, in a sort of collaborative approach. This will be done in front of a PC, either a personal one or one from the room where the exam is taking place.
Then 5 questions will be given in the quiz format, so with 4 answers from which to choose the right one.
And finally other 2 questions with open answers.
Questions will be about what has been treated during the lessons.
The analytical problem is worth 5 points and 30 minutes will be given.
The FE model solution is worth 5 points and 45 minutes will be given.
Each quiz question is worth 2 points for a total of 10 and 20 minutes will be given.
Each open question is worth 3 points for a total of 6 and 25 minutes will be given.
If the score is between 18 and 23 the student can either choose to accept the mark scored or to repeat the exam.
If the score is at least 24 the student can decide to undertake an oral interview to try and improve the mark or accept the mark as it is.

Zienkiewicz, O. C., Taylor, R. L., The Finite Element Method: Basic Formulation and Linear Problems, Editore: McGraw-Hill College, Anno edizione: 1987, ISBN: 9780070841741
Robert D. Cook, Finite Element Modeling for Stress Analysis, Editore: Wiley, Anno edizione: 1995, ISBN: 9780471107743
Claudio Gianini, Computational Structural Engineering - Automatic calculation of mechanical structures, Editore: CG CAE Sagl, Anno edizione: 2021, ISBN: 979-8485290849

Questo insegnamento fornisce le conoscenze di base delle armi, delle munizioni e degli esplosivi con riferimento alle loro tipologie, caratteristiche ed impiego, nonché alla possibilità di prevederne e gli effetti. Gli argomenti principali dell'insegnamento sono di seguito elencati: armi e munizioni, tecnologie di fabbricazione di armi e munizioni, esplosioni ed esplosivi, balistica interna, balistica esterna, balistica terminale, aspetti normativi e giuridici delle armi e degli esplosivi.

At the onset of a technological transition in which Fuel Cells and Batteries, the key electrochemical energy conversion and storage (EECS) devices, are starting to play key roles in mobility at all scales, the purpose of this course is to enable Mechanical Engineering students without previous knowledge in the fields of electrochemistry and physical chemistry, to achieve independence in approaching EECS science and technology problems. Specifically, this course will: (i) allow effective further self-study of the details available in the original literature; (ii) provide the basis for professional work in the EECS field, both in industry and academia. The mission of this course is thus to provide students with the key conceptual tools for critical and quantitative thinking of Fuel Cell and Battery Engineering fundamentals, oriented towards design and control activities, as well as integration in a wider system-oriented technological vision.

From the methodological standpoint, this is a self-contained course, specifically designed for Mechanical Engineering Students, that can be attended also by other Industrial Engineering Students with CVs lacking dedicated chemical and physical background. Special care has been devoted in the design of this course, on the one hand to provide the relevant physical and chemical essentials, and on the other hand to ensure the attainment of a fully technological treatment of the subject matter. Moreover, repetitions of contents conveyed in other eligible courses delivering information in EECS has been avoided with utmost thoroughness, so that this course can be fruitfully followed both by students who have or have not attended them, rendering this course fully independent from other ones offered by Politecnico di Milano.
In particular, the Students will:
i) acquire knowledge regarding the electrochemical and physico-chemical processes implemented in Fuel Cells and Batteries and controlling their operation under ideal and realistic conditions;
ii) become acquainted with the technological implementation of the above-mentioned processes in practically relevant devices;
iii) be exposed to the key experimental methods to assess and quantify the functional properties and performance of EECS devices;
iv) develop skills in the use of basic mathematical tools to model EECS devices and predict their operation and degradation. The basic modelling tools taught in this course will be modular, and can be naturally extended to more face sophisticated cases that the Students might encounter in their activities beyond the scope of this course.

Engineering Fundamentals of the Operation of Fuel Cells and Batteries. (a.i) Overview of main industrially relevant devices and their components. (a.ii) Operating principles and operation modes. (a.iii) Key governing equations: physico-chemical derivation. (a.iv) Representative solutions of governing equations. (a.v) Main measurement methods for performance evaluation and diagnostics. (a.vi) Processes underlying device control, degradation and safety.
Fuel Cell and Battery Technology. (b.i) State-of-the-art systems for automotive and other mobility applications. (b.ii) General characteristics of current lithium battery technologies: state of charge, discharge/charge, efficiency, state of health. (b.iii) Genereal characteristics of Polymer Electrolyte Fuel-Cells: transport processes and electrocatalysis, degradation. (b.iv) Next-generation fuel-cells and batteries for mobility: highlights and perspectives. (b.v) Engineering aspects of durability and safety. (b.vi) Fuel Cell and Battery technology from the circular economy viewpoint.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Each Student's evaluation will be based on two Tasks, detailed below.
(Task i) An Oral Exam, regarding the programme of the whole course, including Lessons and Laboratory Units.
The Aspects of the Learning Outcomes assessed with the Oral Exam refer to the level of understanding of the Course contents.
The oral exam consists in thematic questions, organized as follows: (a) 2 questions on the topics presented in the Course Section regarding Fuel Cells; (b) 2 questions on the topics presented in the Course Section regarding Batteries. One of the two questions of each Section will cover a theoretical topic and the other one will be oriented to applications or technological aspects.
The total score allotted to the Written Exam is 20/30: each correct answer contributes equally to the total score.
(Task ii) Elaboration of a Project addressing a topic among those expounded in the Course.
The Aspects of the Learning Outcomes assessed with the Project refer to the capability of critically thinking, correctly expounding and logically linking the topics presented in the Course.
The Project will consist in the following steps. (a) Freely select and check with the professor one of the topics presented during the Lessons or Laboratory Lessons of the Course. The project can be of one of the following types: (i) bibliographic analysis; (ii) critical review / elaboration of course contents; (iii) original computational / modelling aspects; (iv) experimental activity with related reporting. (b) Prepare a PowerPoint presentation: the PowerPoint file will have to be delivered to the Professor before the presentation, for archiving purposes. (c) Expound the presentation publicly in ca. 15 min. (d) Q&A session (ca. 5 min) in which the Student will answer questions, put by the Professor, on the contents of the presentation. The aim of the Q&A session is to assess the depth of the understanding of the topics expounded and the capability of justifying the statements made during the presentation.
The total score allotted to the Project is 10/30, with the following breakdown: (a) accuracy of the presentation of the subject matter (i.e. comprehensive and correct formalism): 2; (b) originality of the organization of the PowerPoint presentation (e.g. layout of the whole presentation and of the individual slides that helps to clarify the subject matter and establish conceptual links, extending the didactic material distributed during the Course): 2; (c) quality of the oral presentation (e.g. clearly elucidated conceptual points, capability of framing the background, showing confidence, avoiding fillers, conveying effectively the take-home message ): 2; (d) replies in the Q&A session: 4.
Both tasks will have to be performed in the same session.
NB - For the achievement of the score “30/30 with Honours”, the Student who has obtained a score of 30/30 in the two Tasks described above (points (i) and (ii)), will be asked one Additional Question. This additional question will assess the Student’s capability of critically and creatively linking advances aspects of the subject matter of the Course.

R.A. Huggins, Energy Storage: Fundamentals, Materials and Applications, 2nd ed., Editore: Springer, Anno edizione: 2016, ISBN: 978-3-319-21238-8
Note: Reference text for section of course regarding Batteries. Recommended reading: chapters 9-24.
Ryan O'Hayre, Suk-Won Cha, Whitney Colella, Fritz B. Prinz, Fuel Cell Fundamentals, Editore: Wiley, Anno edizione: 2016, ISBN: 9781119114154
Note: Reference text for section of course regarding Fuel Cells

The course aims at providing knowledge about organic materials for electronics, optoelectronics and optics and related devices. The course deals with conducting materials, photochromic materials, liquid crystals, as distinct topics. For each class of materials, molecular structure-properties relationships are studied also considering the possible technological applications. Attention is focused on the design of devices such as LEDs, transistors, photovoltaic cells, LCDs, sensors and smart windows. Finally, techniques for the deposition of the organic materials into films are considered.

The expected learning outcomes are:
aquiring knowledge of the principles of molecular engineering of electronic materials, i.e. organic semiconductors, and optically-active materials (DdD1);
aquiring knowledge of the structure to property relationship, with specific focus on optical and electrical properties (DdD1);
aquiring ability to apply the principles of molecular engineering to design functional materials for specific applications (DdD2);
aquiring the ability to predict the properties of a functional material, given the molecular structure (DdD2);
aquiring knowledge of the working principles of the main electronic devices, their characteristics, components and architecture (DdD1);
aquiring ability to apply the above knowledge to a critical description and discussion of the devices and related materials properties, limitations and developments (DdD2).
Overall, these learning outcomes are expected to provide the student basic knowledge tools necessary to i) understand the technology trends and i) perform future activities aimed at the development of materials for electronics optoelectronics and smart optics.

Functional materials:
Basic principles.
Fundamentals on organic functional materials: molecular skeleton, side groups; the electronic effect of side groups.
Conjugated materials
Molecular design: from localized chemical bonding to delocalized chemical bonding (LCAO, the frontier energy levels)
Structure to properties relationship: the UV-vis spectroscopy
Polyacetylene: structure, synthesis, electrical properties; Shirakawa films
Doping: chemical and electrochemical processes; charge carriers in organic materials; fundamentals of charge transport
The deactivation from the excited state: the emissive properties (photoluminescence)
Applications of conducting polymers: OLED, photovoltaic cells, thin film transistors, smart windows, sensors
Liquid crystals
Fundamentals, mesogens, main LC phases; polymer liquid crystals; LC embedded in polymer matrix (preparation methods, drop configuration, smart windows).
Optical thermometers. Smart windows. Liquid crystal displays.
Photochromic and thermochromic materials
Fundamentals, main families
Applications: ophthalmic lenses, inks
See bibliography for suggested books (covering more than the programme of the course). Additional material or lecture notes are given by the lecturer.

Prova scritta obbligatoria, senza prove in itinere
A written examination, which consists in:
A numerical exercise on a device: OFETs, photovoltaic cells, OLEDs or smart windows and filters.
The exercise aims at applying knowledge to calculate the efficiency or the main characteristics of a device starting from given experimental data. Regarding this part, not only the correct calculation is assessed but also the proper use of significant decimals and units of measurement. Then, student is required to give a critical assessment of the performance with regards to the materials amployed as well as the manufacturing process. Similarly, student is required to assign specific devices to the corresponding materials on the basis of the materials structure and processing. The assignment has to be properly supported.
An open question of one of the main topics of the course
In the open question, the student is required to clearly describe and critically discuss the proposed topic. Not only the knowledge about the topic is assessed, but also the correct use of a proper scientific language and clarity in the description.
An exercise on the structure-to-property relationship
It aims at evaluating the ability of the student to apply the acquired knowledge on molecular design to a case study, finding the right key to solve the problem.
A series of multiple choice questions
It allows to assess the knowledge and comprehension throughout the subjets.

Functional Organic and Polymeric Materials, Editore: Ed. by T.H. Richardson - Wiley, ISBN: 0471987247
Handbook of Conducting Polymers, Editore: Ed. by T.A. Skotheim - Marcel Dekker inc., Anno edizione: 1986, ISBN: 0-8247-7395-0
Handbook of Conducting Polymers, Editore: Ed. by T.A. Skotheim, R.L. Elsenbaumer, J.R. Reynolds - Marcel Dekker, Anno edizione: 1998, ISBN: 0-8247-0050-3
S.O. Kasap, Optoelectronics and Photonics: Principles and Practices, Editore: Prentice Hall, Anno edizione: 2001, ISBN: 0-201-61087-6
Organic Photochromic and Thermochromic Compounds, Editore: Ed. by J.C. Crano and R.J. Guglielmetti - Plenum Press - New York, Anno edizione: 1999, ISBN: 0-306-45882-9

Il corso si propone di introdurre gli studenti agli aspetti fondamentali che caratterizzano la disciplina dell'Elettronica Analogica per microsistemi. In particolare, il corso affronta i concetti fondamentali dell'elaborazione delle informazioni con l'elettronica analogica, concentrandosi anche sull'esame del comportamento fisico di componenti e circuiti analogici, in modo che lo studente possa valutare la loro influenza sulle prestazioni del sistema reale (amplificazione, risposta in frequenza, ...). Per questo motivo, durante il corso verranno introdotti anche i concetti di base sui principi di funzionamento dei dispositivi elettronici analogici elementari.

Il corso si propone di introdurre gli studenti agli aspetti fondamentali che caratterizzano la disciplina dell'Elettronica Digitale per microsistemi. In particolare, il corso affronta i concetti fondamentali dell'elaborazione delle informazioni con l'elettronica digitale, concentrandosi anche sull'esame del comportamento fisico dei componenti e dei circuiti digitali, in modo che lo studente possa valutare la loro influenza sulle prestazioni del sistema reale (velocità, dissipazione di potenza...). Per questo motivo, durante il corso verranno introdotti anche i concetti di base sui principi di funzionamento dei dispositivi elettronici digitali elementari.

The course begins with an introduction to atomic and molecular structures, followed by an analysis of the different types of intra- and inter-molecular interactions. These interactions are used to determine the potential energy of materials and to classify them into the following key categories: ionic, covalent, molecular, macromolecular, and metallic.
Model potentials appropriate for describing these interactions and the molecular arrangement at the nanoscale will be examined in detail, considering both crystalline and amorphous domains, as well as short- and long-range order. Particular attention will be given to the correlations between atomic, molecular, and supramolecular structures and the resulting macroscopic properties of materials (structure–property relationships). The course also considers the principal tools for describing crystal structures in the solid state, introducing the mathematical and geometrical concepts required for their analysis.
Building on these foundations, the fundamentals of materials physics will be presented to support the understanding of key structural, electrical, optical, and thermal properties. Selected characterization methods will be introduced, including X-ray diffraction (XRD), vibrational spectroscopy, molecular modeling, and differential scanning calorimetry (DSC).

After attending the course and following a positive evaluation, regarding the Dublin Descriptor 1 (DD1) of knowledge and understanding, the students will be able to:
describe intra- and inter-molecular interactions and evaluate the potential energy of materials using appropriate model potentials;
understand the molecular and crystal structure of materials through the use of suitable geometrical, graphical, and mathematical tools;
demonstrate knowledge of key characterization methods such as X-ray diffraction, vibrational spectroscopy, molecular modeling, differential scanning calorimetry, and dynamic thermo-mechanical analysis, and their practical applications.
Regarding the DD2 of applying knowledge and understanding, the students will be able to:
analyze and interpret the structural features of different classes of materials (ionic, covalent, molecular, macromolecular, and metallic) at various length scales;
compute and correlate macroscopic properties—electrical, optical, thermal, and mechanical—with micro- and nano-scale structure, using appropriate physical and mathematical models.