Industrial Safety and Risk Engineering

Source models: single-phase liquid outflow, outflow gaseous phase, two-phase outflow, formation of aerosols and rain - out, sizing and evaporation from pool. Dispersion models: punctual models, integral models and computational fluid dynamics . Models of explosions : TNT equivalent model, TNO, Multi -Energy , Baker - Strehlow. Fire models

1. Introduzione all'apprendimento statistico. Il tradeoff tra bias e varianza.
2. La maledizione della dimensionalità e la riduzione della dimensionalità. Analisi delle componenti principali.
3. Classificazione non supervisionata. Clustering gerarchico, clustering K-means.
4. Modelli lineari. Regressione lineare semplice e multipla. Adattamento del modello attraverso i minimi quadrati ordinari e la massima verosimiglianza, valutazione
dell'accuratezza delle stime dei coefficienti, valutazione dell'accuratezza del modello, intervalli di previsione. Predittori qualitativi e interazioni. Selezione del modello e
regolarizzazione: metodi di shrinkage (ridge regression e lasso), metodi di riduzione della dimensionalità.
5. Classificazione supervisionata. Regressione logistica e stima di massima verosimiglianza. Analisi discriminante lineare e quadratica.
6. Metodi di campionamento. Cross-validation e bootstrap.
7. Metodi basati sugli alberi. Alberi di classificazione e regressione. Bagging, random forests, boosting.

Difference between safety- and security-related risks. Risk sources and typologies and risk appetite. Techniques for open source risk identification and business intelligence. Integrated functional analysis and representation methods of business processes. Deductive and inductive logic and logic operations. Risk spectrum definition. Critical paths and critical elements identification. Probability calculation (values, strength and cost). Risk in project management. Organisational forms and risk prevention. Culture and leadership as tools for risk prevention. Risk perception. Sanction and reward in risk management. Decision making strategies in risk management. Decision making models. Managerial perspective of the risk prevention Law. International standard and approach in risk management. Emerging risks.

Operations Research (O.R.) is the branch of applied mathematics dealing with quantitative methods to analyze and solve complex real-world decision-making problems. The course covers some of the fundamental concepts and methods of O.R. pertaining to graph optimization, linear programming and integer linear programming. The emphasis is on optimization models and efficient algorithms with a wide range of important applications in engineering and management.

Knowledge and understanding (DdD 1)
The students will learn:

• the mathematical language of optimization models and some important classes of models
• the main properties and algorithms (including the worst case complexity) of/for the following graph optimization problems: minimum cost spanning tree, shortest path and maximum flow
• the critical path method for project scheduling
• the geometrical and algebraic aspects of Linear Programming (LP), and an LP algorithm
• the main properties of LP duality, including weak/strong duality and the complementary slackness optimality conditions
• the economical interpretation of the dual of some LP problems
• the main characteristics of Integer Linear Programming (ILP) problems
• the cutting plane method with fractional Gomory cuts
• the Branch-and-Bound method for ILP and other combinatorial optimization problems.
  Applying knowledge and understanding (DdD 2)
  The students will be able to:
• build optimization models starting from the decision problem descriptions, solve them using a modelling language based on Python and a state-of-the-art solver, and interpret the output
• identify an appropriate graph optimization algorithm to tackle a given decision problem and apply it to small examples
• apply the LP method to textbook examples
• construct the dual of LP problems in explicit and parametric form
• apply the studied ILP methods (Branch-and-Bound method, cutting plane method with fractional Gomory cuts) to small examples
• leverage on the acquired theoretical and algorithmic knowledge to answer simple questions.
  Learning skills (DdD 3, DdD 5)
  The students will learn how to tackle complex decision-making problems with a solid mathematical and algorithmic approach, which can be adapted and extended to deal with a variety of real-world problems.

1. Introduction
Decision-making problems. Main steps of an O.R. study. Different types of optimization (mathematical programming) problems. Optimization models (decision variables, objective function, constraints) and modeling techniques.
2. Graph and network optimization
Optimum spanning trees. Shortest path problems: algorithms for the main variants (including Dynamic programming for acyclic graphs). Application to project scheduling: critial path method and Gantt diagrams. Maximum flows: Ford-Fulkerson algorithm and maximum flow-minimum cut theorem. Minimum cost flows, matching in bipartite graphs. An example of NP-hard network optimization problems: the Traveling salesman problem.
3. Linear Programming (LP)
LP models. Geometric aspects (vertices of the feasible region) and algebraic aspects (basic feasible solutions). Fundamental properties of linear programming. The Simplex method. LP duality theory: pair of dual problems, weak and strong duality, complementary slackness conditions. Economic interpretation. Sensitivity analysis. Special cases: assignment and transportation problems.
4. Integer Linear Programming (ILP)
ILP models for, among others, transportation, routing, scheduling and location problems. Formulations and linear programming relaxation. Exact methods: Branch-and-Bound algorithm, cutting plane method with fractional Gomory cuts.
Time permitting we will review some basics of computational complexity (recognition problems, classes P and NP, polynomial-time reductions, NP-complete and NP-hard problems) and introduce basic heuristic algorithms (greedy and local search).
A couple of topics will be assigned for independent study (e.g. LP sensitivity analysis) prior to sessions devoted to exercises or computer laboratory activities. There will be computer lab meetings and computer lab assignments.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Valutazione continua facoltativa (a scelta dello studente)
A written exam which covers all the material presented in the lectures, the sessions devoted to the exercises, and the computer laboratory sessions and assignments. The first part of the written exam will be closed book and the last part will be open book. A few points will be assigned based on some formative assesments during the semester, further details will be provided at the beginning of the course.
The exam consists of several questions aimed at evaluating the level of (applying) knowledge and understanding of the main concepts, models, results and methods covered in the course as specified in the expected learning outcomes. In particular, it includes modeling questions, the solution of numerical problems using appropriate algorithms, and theoretical questions related to the main concepts, methods and results. (DdD 1, DdD 2, DdD3)

All the course information and material will be available on WeBeep.
F. Hillier, G.J. Lieberman, Introduction to Operations Research, Editore: McGraw-Hill, Anno edizione: 2021
Note: 11th Edition
R.K. Ahuja, T.L. Magnanti, J.B. Orlin, Network flows. Theory, algorithms and applications, Editore: Prentice Hall, Anno edizione: 1993
D. Bertsimas, J. Tsitsiklis, Introduction to Linear Optimization, Editore: Athena Scientific, Anno edizione: 1997
M. Fischetti, Introduction to Mathematical Optimization, Anno edizione: 2019

This course covers empirical strategies aimed at answering economic research questions. The course illustrates several applied econometric models, and develops the skills needed to plan and carry on empirical research projects. Since most applied economic research examines questions with direct policy or managerial implications, this course will clarify the difference between correlation and causal links. Purely predictive methods, grounded in correlation and regression analysis will be presented and compared with alternative estimation techniques (such as instrumental variables) more focused on the analysis of causal effects. The goal of the course is to provide valuable econometric tools for students majoring in several fields, from micro/macro/international/industrial economics to finance, and management.
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:
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

With respect to the first learning goal, at the end of the course students will be able to:
Understand in depth the key aspects of the linear regression model and the relevance of the underlying standard assumptions
Understand the variants of the linear regression model to be used when the standard assumptions do not hold
Understand why the linear regression model is not appropriate when the dependent variable is discrete, truncated or censored and which are the appropriate models to be used in those cases
With respect to the second learning goal, at the end of the course students will be able to:
Select the appropriate econometric model to be applied in practical economic situations.
Interpret the output of econometric packages implementing econometric models
Test the validity of the underlying assumptions for each model
Use econometric models to support economic decisions

Overview
The agenda includes regression, instrumental variables, differences-in-differences, probit, logit, tobit, survival analysis. One of the goals is to equip students with working knowledge of the tools of probability and statistics, skills in data handling and statistical programming, and an understanding of the models and methods of applied econometrics. To this aim, problem sets with both analytical and computer-exercise components will be a relevant part of the course. The cases will be illustrated and discussed using the open source econometric package Gretl ( gretl.sourceforge.net ).
Main topics
0. Basics refresher: estimation and testing theory, matrix algebra
1. The linear multiple regression model under standard assumptions: estimation through Ordinary Least Squares, reading and interpreting the regression output, using the model for prediction.
2. Checking assumptions of the regression model: functional form, multicollinearity, heteroskedasticity, autocorrelation, non-normality
3. Using the model to investigate causal relationships: omitted variables, endogenous regressors and the method of instrumental variables
4. Using the model to analyze the effectiveness of policies and managerial choice: the differences-in-differences method
5. Analysis of binary variables (probit and logit models)
6. Analysis of categorical variables (multinomial logit models)
7. Analysis of ordinal variables (ordered probit models)
8. Analysis of count variables (Poisson regression)
9. Analysis of truncated and censored variables (Tobit models)
10. Analysis of durations (survival model

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, senza revisioni periodiche, con presentazione/discussione finale
(i) Written exam (80 minutes, weight 60%). The written exam is based on two exercises (the first is on the topics 1 to 4 illustrated above; the second is on the topics 5 to 10). The main purpose of the written exam is to assess the achievement of the second learning goal and the associated learning objectives (ability to select the appropriate model to answer research questions, to read the output of econometric packages, to perfom the appropriate tests, to use the models to support economic decisions)
(ii) Oral exam (15 minutes, weight 40%). The main purpose of the oral exam is to assess the achievement of the first learning goal and the associated learning objectives (understanding of the main theoretical aspects of econometric models). The oral exam has to be taken after the written exam, not necessarily in the same call.
(iii) Non-compulsory team project work (2 students): a paper about 10/15 pages long, where some of the techniques illustrated in the course is applied to a real problem; the paper has to be illustrated in a 30 minutes presentation, possibly via skype; the project work may increase the final mark by at most 2/30. The project work gives you the opportunity to get an hands-on perspective on the discipline. Highly recommended if you plan to include econometric models in your final thesis, or if you think that a deep understanding of statistics in general and econometrics in particular is a valuable asset for your future.

William Greene, Econometric Analysis, 7th Ed., Editore: Pearson, Anno edizione: 2012, ISBN: 9780131395381 http://pages.stern.nyu.edu/~wgreene/Text/econometricanalysis.htm
Note: selected chapters

The course aims to provide the necessary competences to the students to perform the risk assessment for workers exposed to hazard of chemical, physical and biologica1 origin; as well as to perform experimental verifications for risk assessment and to define the improving actions.
1. History and principles of the prevention. Signs of biology, anatomy and physiology. Changes happened in the organization of the job of the countries industrialized. Definition of danger, risk, accident, professional illness, job-in partnership illness
2. The risks of chemical origin: Principles of toxicology. Toxicological Risk (general concepts, toxic effects of chemical substances, relationships dose-response and dose-effect, pathways of exposure, metabolism and elimination of toxicants, carcinogenesis, mutagenesis and teratogenesis). Toxicology of Metals, Gases and Solvents. Estimation of generations, techniques for planning of the investigations and evaluation of the results, analysis of the principal methods of environmental improvement.
3. The risks of physical nature. The microclimate, the energetic balance applied to the human body, criterions of evaluation for moderate environments, criterions of evaluation for warm severe environments, criterions of evaluation for cold severe environments.
The noise, characteristics of the sounds, techniques of measure and evaluation of the data. Vibrations, techniques of measure.
4. The risks of biological nature: Definitions of the principal classes of biological agents: Bacteria, Virus, infecting yeast and mould, allergens and profiles of risk.
5. Occupational Health. Signs to the Professional Diseases: professional cancer, renal and liver pathologies, allergies and dermatopathies, muscle-skeletal disorders, vasculopathies and neuropathies. Signs of Ergonomics and Epidemiology

Modern complex industrial systems require a systematic approach to design and operation, with specified safety and reliability constraints/objectives (safety-based and reliability-based design and operation).
The goal of this course is to provide the students with the adequate competences on methods and computational tools for the evaluation, the analysis and the control of the risk associated to the operation of industrial equipment and systems. These competences, typical of safety and reliability analysts and managers, are necessary in all modern engineering for the design and operation of safe and reliable systems.

PART A
The student knows:

• ELO A.1 - the basics of probability theory, system analysis and simulation methods for reliability and availability assessments;
• ELO A.2 - the basics of maintenance engineering.
  The student is able to:
• ELO A.3 - estimate reliability and availability indicators of industrial equipment and systems;
• ELO A.4 - develop stochastic simulation methods for estimating system reliability and availability indicators;
• ELO A.5 - apply methods of maintenance engineering to industrial equipment and systems.
  PART B
  ELO B.1 - the student understands the concept of risk and the probabilistic framework for its assessment;
  ELO B.2 - the student is able to apply the methods and tools for the probabilistic risk assessment of industrial equipment and systems;
  ELO B.3 - The student knows the methodological tools to treat the uncertainty in the reliability and risk assessments and can make judgments on the confidence in the results obtained, for robust decision-making.

PART A
Basics of probability theoryfor applications to reliability analysis and risk assessment (ELO A.1);
Estimationof reliability parameters from field data(ELO A.3);
Reliability of simple systems:series, parallel, redundancies, standby (ELO A.3);
Reliability and availability of complex systemssubject to realistic procedures of inspection, maintenance, repair, renewal (ELO A.3);
Monte Carlo simulation methods for reliability and availability analysis:stochastic simulation framework; random sampling; definite integrals estimation; variance reduction techniques to increase simulation efficiency,estimation of reliability and availability of complex systems (ELO A.4);
Maintenance engineering (ELOs A.2 and A.5).
PART II
Risk:qualitative and quantitative definitions (ELO B.1);
Probabilistic risk assessment framework:identification and quantification of accident sequences (Failure Mode and Criticality Analysis, Hazard Operability Analysis, Fault and Event Tree Analyses, and Bayesian Belief Networks); risk curves and matrices; risk analysis as a tool in support of regulatory licensing and operating requirements (ELOs B.2 and B.3);
Dependent failures (ELO B.2);
Importance measures (ELOs B.2 and B.3);
Uncertainty and Sensitivity Analysis (ELOs B.2 and B.3)
Seminars on advanced topics (e.g. digitalization in Industry 4.0, integrated deterministic and probabilistic safety assessment, Prognostics and Health Management);
Case studies taken from real industrial systems and plants will be illustrated, and quantitative exercise classes will be carried out in support to the comprehension of the material covered in class.

Prova scritta obbligatoria, senza prove in itinere
Modalità di valutazione
The evaluation consists in a written exam consisting of numerical exercises theory questions.
The numerical exercises will evaluate the student abilities in applying the techniques for quantifying the reliability and availability and control the risk of industrial equipment and systems (ELOs A.3 and B.2).
The theory questions aimsat verifying the student understanding of the risk concept, the probabilistic framework for its assessment, the basics of probability theory and stochastic methods for reliability, availability and risk analysis, dependent failures, importance measures, the maintenance engineering approaches (ELOs -A.5 and B.1, B.2). Furthermore, it verifies the student ability of making judgments on the confidence in the results obtained, for robust decision-making (ELO B.3).

The course provides fundamental notions aimed at building solid awareness of the responsibilities arising from technical activities.
Specifically, the course is oriented towards providing a general overview of the rights and duties of technical experts, along with the identification of tools and procedures for legal protection (such as insurance, contractual clauses). Furthermore, the course aims to illustrate the rules protecting inventions - copyrights, and patents - granting the student immediate access to reference sources and applicable regulations, also through the analysis of practical cases.
The last part of the course offers an analysis of the legislation related to artificial intelligence and its evolution.

Technology-driven businesses are nowadays struggling to keep up with the rapid pace of technology innovation and change, such as the increasing complexity of modern cyber-physical systems. In this context, Technology Risk Governance (TRG) comprises the set of strategies, methods and organisational models that different organisations put in place for understanding, assessing and managing technology-related risks. This course aims at transferring to students theoretical and practical knowledge on TRG through in class discussion of real cases and testimonials from companies, which will cover a wide spectrum of industrial and service systems (e.g. manufacturing, energy, transport).
The course addresses the state-of-the-art approaches, methods and models for supporting risk-informed decisions in managing complex socio-technical systems, from technology selection to system design, from organisational risk factors to regulation and governance.

After successful completion of this course module students:
Will demonstrate the ability of identifying and analysing technology risks in cyber-physical systems, eventually discussing alternative mitigation options (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative technology risk assessment methods at different system life cycle stages (Applying Knowledge and understanding);
Will be able to identify and critically discuss emerging relevant challenges to the governance of technology risks in cyber-physical systems, leveraging on state-of-the art knowledge (Making Judgements and Learning skills), and prepare a technical report on technology risk assessment (Communication).

The course addresses the state-of-the-art approaches, methods and models for supporting risk-informed decisions in managing complex socio-technical systems, from technology selection to system design, from organisational risk factors to regulation and governance. More specifically:
Risk governance of new and emerging technologies. Technology outlook and risk assessment methods for technology foresight and selection. Discussion of application cases.
Risk analysis of complex socio-technical systems. Risk definition, modelling and reporting under the precautionary principle; Risk engineering methods (with exercises on FMECA, FTA-ETA, PRA). Safety and information security analysis of cyber-physical systems: differences and relationships.
Human and Organisational risks in complex socio-technical systems. Modelling and analysis of human and organisational risk factors; Risk Management of safety-critical and mission-critical systems (the High Reliability Organisation theory). Critical incident analysis case discussion. Discussion of industrial practices; Testimonials.
Risk governance of interdependent systems. Characteristics of networked cyber-physical systems. Types of interdependencies. Modelling tools for vulnerability and interdependency analysis. Risk governance models and processes, discussion of cases and testimonials from companies.
The learning experience of this course includes, in addition to face-to-face lectures, numerical exercises, case discussions, a group project, real examples and interactions with guest speakers from industry.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Group Assignment: Groups of students (max 3 students/group) will be engaged in actively applying risk management principles, models and methods by means of a major assignment. The assignment may take the form of a Technology Risk Assessment study, or an ex-post systematic analysis of a technology-driven industrial accident, by making use of the methods and tools presented in class. The assignment is intended to evaluate the student’s ability to: i) choose and apply the most appropriate approach and methods given the key features of the complex socio-technical system at stake; ii) examine and assessing the suitability of an organization’s technology risk governance model; iii) preparing a technical report on technology risk governance. The deliverable consists of a final written report;
During classes some minor assignments will be suggested, as an extension of in-class exercises, to be completed in groups on a voluntary basis.
Written test: focuses on analytical problems in technology risk assessment, aiming at evaluating the student’s ability of using proper methods and correctly interpreting results.
Grading: Student evaluation will be based on course assignments:
Group assignment: 50%;
Written test: 50%;
The submission of minor assignments may award the student with max 0.5/30 point each.

Course instructor, Teaching notes, Case texts and suggested readings
Note: Available on Beep course web page
Bedford, Tim & Cooke, Roger M, Probabilistic risk analysis: foundations and methods, Editore: Cambridge University Press, Anno edizione: 2012 https://www.cambridge.org/core/books/probabilistic-risk-analysis/E7AB7D462EA12249CA33D828B6A44ECF
Reason J. T., Managing the risks of organizational accidents, Editore: Routledge-Ashgate, Anno edizione: 1997

The course is offered in a 5-CFU course (ARTIFICIAL INTELLIGENCE FOR RISK ENGINEERING). The following detailed program defines goals, learning outcomes and topics for the course.
The objective of the course is to provide students with knowledge and understanding of Artificial Intelligence (AI) methods for their use in risk engineering. The course presents frameworks, methods and techniques of AI for the solution of risk engineering tasks in industry.

The Expected Learning Outcomes (ELO) are as follows.
The student knows:
ELO 1 - the frameworks, methods and techniques of AI and their implementation in risk engineering for industrial applications
The student understands:
ELO 2 - the strengths and limitations of AI-based risk assessment and management
The student is able to:
ELO 3 - exploit AI surrogate modeling for efficient simulation, within a computational risk engineering framework
ELO 4 - process by AI the monitoring data recorded by sensors allocated on components and systems, within a framework of prognostics and health management (PHM) by fault detection, fault diagnostics and failure prediction for condition-based risk engineering
ELO 5 - extract knowledge for supporting risk engineering by Natural Language Processing and Large Language Modeling of text from inspection and safety reports
The student can communicate:
ELO 6 - the development and application of AI algorithms and methods for risk engineering, and the interpretation of the results, with focus on industrial equipment and systems

Fundamentals of Risk Engineering and AI:
Fundamentals of reliability, safety, hazard, vulnerability, risk and resilience
Model-based and AI-driven risk engineering
strengths and limitations of AI-based risk engineering
Methods and Techniques of AI for Risk Engineering:
AI-based surrogate models for efficient simulation and for processing monitoring data, within a framework of PHM for condition-based risk prediction
AutoEncoders, Convolutional, Recurrent and Physics-Informed Neural Networks, and Reinforcement Learning for risk assessment and management
Transfer Learning and Domain Adaptation for safety and risk analysis
Natural Language Processing for risk identification

Prova scritta obbligatoria, senza prove in itinere
The evaluation consists of a final written exam and possibly a project work.

Enrico Zio, An Introduction to the Basics of Reliability and Risk Analysis, Editore: World Scientific
Enrico Zio, Computational methods for reliability and risk analysis, Editore: World Scientific
Enrico Zio, Piero Baraldi, Francesco Cadini, Basics of Reliability and Risk Analysis: Worked Out Problems and Solutions, Editore: World Scientific

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

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

Le lezioni riguarderanno, in particolare, i seguenti argomenti:

• cenni sui combustibili e sui principali prodotti di combustione;
• fattori che possono influenzare l'innesco, lo sviluppo e l'evoluzione di un incendio;
• comportamento dell'incendio in base ai materiali coinvolti e alla potenza;
• sostanze estinguenti e modalità di contenimento/estinzione incendi;
• misure di prevenzione e protezione incendi;
• criteri di sopravvivenza (es. visibilità, effetti termici diretti e indiretti, tossicità);
• piani di gestione dell'emergenze incendi e modalità di esodo delle persone;
• cenni a norme e letteratura tecnica nell'ambito della sicurezza e prevenzione incendi;
• introduzione ai modelli dettagliati per la simulazione d'incendi.

The course focuses on NaTech (Natural Hazard Triggering Technological Disasters) risk assessment and management. NaTech events occur when natural hazards such as earthquakes, floods, or hurricanes impact industrial facilities, leading to fires, explosions, and toxic or radioactive releases.
These accidents can have severe social, environmental, and economic impacts and are often overlooked in disaster risk reduction frameworks.
The NaTech Risk Assessment requires a comprehensive understanding of the interdependencies between human, natural, and technological systems. Effective Natech risk management involves identifying potential hazards, assessing vulnerabilities, and implementing Natech-specific safety measures, as well as proper emergency procedures.
For this reason, it is important to define variables useful for characterizing the different types of natural events (such as wind speed for gusts, lightning energy, etc.) that can trigger industrial accidents and to define maps for the areas of interest. Historical analysis of accidents, databases, lessons learned, and case-studies will be considered. Models available for risk analysis, both short-cut and QRA models (where and how to insert the Na-Tech parameters), will be described and used.

This course aims at providing the student with fundamental criteria, processes and methods to manage operational and supply chain risks in uncertain business contexts and achieve operational resilience against unexpected disruptions. The student will learn and apply different risk modelling and analysis techniques, either qualitative and quantitative, in relation to specific application contexts. A clear understanding of the peculiarities and relevance of adopting risk-informed or resilience-driven decisions, at both strategic and operational level, is achieved through class discussion of real cases in different industrial sectors and seminars from industry managers.

After successful completion of this course the student:
Will demonstrate the ability of classifying and modelling different risk sources in operations and supply chains, eventually selecting sound mitigation strategies (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative risk assessment methods (Applying Knowledge and understanding);
Will be able to identify and critically discuss emerging relevant ORM&R challenges, leveraging on state-of-the art knowledge (Making Judgements and Learning skills), and editing a final report on the subject matters (Communication).

The course covers the following topics:
Introduction to Operations Risk Management. Operations strategy and Operations Risk Management (ORM). Classifications of operational risks. Integration of Operations Risk Management and Enterprise Risk Management. The Risk Management Process (ISO31000). Risk homeostasis.
Quantitative and Qualitative Risk Assessment. Anatomy of risk (the risk concept and fundamental definitions). Reference Risk Identification and Assessment Methods (ISO31010). Application of Monte Carlo Method to operations risk analysis.
Supply Chain Risk Management. Vulnerabilities of global Supply Chains, the case of COVId-19 pandemic. Operational and disruption risks in Supply Chains. Supply and Supplier Risk Management: Business Impact Analysis of supplier disruptions; FMECA-based supplier assessment; risk-based supplier segmentation. Risk mitigation strategies and the role of digital technologies. Exercises and discussion of cases.
Operational & Supply Chain Resilience. Core resilience functions and resilience capabilities. Business Continuity Management. The influence of Operations strategies and Supply Chain complexity on resilience. Business game and discussion of cases.
The learning experience of this course includes, in addition to face-to-face lectures, numerical exercises, case discussions, a group project, real examples and interactions with guest speakers from industry. Groups of students (max 3) will be engaged in a major assignment focusing on either a state-of-the-art review paper or an ex-post analysis of a supply chain disruption event. The final report will be part of the student assessment process (see next paragraph).

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Group Assignment: Groups of students (max 3 students per group) will be engaged in actively applying risk management and operational resilience principles, models and methods by means of a major assignment. The assignment may take the form of a state-of-the-art review paper, or an ex-post analysis of a supply chain disruption event, by making use of the methods and tools presented in class. The assignment is intended to evaluate the student’s ability of critically analysing a novel problem and discuss possible alternative solutions, by integrating different perspectives and contributions coming from the team members.
During classes some minor assignments will be suggested, as an extension of in-class exercises, to be completed in groups on a voluntary basis.
Written test: based on a mix of closed- and open-ended questions, it is intended to evaluate the student’s ability of selecting, justifying and applying the relevant knowledge to manage different sources of uncertainty in industrial operations.
Grading: Student evaluation is based on course assignments:
Group assignment: 50%;
Written test: 50%;
The submission of voluntary minor assignments may award the student with max 0.5/30 point each.

Course instructor, Teaching notes, Case texts and suggested readings
Note: Available on Beep course web page
Waters D., Supply Chain Risk Management: vulnerability and resilience in logistics, Editore: KoganPage, Anno edizione: 2011
Sheffi, Y, The Resilient Enterprise, Editore: The MIT Press, Anno edizione: 2005

Air Pollution. Particle Dynamics. Particle control. Technical elements for environmental risk analysis. Gravimetric chambers. Cyclones Collectors. Electrical Precipitators. Fabric Filters. Scrubbers. Gas absorption and adsorption. Equipments for handling emergency relief effluents: vapour-liquid separation; quench pools; flares. Water and first flush stormwater treatments. Grinding, Sedimentation Equalization Physical treatments. Polluted soils remediation.

The Risk Management Lab is a field-based experiential course in which teams of students address live safety and risk management challenges proposed by industrial companies, insurers or public institutions. Supported by faculty and tutors, students frame the problem, collect and analyze evidence, assess relevant technical and organizational risks, develop the proof-of-concept or a basic design of the proposed solution, and formulate implementable recommendations. Projects may concern industrial safety, critical infrastructure, operational and supply-chain risk, major projects risk management, climate risk or insurance and loss prevention. Each project concludes with a concise professional report and a final presentation to the partner organization.
The Risk Management Lab aims to enable students to:
Apply risk-engineering and risk-management methods to real organizational problems.
Integrate technical, human, organizational, economic and environmental perspectives in risk management.
Translate analytical findings into practical and implementable risk-management recommendations.
Understand how risk decisions are shaped by operational constraints, stakeholder interests, regulation and organizational capabilities.
Develop professional skills in teamwork, stakeholder engagement, and technical communication to risk specialists and managers

At the end of the Lab, students will be able to:
Define the organizational problem, decision context and scope of a live risk challenge.
Select and apply appropriate qualitative, semi-quantitative or quantitative risk analysis methods.
Collect, structure and assess evidence obtained from documents, data, interviews, and field observation.
Compare alternative risk treatment options using technical effectiveness, feasibility, cost, sustainability and stakeholder criteria.
Produce a concise, evidence-based professional risk report and present findings and recommendations to an executive or technical audience.
Demonstrate professional conduct, confidentiality and integrity.

The Risk Management Lab is an applied learning experience in which teams of students address live risk-management problems proposed by external organizations. The Lab connects the scientific and engineering foundations of the MSc in Industrial Safety and Risk Engineering with the organizational, economic and decision-making dimensions of risk management. Projects may involve risk analysis and treatment solutions for industrial facilities, infrastructure systems, construction and engineering projects, supply chains or public services. Whenever feasible, projects include stakeholder engagement activities such as interviews, direct observation of operations, analysis of organizational procedures and interaction with managers, engineers, safety professionals, risk managers, insurers and institutional stakeholders.
Each team is supported by:
a faculty supervisor;
a university tutor;
a partner organization;
common project milestones (presentation of risk management challenges by partner organizations, group formation, mid-term review, final presentation).
The Lab follows a reference risk management cycle and adopts a common methodological framework:
Problem framing
Definition and framing of organizational risk problems.
Stakeholder analysis and decision-context analysis.
System and hazards/threats Analysis
System boundaries, critical functions, assets, and processes.
Hazard, threat and vulnerability identification.
Risk analysis and assessment
Qualitative / quantitative risk assessment.
Effectiveness of current risk control measures.
Resilience, continuity and recovery.
Basic design or PoC of the proposed solution
Risk-treatment strategies.
Cost–benefit and multi-criteria decision analysis.
Risk governance, ownership and accountability.
Risk indicators and monitoring dashboards.
Recommendations for swift implementation
Criteria and strategy
Roadmap
Sustainability and societal implications of risk decisions.
Communication
Preparation of the professional report and executive presentation.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
a) Final Report (80%)

• Problem framing and understanding of the industrial/organizational/institutional context (20%)
• Quality and appropriateness of risk-analysis methods (25%)
• Evidence, assumptions and treatment of uncertainty (15%)
• Feasibility and decision usefulness of recommendations (20%)
  b) Final presentation (20%)
  Note: individual performance may be differentiated based on faculty and tutor observations on lack of substantial contribution or inappropriate student’s behaviours.

All sectors of our societies, from aircraft traffic to healthcare, electric grid and finance have been undergoing unprecedented levels of digitalization with beneficial consequences on efficiency and flexibility of services provided. However, this dependence on and seamless integration of technology into the daily activities and operations exposes these systems to various manmade and natural threats, with possible negative consequences on their security and even well-being of citizens. The constantly evolving threat landscape pushes the current concept of protection towards a resilience status. Moreover, the high interdependency and complexity of sectors require a multidisciplinary approach to educating the workforce called to safeguard it. Putting this strategy into practice, in turn, requires an unprecedented partnership and information sharing between the public and private sectors at all levels. After successful completion of the course, students will be able to identify the vulnerability of the critical sectors in our economies to cyber risks, and recognize how to tackle them from a public sector perspective in order to define policies and programs, as well as put in place actions required to govern it. More specifically, they should be able to: - acquire hands-on knowledge in identifying physical and cybersecurity concerns in the critical infrastructure systems and their centrality in modern societies (principal threats and challenges, who owns them) - gain understanding and critically analyse approaches and methods of risk assessment and mitigation of persistent threats and incidents (how are threats/risks assessed & mitigated, are they useful in paving the way to resilient systems?) - develop knowledge about the specificity and interrelatedness of various CI systems - analyse trends in the global system connected to the evolution of cyber risk, interpret how they affect government activities and define policies, programs and road maps for governing it - develop mathematical skills to model and forecast the risks - apply logic models to critical infrastructure protection - discover and apply complex theory to multiple scenarios.

The course ‘Accounting Finance & Control’ (AFC) aims at providing students with the state-of-art, theoretical frameworks and instruments to measure and manage the overall performance of a (for profit) enterprise
The course fits into the overall program curriculum pursuing some of the expected 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
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

At the end of the course, students will know and understand:
The main methods for assessing and reporting the financial and non-financial (e.g. ESG / sustainability) performance of an enterprise
The different drivers of value creation and the linkages among them
The goals, the structure and the processes of the Planning & Control (P&C) Cycle
The organisational role of the “Accounting, Finance and Control” Units in an enterprise and its evolution over time
Students will be able to:
Apply the methods and models discussed during the course to real cases (e.g., to enterprises that belong to different sectors or have different organizational structures)
Design tailored performance measurement systems (e.g., systems that match the goals and the peculiarities of real enterprises)
Prepare performance reports tailored to the information needs of different stakeholders
Read and interpret the financial and non-financial performance of an enterprise (and of its constituencies)

The context:
The “Accounting, Finance and Control” (AFC) domain: the role of financial accountants and controllers and its evolution over time
The “AFC” organizational unit within the enterprise
Financial Accounting:
The multidimensional nature of financial accounting and its role and evolution over time
The concept of group of companies and consolidated financial statements
Corporate Performance Measurement:
Accounting-based Performance Measures. The analysis of consolidated financial statements of a business group
Value Based indicators: Discounted Cash Flow techniques; Enterprise Value vs. Equity Value; the calculation of Free Cash Flows; the Cost of Capital; Relative Valuation
Value Drivers (non-financial performance measures and risk indicators)
The integrated Planning & Control Cycle:
The “Planning” phase: the elaboration of operating; capital and cash flow budgets; and financial planning
The “Control” phase: periodic management reporting; the structure and content of management reports; corporate dashboards and balanced scorecards
Measuring and reporting performance of internal responsibility centers (business units, divisions, functions); corporate costs allocation and transfer pricing

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Altro
For attending students, the assessment is based on a combination of in-class applied activities and final individual assessment. This format allows students to progressively build part of their final grade during the semester and to apply the methods discussed in class to real-world cases.
Two hackathons (40%), held during the semester, aimed at assessing students’ ability to apply the methods presented in the course to real-world cases. The participation to both hackathons is mandatory and the mark of the hackathons cannot be refused and it remains valid for one year.
Written test (60%), which aims at assessing students' knowledge and full comprehension of key concepts, methods and tools illustrated during the course (with particular focus on pre-requirements for their application, pros and cons of alternative solutions, etc.)
Conditioned Oral test (+/- 2 points/ fail), which aims at assessing students’ capability to choose the most appropriate solution among the different alternatives according to the peculiarities of the application context.
For non-attending students and for students who receive an insufficient grade (<18) in the hackathons, the assessment consists of two parts:
Written test (50%), which aims at assessing students' knowledge and full comprehension of key concepts, methods and tools illustrated during the course (with particular focus on pre-requirements for their application, pros and cons of alternative solutions, etc.)
Oral test (50%), the oral examination is mandatory for non-attending students and has a substantial impact on the final grade. It is a comprehensive individual assessment aimed at evaluating students’ full comprehension of all the course concepts, and their ability to select, apply and justify the most appropriate methods and solution among different alternatives, considering the specific features of the application context.

Arnaboldi, A. Azzone, G. and Giorgino, M., Performance Measurement and Management for Engineers, Editore: Elsevier, Anno edizione: 2014, ISBN: 9780128019023
Anthony R. and Govindarajan V., Management Control Systems, Editore: McGraw-Hill Higher Education, Anno edizione: 2006, ISBN: 9780072819311

Big data and IOT are crucial concepts in the Industry 4.0 framework and the rapid evolution of measurement instrumentation is changing how measurements are performed. The recent developments in the field of sensors enable the description of physical phenomena at an incredibly low cost. As a matter of fact, the developments of novel sensors, data acquisition techniques, and data analysis procedures imply the necessity of deep metrological knowledge for an automation engineer.
The teaching aims at helping the students in the selection of the proper transducers for mechanical and thermal control applications, by describing the main categories of mechanical and thermal instrumentation from both a theoretical and a practical point of view. In addition to a description of the sensors that nowadays can be used for different applications, the teaching will focus on identifying the generic properties of instruments that can be used to select and compare the optimal instrumentation and to design smart sensing infrastructures. In this way, the student will be prepared to face the rapid evolution that characterizes the world of metrology in the industry 4.0 era.

At the end of the teaching, the student is expected to reach the following learning outcomes
Knowledge and comprehension (Dublin Descriptor 1, DD1)
Traceability and calibration
measurement uncertainty
Metrology
Ability in the application of knowledge (DD2)
prepare a setup for the acquisition of data coming from the most common measurement instruments
compute the measurement uncertainty in accordance with the ISO GUM
to design fit-to-purpose measurement chains for specific mechanical and thermal applications
Authonomy in judgement (DD3)
select the best trasducer for the majority of mechanical and thermal measurements.
compare two similar transducers by analyzing their datasheet and their metrological characteristics
identify the correct calibration procedure for the majority of mechanical and thermal sensors
Communication skills (DD4)
Students that decide to present the project instead of the written exam will learn how to work in team and how to present the results of a project
All the competences listed above will be developed relying on the theoretical lectures and on the laboratory experiences, that are crucial for a deep understanding of the most common problems that have to be faced during the automation engineer working life.

Generalized performances of measurement instruments
Uncertainty; Static and dynamic performances of measurement instruments; generalized theory of measurement instruments; load effect.
Fourier Analysis; dynamic performances of measurement systems; time response of first- and second-order systems. Experimental identification of response of first- and second-order systems; edge computing and smart sensing infrastructures.
Strain measurements
Introduction to strain gauges; calibration, Wheatstone bridge measurement circuits; compensation of thermal effects and improvement of sensitivity.
Vision-based sensors
Non-contact optical transducers: Laser triangulation sensors; Time of Flight lasers and Cameras, Laser Doppler vibrometers and interferometers. Vision-based systems and machine vision. Cameras for 2D and 3D machine vision applications; most common algorithms for machine vision
Non-contact temperature measurements
Rapid recall to thermal resistances, thermistors, thermocouples. Infra-red sensors: theoretical principles. Pyrometers, dual-color pyrometer. IR cameras. Experimental identification of emissivity
Each topic is treated theoretically in a classroom lecture. Students can use the different measurement instruments and analyze the experimental data according to the procedures learned during the theoretical lectures in the following laboratory experience.
There will be a relevant collaboration with company leaders in the field of measurement for automation. One or more companies will provide assignments to students, that will use the knowledge developed during the course to propose a solution, that will be presented to the company during a pitch.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The exam is a Project-Based Assessment
1. Project Assignment

• Each student or group of students is assigned a project topic related to measurement systems and data analysis.
  2. Laboratory Component
• Students will perform supervised or unsupervised experiments in lab settings, using Polimi instrumentation, to to collect data relevant to their project topic. Students are required to record data and troubleshoot normal issues that arise during experiments.
  3. Independent Research and Analysis:
• In supervised classroom labs, students will prepare the groundwork of the project; students are expected to apply theoretical concepts learned in the course to interpret experimental results and draw meaningful conclusions from their analysis.
  4. Project Presentation
• Students will prepare a presentation of their work and a short report. Presentations should be based on slides, graphs, and charts.
  5. Evaluation Criteria:
  Criterion
  Points
  Description & Dublin Descriptors (DoD)
  Quality of Work
  20 pts
  Evaluation of the technical solution and the ability to apply acquired knowledge. Includes the intelligent and balanced use of AI tools in document preparation.
  DoD: Applying knowledge and understanding and Making judgements (critical selection of tools and solutions).
  Presentation Skills
  5 pts
  Assessment of delivery clarity, the quality of slides in transferring key concepts, and strict adherence to the 15-minute time limit.
  DoD: Communication skills.
  Response to Questions
  5 pts
  Evaluation of the student's ability to defend their work and apply their knowledge to specific inquiries.
  DoD: Applying knowledge and understanding and Learning skills.

This course aims at providing the student in the fist part of the course with fundamental criteria, processes and methods to understand Risk Management Priciples and Business Continuity Management System and how they work efficiently togheter. The course will describe the processes, activities, actions and challenges that should be coordinated in order to manage effectively and efficiently a disruptive interruption. In doing this, the types and sources of crisis will be identified, analyzed, managed and defined, this is the reason why in the first part of the course ww eill have a strong focus on Risk Management. The course will also provide students with practical methodologies and techniques that can be adopted in order to assess and mitigate risks and vulnerabilities related to a disruptive event from both a risk management and a business continuity perspective. The student at the end of this course, will be able to design, develop, manage, maintain, review and lead effectively a business continuity management system in each parts, they will be able to take advantage from the knowledge of best international practice and Standard adopted every day by any kind of organization.

The goal of this course is to provide specific knowledge about business continuity management.
After successful completion of this course the student:
Will demonstrate the ability of classifying and analysing different risk sources plus the capacity to select good mitigation strategies;
Will be able to select and undestand qualitative and quantitative risk assessment methods;
Will be able to manage all the steps needed to develop a business continuity management system;
Will be able to conduct a proper Business Impact Analysis and develop a full business continuity plan
Will know the standards and sound practive for a certificable business continuity management system.

The course covers the following topics:
Risk Management - Principles and aims of enterprise-wide risk management
Risk Management - Frameworks and standards
Risk Assessment - Risk and uncertainty and their impact on strategy, risk identification and classification, risk assessment tools
Risk Analysis tools, Risk register, risk matrix, risk profile, risk map
Risk Treatment - General aspects of risk treatment, Identifying and designing risk treatments
Risk Treatment - Risk control/reduction techniques
Risk Financing Techinques and tools to manage financial consequences
Business Continuity Management - Introduction
Business Impact Analysis - Business Continuity Strategy - Solution Design
Incident Preparedness and Response and Plan Development and Implementation
Crisis Management & Communication
Business continuity Management Test and Maintenance
ISO Series 223xx for Business Continuity System
Introduction Case
Case Study
The learning experience of this course includes, in addition to face-to-face lectures, case discussions, a group project, real examples and interactions with guest speakers from industry. Groups of students will be engaged in a major assignment focusing on an analysis of a Business continuity management system. The final report will be part of the student assessment process (see next paragraph).

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Group Assignment: Groups of students will be engaged in actively applying risk management and business continuity management methodology. The assignment may take the form of a state-of-the-art review paper, by making use of the methods and tools presented in class. The assignment is intended to evaluate the student’s ability of critically analysing and discuss possible alternative solutions, by integrating different perspectives and contributions coming from the team members.
Written Exam: is intended to evaluate the student’s ability of selecting, justifying and applying the relevant knowledge to manage different sources of uncertainty to guarantee resilience.
Grading: Student evaluation is based on course assignments:
Group assignment: 50%;
Written exam: 50%;

Course instructor, Teaching notes, Case texts and suggested readings
Note: Available on Beep course web page

The course consists in the practical / experimental analysis of measurement and control systems. The course, after a brief recall to the main aspects related to the dynamics of the processes, the control theory and the measurement and control loops, consists in the practical application in a didactical laboratory of the control theory to the tuning and operation of control systems of level, temperature, pressure, flow; emphasizing the aspects of process safety.

The Course aims at giving students the necessary knowledge and technical tools to critically approach Chemical Projects Engineering and Management. A relevant interaction/involvement from a large EPC contractor is planned to be a key issue of the course, so as to provide students the highest connection with the real Chemical/Petrochemical/Oil&Gas Projects, and their Engineering and Management.
In particular, the course starts from (1) the feasibility study of any initiatives – (large) projects included – in which (2) further develops technical aspects of relevant phases of the basic engineering (from the process selection to the cost estimation), then (3) encompasses a critical picture and evolution of the Engineering, Procurement and Construction (EPC) industry and the relevance of chemical engineering within it, provides (4) some basics of Project Management (PM), and enforces a practical approach to the overall issue by means of two voluntary project works (in teams of 5÷8 students) to be performed during the course, having professionals in the EPC sector as tutors.
The course targets the following Goals, within the broader context of the Programme, so as to empower the Student capabilities to:

• Understand context, functions, processes and performance with reference to chemical plants and related projects
• Design solutions applying a scientific and engineering approach with reference to chemical plants and related projects

With reference to the selected Goals at the Programme level, the Expected Learning Outcomes of the course relate to each Student being able to:

• Identify in a systematic way the relevance of the contextual factors, functions and processes with respect to the performance of a project, of a plant as a whole, or of a component, based on the general principles and laws/methods/models for project/plants engineering and management
• Set up and solve a problem related to a project, to plant as a whole, or to a component, applying the general principles and laws/methods/models for project/plants engineering and management

Chemical projects/plants: introduction and general concepts.
General principles of plant design: cost of downtime, bottleneck management and distributed vs. centralized capacity design.
Feasibility study – in the view of a (large) chemical project/plant: project strategy (scope), sales programme (and marketing concept), material inputs, location, site & environment, technology, engineering & layout (from a conceptual viewpoint, tackling bottleneck management and decentralized capacity design) later issue within the course), plant organization, human resources, project implementation (later issue within the course), investment appraisal.
Insights on plant engineering: project requirements and documents: overview of the tools, documents, workflow methods and procedures used in plant layout and piping design. Effective arrangement of equipment, also taking into account process needs, process integration, safety, environmental considerations, constructability, maintainability and operability. Simulation tools used for process, equipment and plant design. Lessons are organized using one or two case studies on plant design for chemical/petrochemical/oil&gas processes, and will include specific inputs and contributions by engineers of a large EPC company.
A view on (from) the industry: insights on the Engineering, Procurement and Construction (EPC) industry and their projects/plants, with a special focus on chemical ones, through seminars and test cases held by experts in both technical and managerial/strategic aspects.
Project management: Introduction to Project Management, Scope Management, Work Breakdown Structure, Time Planning (Bar Chart, Network Diagram, CPM).
A practical approach is enforced by means of two voluntary Project Works (one for management, one for engineering), whose effort is planned mainly in October and December.
Regarding the INDEPENDENT STUDY, some (one or two) topics are introduced by corresponding packages of introductory clips that should be listened to and possibly understood independently by the students (it is advisable to dedicate approximately 4-5 hours of independent study for the package of clips of each topic), to ensure more in-depth discussions and applications, giving substance to the topics presented, and developing adequate preparation for solving numerical-quantitative problems.
Regarding the ASSISTED TEACHING, the course overall includes:

• TRANSMISSIVE/FRONTAL TEACHING: the hours are dedicated to the theoretical and quantitative content developed entirely by the teachers, except for moments of interaction planned by the teachers and/or requested by the students, functional to a better understanding.
• INTERACTIVE/PARTICIPATIVE TEACHING: the hours are dedicated to a structured discussion of the introductory clips, and – predominantly – to the development by the students – accompanied by the teachers – of some particularly significant and complex exercises/problems that are addressed during the course.
• PROJECT DEVELOPMENT TEACHING: the hours (in class) are dedicated to launching the two Project Works and accompanying the students in their preliminary efforts (the PWs are then developed, in Groups, as “independent study”).
• EVALUATIVE TEACHING: the hours are dedicated to moments of guided self-assessment (which does not contribute to the exam grade), also called “previous knowledge tests” of formative assessment, designed to help students understand their state of preparation and level of comprehension, as well as to allow the teachers to revisit topics that may be less understood.
  As far as SW applications are concerned, extensive use of MS Excel is part of the design of the course, ranging from the basic use of standard formulae to the use of the Solver function.

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, senza presentazione/discussione finale
The final grade will be based on a written exam, on an oral exam, and - when applicable - on the project works.
The written and oral exams have to be held in the same call, whilst the results of the project works keep their validity for the whole academic year.
The written exam consists of a set of quantitative problems to solve, and questions to answer; 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 component
• Set up and solve a problem related to a project, or to plant as a whole, or to a component
  The oral exam starts with the discussion of the written exam, then focuses on the knowledge and understanding of the content of the course, as well as of the general principles and laws/methods/models for project/plants engineering and management
  The voluntary project works (teams of 5÷8 students) result into reports; their assessment equally takes into account the formal development and the quantitative/qualitative content, so as to appraise the capability of each Student to:
• Set up and solve a problem related to a project, or to plant as a whole, or to a component

Gavin Towler, Ray Sinnott, Chemical engineering design/Principles, Practice and Economics of Plant and Process Design, 2nd Ed., Editore: Elsevier, Anno edizione: 2013
Max S. Peters, Klaus D. Timmerhaus, Ronald E. West, Plant Design and Economics for Chemical Engineers, 5th Ed., Editore: McGraw-Hill, Anno edizione: 2003

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

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.

La conoscenza delle problematiche relative agli impatti ambientali delle attività industriale è fondamentale nella vita lavorativa dell'ingegnere in qualunque settore industriale: dal settore oil&gas, a quello chimico, farmaceutico, alimentare, o del trattamento rifiuti. Questo corso si propone di fornire queste conoscenze in primo luogo illustrando gli aspetti regolatori e le normative relative alla gestione ambientale in azienda, per poi focalizzarsi sulle tematiche più di frontiera del monitoraggio e della valutazione degli impatti ambientali, considerando sia le emissioni ordinarie che quelle accidentali. Nel corso verranno presentati degli esempi pratici e dei casi studio riferiti principalmente ad aziende dei settori food e oil&gas, prendendo in considerazione l'intero ciclo di vita delle produzioni industriali.

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.

This course will be useful to students who plan to take empirically oriented finance courses as well as students who want to get a solid understanding of the tools required to analyze and model financial asset prices and, more generally, economic time series related to any field of economics and management. The link between statistical models and their implementation is emphasized.
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:
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

With respect to the first learning goal, at the end of the course students will be able to:
Understand the key aspects of statistical time series models, and how these models can be used to forecast economic variables and analyze their relationship
Understand the differences between univariate and multivariate time series models
Understand the importance of confidence intervals associated to point forecasts
Understand the notion and relevance of stationarity in time series analysis
Understand the key aspects of dynamic volatility models
With respect to the second learning goal, at the end of the course students will be able to:
Select the appropriate time series model to apply in practical economic situations.
Interpret the output of econometric packages implementing time series models
Use time series models for forecasting economic and financial time series
Use time series models to support economic decisions

Overview
The course introduces students to financial econometrics, providing them with appropriate techniques for empirical investigation in finance. The emphasis will be on understanding and applying a set of econometric tools that are widely used by academics and practitioners working in quantitative areas such as risk management, investment management, and financial engineering (although most of the techniques are widely used also in empirical macro and monetary economics). After a quick review of the multiple linear regression model, the course will illustrate univariate and multivariate models for time series analysis and forecasting. The analysis of non-stationary time series will be discussed, illustrating the theoretical and empirical relevance of the notion of integration and cointegration. The course also covers dynamic models for volatility analysis (ARCH and GARCH models) and one topic, possibly varied from year to year (event studies, Markov switching models, Factor models,...). Providing the students with the ability to use the models is one of the goals: to this aim, problem sets with both analytical and computer-exercise components will be a relevant part of the course.
Main topics
0. Refresher on the linear multiple regression model: estimation through Ordinary Least Squares, checking assumptions (functional form, multicollinearity, heteroskedasticity, autocorrelation, non-normality)
1. Univariate analysis of time series: Stochastic processes and their properties. AR, MA and ARMA models. Analysis of trend, cycle and seasonality.
2. Multivariate analysis of time series: ARX models and VAR models
3. Analysis of nonstationary univariate and multivariate time series: integration and cointegration
4. Models for the analysis of volatility: ARCH and GARCH models.
5. One of the following topics: Event studies, econometric aspects of the CAPM, econometrics of the efficient frontier, econometrics of derivatives, analysis of ultra-high frequency financial data, long memory processes, Markov switching models,... The topic will be chosen at the beginning of the course. Students willing to deepen autonomously, for some reason, a different topic instead of the chosen one, may propose it.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, senza revisioni periodiche, con presentazione/discussione finale
(i) Written exam (80 minutes, weight 60%). The written exam is based on two exercises (the first is on the topics 1, 2 and 3 illustrated above; the second is on the topics 4 and 5). The main purpose of the written exam is to assess the achievement of the second learning goal and the associated learning objectives (ability to select the appropriate model to answer research questions, to read the output of time series packages, to forecast economic time series based on time series model, to use the models to support economic decisions)
(ii) Oral exam (15 minutes, weight 40%). The main purpose of the oral exam is to assess the achievement of the first learning goal and the associated learning objectives (understanding of the main theoretical aspects of time series models). The oral exam has to be taken after the written exam, not necessarily in the same call.
(iii) Non-compulsory team project work (2 students): a paper about 10/15 pages long, where some of the techniques illustrated in the course is applied to a real problem; the paper has to be illustrated in a 30 minutes presentation, possibly via skype; the project work may increase the final mark by at most 2/30. The project work gives you the opportunity to get an hands-on perspective on the discipline. Highly recommended if you plan to include some time series analysis in your final thesis, or if you think that a deep understanding of statistics in general and time series analysis in particular is a valuable asset for your future.

Chris Brooks, Introductory Econometrics for Finance, Editore: Cambridge University Press, Anno edizione: 2014, ISBN: 9781107661455 http://www.cambridge.org/features/economics/brooks/
Note: Chapters 1 to 8

The aim of the course is the analysis of the instruments to finance complex projects in the infrastructure sector (i.e. energy, transport, real estate, healthcare). The course will introduce the role of infrastructure investments as driver of growth and will cover the structure and the characteristics of the structured finance transactions, in terms of financial structure, technical characteristics, players involved, risk analysis, capital budgeting and valuation. In the course, students will analyze the specific characteristics of instruments to finance infrastructure and to cover risks during the construction and operating phases. During to the course guest speakers will share their practical experience on infrastructure and project finance projects.

At the end of the course, students will be able to analyze financial characteristics of complex projects, to identify key elements of the deal and identify proper solutions for deal structuring with financial prospective.

Introduction: the role of complex projects as alternative investment asset. Taxonomy of project and infrastructure finance. Key features of infrastructure assets
Structure and characteristics of project finance deals
The role of the parties involved in complex project financing: banks, sponsors, syndication
The risk profile of complex projects: identification and mapping and instruments to manage risks
Capital budgeting of infrastructure
Financial valuation for project finance

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
Valutazione continua facoltativa (a scelta dello studente)
Students will be graded based on:
a Final Written Exam
a Business Case;
Case Studies.
The Final Written Exam
The Final Written Exam will be composed by:
open-ended essay questions;
short exercises;
multiple choice questions (MCQ). No penalties will be deducted for a wrong pick.
The Business Case
The Business Case will be executed by groups of students and it will be presented after the mid-semester break. Its reports will be delivered and presented orally to the class by the last sessions of the course.
Case Studies
Throughout the semester, a few Case Studies will be presented to support class discussion. Short written reports will be prepared by the students, prepared in-class or as a quick take-home homework, as individuals or in groups, on a case-by-case basis. Details on each Case Study that contributed to this portion of the examination will be announced in class and on WeBeep. The Case Studies’ overall score will be based both on the quality of the deliverables and on the student’s in-class participation.
The mimimum pass grade is 18, with no separate minimum threshold for the three components of the final score. Please consider that students that do not participate in the group Business Case or in the Case Studies, and who do not meet the requirements to sit the test as an eligible student (more detail in the Syllabus) will be awarded 0 points in the Business Case and 0 in the Case Studies, but they will still be allowed to sit the Final Written Exam.

Slides and case studies available on Beep
S. GATTI, Project Finance in Theory and Practice, Editore: Academic Press, Anno edizione: 2018
Note: III Edition

The goal of the course is to enable students to master material and energy balances on single and multiple-unit systems, typical of the process industry, with a particular focus on industrial chemistry. In addition, the course aims to provide the fundamental knowledge on thermodynamics, kinetics and catalysis of chemical reactions which is required for the rational design of chemical processes. Finally, the course introduces students to the industrial process instrumentation.

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

• solve material and energy balances for reactive and non-reactive systems
• apply the fundamentals of thermodynamics, kinetics and catalysis to the analysis of typical industrial processes
• demonstrate fundamental knowledge on industrial process instrumentation

Mass balances on nonreactive and reactive systems:
process classification
material balance calculations
balances on multiple-unit processes
chemical reaction stoichiometry
combustion reactions
Energy balances on nonreactive and reactive systems:
forms of energy
energy balances on close and open systems
tables of thermodynamic data
heat of reaction
fuel and combustion
Chemical equilibrium:
Equilibrium condition for reacting systems
Mass and energy balances in reacting systems under equilibrium conditions
Chemical kinetics:
reaction rate and rate equation
Arrhenius law and reaction orders
Overall stoichiometry and elementary reactions
Examples of reaction mechanisms
Fundamental of Catalysis:
Kinetics of catalytic reactions
Catalytic materials and their applications
Environmental catalysis
Thermodynamic, kinetic and catalytic analysis of selected industrial chemical processes (e.g. steam reforming of natural gas; ammonia synthesis; nitric acid synthesis)
Fundamentals of measurement techniques (e.g. temperature, pressure, flow, level, composition sensors)

Prova orale obbligatoria
The exam will be oral.
In the examination, the student will be asked general questions on the topics of the course, to verify the knowledge and comprehension of the fundamentals. The interview will also verify the ability of the student to use the background matured to the quantitative analysis of specific cases involving mass and energy balances.

Richard M. Felder, Ronald W. Rousseau, Elementary Principles of Chemical Processes, Editore: Wiley, Anno edizione: 2005, ISBN: 047168757X
Richard M. Felder, Ronald W. Rousseau, Lisa G. Bullard, Felder's Elementary Principles of Chemical Processes, Global Edition, Editore: Wiley, Anno edizione: 2017, ISBN: 978-1-118-09239-2

Course Description:
This course explores how human behavior and the physical environment shape the security of digital systems. Students learn threat modeling, and the STRIDE and ATT&CK frameworks. We study how social engineering works, practice basic techniques such as email spoofing, and examine how AI scales or personalizes attacks. We also cover physical security fundamentals, including perimeters, barriers, and access systems based on RKES and NFC.
A second focus is cyber-physical systems (CPS). We contrast IT and OT goals and constraints, model CPS components, and trace cyber-to-physical impact through automotive and industrial case studies. Detection and mitigation strategies include segmentation, defense-in-depth, anomaly and sensor-validation checks, and fail-safe design.
Teaching goals:
Develop an attacker-aware mindset that integrates human, physical, and digital factors.
Practice structured threat modeling and risk prioritization on realistic systems.
Understand attacks and map mitigations for social, physical, and CPS contexts.

DD1 - Knowledge and understanding
Students will understand:
The threat modeling workflow and common frameworks: assets, DFDs, trust boundaries, STRIDE, ATT&CK.
Social engineering principles and vectors (phishing, vishing, impersonation) and the implications of AI.
Physical security fundamentals: perimeters, surveillance, and RKES/NFC access systems.
CPS/OT vs. IT: goals, constraints, architectures, components, and typical communication protocols.
Detection and mitigation concepts: segmentation (the Purdue Model), anomaly/sensor-validation checks, and others.
DD2 - Applying knowledge and understanding
Students will be able to:
Build DFDs, identify trust boundaries, and apply STRIDE to enumerate threats and abuse cases, especially in human and CPS contexts.
Analyze social engineering campaigns and safely demonstrate techniques (e.g., email spoofing, MFA phishing) in labs.
Implement an intrusion detection system for a CPS domain.
DD3 - Making judgements
Students will be able to:
Understand risks especially in human or CPS related domains, balancing safety, usability, cost, and operational constraints.
Select and justify countermeasures for human, physical, and CPS contexts.
DD4 - Communication
Students will learn to:
Produce clear diagrams (DFDs, architectures) and threat reports.
DD5 - Lifelong learning skills
Students will learn:
A repeatable workflow to track emerging threats.
How to transfer the approach to new, unanalyzed security domains, especially human or physical security ones.

Threat modeling basics: assets, DFDs, trust boundaries.
Threat modelling frameworks: STRIDE; mapping to MITRE ATT&CK;
Social engineering: principles, phishing, vishing, impersonation; AI-assisted attacks;
Physical security basics: perimeters and surveillance; RKES/NFC access systems;
CPS security: IT vs. OT; security of sensors, controllers, networks;
Automotive security: peculiarities and common protocols vulnerabilities (e.g., CAN).
Industrial security: well known case studies and mitigations (Purdue model).
Laboratories on threat modelling, phishing and email spoofing, and intrusion detection on CAN.

Prova scritta condizionata (a scelta del docente), senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Assessment consists of coursework (labs and projects) and a final written/oral exam.
Lab attendance is optional, but the project works (which may be completed throughout the academic year) contribute to the final grade.
Depending on the year and availability, minor points may be awarded for participation to workshops organized with external entities.

Adam Shostack, Threat Modeling: Designing for Security, Editore: Wiley
Cyber-Physical Systems Security Knowledge Area https://www.cybok.org/media/downloads/Cyber-Physical_Systems_Security_issue_1.0.pdf

Learning Goals (Obiettivi dell'insegnamento)
This course aims at outlining relevant developments in manufacturing and service industries with regard to automation and digitalization developments. This is especially tailored towards the new Industry 5.0 (I50) concept of human-centered operations systems. Therefore, the course wants to address the challenge of Human-System Interaction ( HSI ) and the design of successful human-centered systems. HSI is critical in modern operations and supply chain management due to the increasing use of automated and digital systems. Counter-intuitively during automation and Artificial Intelligence (AI) applications, the human factor is increasing in importance in terms of operational performance and business success. In most empirical evidence studies within operations management we find that hybrid systems are performing best, combining the strengths of automated and computer systems with human workers.
Consistently with premise, the course has the following structure: This course aims to provide the main methodologies and criteria for analysing, designing and managing hybrid, i.e. human-digital work systems in logistics, manufacturing and supply chain systems. After an overview on the strategic importance of human-centered operations systems, the course addresses the 3 main pillars of hybrid work systems from a human perspective: Safety, Efficiency and Trust. The last section of the course is dedicated to application examples and blueprints for successful human-centered operations systems. 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 for the participants:
Understand context, functions, processes in a hybrid (human-technology interaction) operations system and the impact on business performance
Identify trends, technologies and key methodologies in a specific application domain (specialization streams like manufacturing, retail logistics or healthcare services)
Design solutions applying a scientific approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face challenges and opportunities in business, service and industrial environments with HSI

Intended Learning Outcomes (ILO, Risultati di apprendimento attesi)
Understand and describe the main challenges in hybrid systems for digital operations systems and their interaction with the general company strategy [Understand]
Define an evolving HSI operations strategy of a company, based on both its operations processes and the its general digitalization and business strategy [Understand and Identify]
Understand and describe: the main HIS stages of Safety, Efficiency and Trust (SET) the following exemplary fields: manufacturing, transport, inhouse logistics (storage and picking), and service processes like for example healthcare [Understand and Identify]
Identify and present innovative HSI solutions in new fields (e.g. service processes, after sales or maintenance processes) [Identify and Design]
Apply criteria, methodologies and models to hybrid operations / HSI challenges in order to: design and manage digital operations systems with AI / ML / Robotics applications in a service and industry contexts [Design]

Topics (Argomenti trattati)
Operations automation and artificial intelligence (AI). Definition of technology adoption in operations systems. Implications of the use of automation and artificial intelligence in operations. The importance of process re-design and digital transformation contexts.
Challenges for digital transformation and AI business models. The human factor as the bottleneck explained. System and supply chain perspectives instead of workplace or corporate perspectives for success. Digital transfer from private to corporate systems.
Analyzing cognitive workload. Stress analysis in digital operations with the MESTAT concept. Differentiating operations tasks and supervising tasks on the rise. Analyzing new required competencies for human workers in future operations systems e.g. gold collar.
Design principles for I50. Discourse how to design human-centered operations systems with tools like design thinking and employee integration. Kaizen and TQM instruments to be used in I50 digital transformation settings.
I50 strategy design. Business model analysis and business canvass methods for I50 purposes in manufacturing and service industries. Strategy by design with human worker integration for competitive advantages.
I50 research update. Latest research outline regarding I50 and human-centered supply chain operations. Examples from different manufacturing and service industries explained.
Case study. Example case study on the empirical analysis of digital operations. E.g. retail logistics, manufacturing or healthcare services innovation cases.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Assessment (modalità di valutazione)
The final exam consists of a written part and an oral part. The written exam is made of:
3 Written Assignments: Theory Abstract, Method Abstract & Experiment Abstract where students are required to design a HSI operations system (e.g. a warehouse, a picking system, service process) applying the models learnt during the course (ILO 4)
Oral presentation exam: Presentation session on Dec 19 where student groups report about own designed and implemented experiments in human-centric systems analysis (ILOs 1, 2, 3)
The teaching material consists of: (i) set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) supplementary exercises; (iv) selected references (selection of papers and chapters of relevant books, videos, etc.). All the material will be available before the related lesson on https://beep.metid.polimi.it.

This course provides basic knowledge for choosing and functionally designing industrial robots. Great attention is given to manipulators and a brief overview is given on service robots. Topics covered include mathematical analysis of principal kinematic chains and dynamic analysis, an introduction to path planning theory, an overview of the mechanical devices or components used in this field and touches on the criteria in the use of industrial robots. The emphasis is not on the control algorithm structures or complicated robot mathematical modelling, but on learning the fundamental concepts and core principles useful in the design and use of robots, especially from a mechanical point of view. The intent is to help students acquire a basic set of analytical tools and expertise for working in the robotic field. The lessons are complemented by exercises based on industrial cases. The exercises could be carried out in groups.

Knowledge and understanding.
After the exam the student:
Has an overview of the robotic field and the use of robots in industrial applications
understands how to model a robot from a kinematic and dynamic point of view
knows the principal mechanical components used in the robotic field
knows the principal methodologies and approaches used to program an industrial robot
knows the basis of the path planning problem for robotic applications
has an overview of the performance of a robot with particular reference to the calibration problem and reference to harmonized technical standards
Applying knowledge and understanding
After the exam the student will be able to:
solve the kinematic and dynamic problem of a robot
plan the trajectory of an end effector in the joint space as well in the working space
design a simple 3dof industrial robot
design the layout of a robotic cell and its production cycle
use an industrial manipulator for simple handling tasks

Origins, history and description of robots: origins and modern trending in robotics. Robot classification. Industrial robotic objectives and issues. Description of basic structure of a robot system: controllers, actuators, transducers, sensors and the like. General characteristics of an industrial robot.
Manipulators analysis: References to general methodologies for direct and forward kinematic analysis and dynamics of multi-degree of freedom systems (Jacobian matrix, singularities, …). Matrix methods for the analysis of 3D systems. Position and orientation of a body in the space (reference systems, position, velocity and acceleration matrix, …). Manipulator dynamics, lumped parameter models for dynamic simulation.
Reference to path planning and control: References to trajectory descriptions in the joint space and in the workspace. Mentions of control of the manipulators in position, force and hybrids. Language and robot programming systems.
Components for industrial robotics: Electric actuators. Speed reducers, remote transmissions. Gripping systems. Position, speed, acceleration and force sensors.
Robot performance: Effects of structural errors, elasticity, backlash and friction in mechanical transmissions. Kinematic and dynamic calibration of the robots. The international regulation for the definition and measurement of robot performance.
Overview of the uses of industrial robots. Principal technical standards: nomenclature, presentation of characteristics, performance criteria and related test methods, safety, coordinated systems and movements, mechanical interfaces (Italian and European legislation, machine directives, harmonized technical standards). Reference to security in the robotic cells and use of a robot in a production line. Applications, case description in assembly, handling and processing operations.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The exam consists of an optional project developed during the practice sections and evaluated during the last period of the course and an oral exam on the main subjects treated during the lessons.
The project mostly aims at checking the acquired capabilities of applying knowledge and understanding, while the oral part of the exam is focused on checking also knwowledge and understand of the student.

B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics: Modelling, Planning and Control, Editore: Springer-Verlag London, ISBN: 978-1-84628-642-1
G. Legnani, Robotica Industriale, Editore: Casa Editrice Ambrosiana, ISBN: 88-408-1262-8

The aim of the course is twofold.
In the Insurance module, students are introduced to actuarial mathematics and learn models and methods used to price insurance contracts and analyse insurance portfolios, both in the life and non-life insurance cases.
In the Econometrics module, students are equipped with the skills needed to thoroughly and appropriately model, analyse, and forecast financial time series.

Lectures and computer laboratory sessions allow students to acquire the following competences.

• Knowledge and understanding.
  Students know the main models and methods used in actuarial mathematics, both in the life and in the non-life insurance cases.
  Students understand the main concepts of statistics and econometrics used to analyse and forecast financial time series.
• Ability to apply knowledge and understanding.
  Students can apply the models and methods of actuarial mathematics to price life insurance benefits, and to model and analyse insurance portfolios to guarantee profitability and solvability of insurance companies.
  Students can analyse in a proper way a financial time series.
• Making judgements.
  Students can judge the main risks in insurance contracts and quantify their impact on insurance portfolios.
  Students can find proper modelling assumptions to analyse and forecast financial time series.
• Communication skills.
  Students are able to express mathematical and financial concepts in a clear and rigorous way.

Actuarial mathematics.
Life insurance: survival models, life tables, pricing of insurance benefits and annuities, reserves, modelling life insurance portfolios, Solvency II regulation.
Non-life insurance: collective risk models for general insurance portfolios, premium calculation principles, the Cramér-Lundberg model.
Econometrics.
Financial time series; stationary processes and selection, estimation, and forecasting of ARMA models; unit root processes, vector autoregressive (VAR) models, and key concepts such as Granger causality and cointegration (Engle and Granger theorem); discrete-time models for heteroskedasticity, including ARCH and GARCH.
Throughout the course, numerous applications to financial market time series are discussed, including volatility estimation and topics in green finance.
Computer laboratory sessions are an integral part of the course. Two group project works, one for each module, are assigned during the semester and evaluated at the end of the course.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation consists in two project works, one for the Insurance module and the other one for the Econometrics module, and an oral exam.
Project works need to be carried out in groups. Students are expected to apply the models and methods taught in class to actual case studies and real-world data, and to develop teamworking skills.
Project works are assigned during the semester and specific deadlines for submission are communicated in due time, for each of them.
Project works are evaluated at the end of the course, each on a scale 0-12, based on the submitted documents (report, MATLAB or R code, etc.). Students are required to show:
Knowledge and understanding of actuarial mathematics models and methods and the Solvency II regulation;
The ability to price insurance contracts and to analyse the profitability of an insurance company;
The ability to discern and analyse the main sources of risk of insurance portfolios;
Knowledge and understanding of econometrics models and methods, time series volatility modelling and cointegration, and multivariate time series models;
The ability to properly analyse and forecast financial time series;
The ability to express mathematical and financial concepts in a clear and rigorous way.
The oral exam is individual, distinct for the Insurance and the Econometrics modules, each evaluated on a scale 0-20. The oral exam can be taken only during official exam sessions; a midterm oral exam will also be scheduled.
The oral exam consists of three questions for each module on the whole program of the course. To pass the oral exam, students must correctly answer to two questions for each module.
Students are expected to show:
Knowledge and understanding of the models and methods taught in class;
The ability to prove in a rigorous way the results discussed during lectures;
The ability to interpret the concepts from an actuarial and/or financial perspective;
The ability to apply the acquired knowledge to examples and case studies;
The ability to express mathematical and financial concepts in a clear and rigorous way.
The final grade of each module, on a scale 0-32, is given by:
Insurance module: sum of project work (0-12) and oral exam (0-20);
Econometrics module: sum of project work (0-12) and oral exam (0-20).
The exam is passed if and only if the grade of each module is 16 or higher and their arithmetic average, denoted by AVG, is 18 or higher. In this case, the final grade of the exam is:
AVG/30, if AVG is between 18 and 30;
30/30, if AVG is higher than 30; in this case, the teachers may award the grade 30/30 cum laude, at their own discretion.
The grades of the project works and of the midterm exam are valid up to the last exam session for this edition of the course (January-February 2027); they are erased afterwards.
If during an exam session only one of the grades of each module is 16 or higher, then the student may retain that grade for the next exam sessions, up to the last one for this edition of the course (January-February 2027); it is erased afterwards.

D. Dickson, M. Hardy and H. Waters, Actuarial Mathematics for Life Contingent Risks, Editore: Cambridge University Press, Anno edizione: 2020, ISBN: 978-11-08-47808-3 https://www.bibliosearch.polimi.it/permalink/39PMI_INST/1nvvje2/alma99632799908776
H. Schmidli, Risk Theory, Editore: Springer, Anno edizione: 2017, ISBN: 3-319-72005-8 https://www.bibliosearch.polimi.it/permalink/39PMI_INST/1nvvje2/alma99590686508776
A. Olivieri and E. Pitacco, Introduction to Insurance Mathametics, Editore: Springer, Anno edizione: 2015, ISBN: 9783319213774 https://www.bibliosearch.polimi.it/permalink/39PMI_INST/fpq6t9/cdi_askewsholts_vlebooks_9783319213774
H. Schmidli, Stochastic control in insurance, Editore: Springer, Anno edizione: 2008, ISBN: 1-281-13740-5 https://www.bibliosearch.polimi.it/permalink/39PMI_INST/1nvvje2/alma9948777108776
Brooks, Chris., Introductory econometrics for finance., Editore: Cambridge university press, Anno edizione: 2019, ISBN: 978-0-13-348686-2
R. Tsay, Financial Time Series, Editore: Wiley Finance

Green Chemistry (also known as Chemistry for Sustainability) and Green Engineering are a set of knowledge useful in designing the construction of products, materials, and plants in a manner that has minimal impact on human health and the environment. The course introduce the principles of of these disciplines, providing the tools necessary to quantitatively evaluate different synthetic procedures (chemical and biochemical), industrial risk, and toxicity. Examples from industry, including reaction conditions, alternative solvents, feedstock and intermediates selection, optimization of performance materials, will be discussed as well as emerging trends in bioprocesses and catalysis.
Upon completion of this course you will be able to:
recognize and discuss the major issues related to sustainability
understand the basics of green chemistry/green engineering and recognize green chemical processes and products
understand fundamental considerations on alternative energy sources
understand the nature, reactivity, and environmental fates of toxic organic chemicals
undestand the biochemical basis of biological organisms and the importance of biomass as source of chemicals and energy
undestand the recent trends in industry issues related to sustainability and safety with enphasis on national and international regulations.
understand the societal implications of some environmental problems and the green chemistry proposed solutions

The course is intended to provide students in Engineering Chemistry, Environmental Engineering, Safety Engineering and Material Engineering with an overview of the fundamentals of pollution prevention, green chemistry and green engineering. Students should gain a greater appreciation of how improvements and modifications are being made in both research and manufacturing to maintain and even enhance environmental quality, preventing risks connected with the production and use of harmful or toxic chemicals. It may also assist students and laureates in choosing a professional career in chemical industries and in the environmental-safety sectors. The course includes recent trends in the fundamental re-engineering of chemical process, i.e. process intensification, use of catalysis and non-traditional media and energy sources, green metrics and LCA criteria to evaluate alternative processes and products, etc.. A section is devoted to the role of biomasses as renewable sources that are capable to "green up" the chemical industry and to support sustainable development of the human society, satisfying the demand in energy and materials.At the end of the course, students will have the knowledge to address green and sustainability issues described in the objectives.
In terms of knowledge and understanding (Dublin Descriptor 1), students will be able to:
recognize and discuss the major issues related to sustainability
understand the basics of green chemistry/green engineering and recognize green chemical processes and products
understand fundamental considerations on alternative energy sources
understand the nature, reactivity, and environmental fates of toxic organic chemicals
undestand the biochemical basis of biological organisms and the importance of biomass as source of chemicals and energy
undestand the recent trends in industry issues related to sustainability and safety with enphasis on national and international regulations.
understand the societal implications of some environmental problems and the green chemistry proposed solutions
Regarding the application of the knowledge and understanding acquired (Dulino Descriptor 2), students will be able to:
perform simple green metric calculations on simple chemical reactions
have a broad vision about the issues related to a chemical process and how to move in a more green and sustainable direction
have a broad vision about the issues related to the use of natural resources (fossil and sustainable) and how yo reduce the environmental impact related to their use
Through classroom exercises, students will acquire the ability to make independent judgments (Dublin Descriptor 3), and in particular to:
determine the mass balance and the related green metrics through stoichiometric calculations
formulate hypotheses on how to improve a process or how to choos the best on depending on the effect of experimental variables such as temperature, pressure, solvents, reaction times
evaluate the reasonableness of the result of numerical calculations, based on estimates of the orders of magnitude involved.
Furthermore, students will have improved their communication skills (Dublin 4 Descriptor), using correct technical-scientific terminology to describe green and sustainable materials, their transformations, and energy production.
Finally, students will be able to independently rework, select and summarize (Dublin 5 Descriptor) the concepts relating to the information contained in basic and advanced textbooks, scientific and technical literarure in the field of chemical technologies, in particular in green and sustainable chemistry.

The course is organized in several sections:
1) Sustainability and Principles of Green Chemistry
2) Control of Environmental impact of chemical processes and products,
3) Toxicity,
4) Green metrics,
5) Biopolymers and Natural products,
6) Biotransformation and Biotechnology,
7) Energy Efficiency and Emerging Technologies,
8) Process Intensification,
9) Solvent and feedstock selection,
10) Catalysis for Sustainable Chemistry,
11) Product and Process Alternatives
Description of topics
1) Sustainability of raw materials and energy sources: renewable and not renewable resources – survey of main concerns – 12 Principles of Green Chemistry and Green Engineering – tools and methodologies for the assessment of chemical, toxicological and environmental risk – life cycle analysis of products and processes, indicators – green design of chemicals, polymers, and materials.
2) Toxicology – hazard and exposure – toxicity risk assessment
3) Improvement of environmental performance of existing industrial processes – green metrics – greener production of chemical commodities, materials, and fine chemicals from industry
4) Energy – sources, efficiency, safety: fuel types and their environmental impact – hydrogen economy – unconventional energy sources: microwave, ultrasounds, photochemistry and electrochemistry.
5) Biomasses and Cn building blocks – biopolymers and composites.
6) Bio-refinery: transformation of conventional raw materials into commodities – biocatalysis – energy crops – biofuels – solvents and molecular specialties – biotechnological applications.
7) Catalysis in green chemistry: heterogeneous catalysis (acid, metal, micellar, phase transfer) – supported reagents – homogeneous catalysis – biocatalysis.
8) Alternative solvents for Green Chemistry: VOC – supercritical fluids – ionic/eutectic liquids – gas expanded liquids – polymeric liquids.
9) Mechanical, thermal and chemical recycling: effluent and waste minimization and control – durability of products and materials – recycle of plastics.

Prova scritta obbligatoria, con prove in itinere
Exams consist in the evaluation of how the topics discussed during the course are approached by the student, and includes exercises on green metrics, question about the organic chemistry concepts important in green chemistry, and open questions. There is an intermediate exam in november (written) regarding the first part of the course and the second part (written), together with the full exam (written) in january. The students that pass the first part can do the second part, the other students they will do the full exam. It is a choice of the student, to refuse the first part even if positive (>= 18) an do the full exam. All the other written exames will cover the full program of the course. The student that pass the first part in november can take the second part in january, or february, or june, or july, or september; to pass the whole exam, aslo the grade of the second part has to be >=18, if it is lower, the student has to repeat the full exam.

P.T. Anastas, J.C. Warner, Green Chemistry: Theory and Practice, Editore: Oxford Un. Press, Anno edizione: 2000
Note: Testo Introsuttivo
L. Constable, D. Constable,, Green Chemistry Metrics: Measuring and Monitoring Sustainable Processes, Editore: Wiley, Anno edizione: 2009
Note: testo generale
M. Doble, A.Kumar, Green Chemistry and Engineering, Editore: Academic Press, Anno edizione: 2007, ISBN: 0123725321
Handbook of Green Chemistry, Editore: Wiley VCH, Weinheim, Anno edizione: 2013, ISBN: 978-3-527-33710-1
Note: Set I: Green Catalysis, (Vol. 1: Homogeneous - 2: Heterogeneous - 3: Biocatalysis);
II: Green Solvents (- Vol. 4: Supercritical Solvents -: Reactions in Water - 6: Ionic Liquids);
III: Green Processes (Vol. 7: Green Synthesis - 8: Green Nanoscience - 9: Designing Safer Chemicals)

This laboratory course is designed to provide mechanical engineering students with hands-on experience in the field of Noise, Vibration, and Harshness (NVH) testing. NVH is a critical aspect of engineering, particularly in the automotive and aerospace industries, where minimizing noise and vibration is essential to ensuring user comfort and increasing the perceived quality of mechanical components and machinery.
Students will gain a comprehensive understanding of NVH principles and testing methodologies through a practical approach. The core of the course will focus on the use of state-of-the-art NVH measurement instruments, with focus on microphones, sound intensity probes and accelerometers. Students will be guided through the process of collecting NVH data from different mechanical systems and will learn how to analyze the acquired data using dedicated software tools and interpret the results.
The final part of the course will provide insights into the challenges and solutions related to NVH testing.

Dublin Descriptors (DD)
Expected learning outcomes
Knowledge and understanding (DD1)
The lecture sessions will allow students to:
Recall fundamental concepts related to noise generation and transmission.
Recall fundamental concepts related to vibration generation and transmission.
Identify the names and functions of measurement equipment used in NVH analysis.
Explain the principles underlying NVH phenomena, including sources, propagation, and human perception.
Describe the operating principles and functions of measurement instruments and data acquisition systems used in NVH analysis.
Application of knowledge and understanding (DD2)
The laboratory sessions will allow students to:
Apply experimental techniques to measure noise and vibration levels in laboratory and real-world settings.
Use data acquisition tools to collect and process NVH data during experiments.
Identify the correct data acquisition requirements given a target NVH problem.
Design the proper measurement strategy to tackle a target NVH problem.
Analyze experimental data obtained from NVH measurements using signal processing and data analysis techniques already known to the students.
Identify patterns and trends in NVH data to characterize noise and vibration sources and their frequency content.
Forming judgments (DD3)
The laboratory and project sessions will allow students to:
Demonstrate the ability to write a requirement and design specification document.
Demonstrate the ability to design a measurement chain for a target NVH problem.
Integrate the theoretical concepts learnt and extract meaningful parameters for a target NVH problem.
Evaluate measurement results to assess the impact of noise, vibration, and harshness on system performance.

0. Module 0: Introduction to NVH

• Definition and importance of NVH in engineering.
• Overview of NVH phenomena: noise, vibration, and harshness.
• Applications of NVH analysis in various industries (e.g., automotive, aerospace, consumer electronics).
  1. Module 1: Basic Acoustic measurements in NVH
• Topic 1.1: Acoustic quantities and sound propagation.
• Topic 1.2: Measurement of acoustic quantities (sound pressure level, sound intensity, sound power).
  2. Module 2: Advanced Acoustic measurements in NVH
• Topic 2.1: Array acoustics.
• Topic 2.2: Sound Quality and subjective noise evaluation.
  3. Module 3: Vibro-acoustic measurements
• Topic 3.1: Machine Condition Monitoring.
  Each module is addressed through a theoretical introduction followed by practical experimental sessions.
  4. Laboratory Projects
• Design and execution of hands-on experiments focusing on noise, vibration, and harshness measurements.
• Development of project proposals outlining specific NVH problems to be investigated.
• Use of laboratory equipment and data acquisition systems to collect and analyze NVH data.
• Application of signal processing and data analysis techniques to interpret experimental results and draw conclusions.
• Presentation of project findings through written reports and oral presentations.
  By integrating case studies and laboratory projects, students gain practical experience in applying NVH measurement techniques to real-world problems while reinforcing theoretical concepts learned during the course.
  Laboratory projects also provide an opportunity for students to develop critical thinking, problem-solving skills, and effective communication abilities, preparing for future activities in NVH analysis and engineering.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students will pass the course 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 a NVH 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 data processing strategies (DD3, DD5);
critical analysis of the results obtained (DD3);
discussion of the results and defense of the engineering choices made (DD3, DD4).
The project topic will involve both laboratory experimentation and independent work.
Students will perform supervised or unsupervised experiments in laboratory settings using Polimi instrumentation to to collect data relevant to their project topic. Students are required to record data and troubleshoot common issues that may arise during the experiments.
During supervised classroom laboratory sessions, students will prepare the groundwork for the project. They are expected to apply the theoretical concepts learned in the course to interpret experimental results and draw meaningful conclusions from their analysis.
Students will prepare a presentation of their work. Presentations should include slides, graphs, and charts.
Clarity of presentation and exposition (DD4) will also be considered in the final grade.
The following evaluation criteria will be applied.

• Quality of Work: 20 pts
• Presentation Skills: 5 pts
• Response to Questions: 5 pts
  Dublin Descriptors
  DD1: Knowledge and understanding
  DD2: Applying knowledge and understanding
  DD3: Making judgements
  DD4: Communication
  DD5: Learning skills

Students may refer to the reference materials provided during the course.
M. Norton and D. Karczub, Fundamentals of Noise and Vibration Analysis for Engineers, Editore: Cambridge University Press
F. Fahy, Foundations of Engineering Acoustics, Editore: Elsevier

Gli odori rappresentano una delle principali cause di impatto ambientale percepito dalle comunità e costituiscono una sfida sempre più rilevante nella progettazione e gestione di impianti industriali e di trattamento dei rifiuti e delle acque. Il corso di Laboratorio di Caratterizzazione e Modellazione delle Emissioni Odorigene introduce gli studenti ai metodi e agli strumenti utilizzati per analizzare, quantificare e prevedere la diffusione degli odori industriali nell’ambiente.
Attraverso le attività di aula relative allo sviluppo di un caso studio, gli studenti acquisiranno familiarità con le principali tecniche di campionamento e caratterizzazione delle emissioni odorigene, comprendendone i principi di funzionamento, i limiti applicativi e il ruolo nel monitoraggio ambientale.
Il corso approfondirà inoltre l’utilizzo di modelli matematici e strumenti di simulazione per lo studio della dispersione degli odori in atmosfera, consentendo di valutare l’impatto delle sorgenti emissive sul territorio e di interpretare i risultati nell’ambito di studi ambientali e procedure autorizzative.
Al termine del corso, gli studenti saranno in grado, attraverso la presentazione di un progetto di gruppo, di comprendere il percorso che va dalla misura delle emissioni odorigene alla valutazione del loro impatto, integrando dati sperimentali e strumenti modellistici per affrontare problematiche reali di gestione e controllo degli odori.

Al termine del laboratorio progettuale, gli studenti saranno in grado di raccogliere, elaborare e interpretare dati relativi alle emissioni odorigene e al loro impatto sul territorio, applicando in modo integrato le conoscenze teoriche e gli strumenti operativi acquisiti durante il corso.
In particolare, gli studenti svilupperanno un progetto di gruppo finalizzato alla valutazione dell'impatto olfattivo di un impianto reale o simulato. Il progetto comprenderà l'analisi delle sorgenti emissive, la caratterizzazione delle emissioni odorigene, l'applicazione di modelli di dispersione atmosferica e la valutazione delle potenziali ricadute sul territorio circostante.
Al termine dell'attività progettuale, gli studenti saranno in grado di presentare criticamente i risultati ottenuti, discutendo le principali crititità, le incertezze dell'analisi e le possibili strategie di mitigazione dell'impatto odorigeno.

Introduzione alle emissioni odorigene e al loro impatto ambientale.
Quadro normativo e linee guida per la valutazione dell'impatto odorigeno.
Fondamenti di olfattometria dinamica e misura della concentrazione di odore.
Tecniche di campionamento delle emissioni odorigene.
Caratterizzazione delle sorgenti emissive puntuali, superficiali e diffuse.
Introduzione ai composti responsabili delle emissioni odorigene e alle tecniche analitiche di supporto.
Principi di dispersione degli inquinanti in atmosfera.
Modelli di dispersione atmosferica applicati alle emissioni odorigene.
Analisi e interpretazione dei risultati modellistici.
Indicatori di impatto odorigeno e criteri di accettabilità.
Elaborazione di mappe di impatto olfattivo sul territorio.
Strategie di prevenzione, contenimento e mitigazione delle emissioni odorigene.
Sviluppo di un progetto di gruppo per la valutazione dell'impatto odorigeno di un impianto e presentazione dei risultati.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
La valutazione finale del laboratorio progettuale sarà basata sull'esposizione orale, svolta in gruppo, del progetto sviluppato durante il corso.
Nel corso della presentazione verranno valutati la correttezza dell'approccio metodologico adottato, la capacità di analizzare e interpretare i risultati ottenuti, la qualità della presentazione tecnica e l'efficacia della discussione delle criticità e delle conclusioni emerse dallo studio di impatto odorigeno.
Particolare attenzione sarà dedicata alla capacità degli studenti di integrare le attività di caratterizzazione delle emissioni con gli strumenti di modellazione e di comunicare in modo chiaro e rigoroso i risultati del progetto.

Il corso si propone di fornire agli studenti una solida preparazione teorico-pratica nell’ambito della chimica analitica, con particolare enfasi sulle tecniche strumentali più comuni e sul loro impiego nel contesto del controllo qualità. L’obiettivo principale è sviluppare la capacità di selezionare, applicare e interpretare in modo critico le metodologie analitiche più appropriate per l’identificazione e la determinazione quantitativa di composti organici e inorganici in matrici complesse.
L’insegnamento integra le basi concettuali della chimica analitica con l’esperienza diretta in laboratorio. Gli studenti acquisiranno competenze nell’uso di tecniche spettroscopiche, spettrometriche e cromatografiche, imparando a valutare l’affidabilità e la validità dei risultati ottenuti.
Durante il corso verranno inoltre introdotti i principi delle buone pratiche di laboratorio e le modalità di redazione di protocolli analitici. Sono previste 4 sessioni sperimentali di laboratorio, finalizzate all’applicazione operativa delle tecniche studiate, con la determinazione qualitativa o quantitativa di specifici analiti. Tali attività consentiranno agli studenti di acquisire familiarità con la strumentazione analitica e la raccolta dati.

DdD 1: Conoscenza e comprensione
A seguito del superamento dell’esame, lo studente:
conosce i principali metodi chimici e strumentali di analisi e separazione di miscele
conosce i principi di funzionamento delle tecniche strumentali più utilizzate in chimica analitica
conosce in generale le tecniche maggiormente impiegate nel controllo di qualità dell’industria chimica
DdD 2: Capacità di applicare conoscenza e comprensione
A seguito del superamento dell’esame, lo studente:
sa riconoscere l’identità di un semplice composto organico valutando un insieme di caratterizzazioni spettroscopiche e spettrometriche
sa scegliere il metodo analitico più appropriato per l'analisi di un determinato analita
DdD 3, 4 e 5 – Autonomia di giudizio, abilità comunicative e capacità di apprendimento:
è capace di valutare in autonomia l’affidabilità di un metodo analitico e scegliere la tecnica più idonea al problema;
comunica i risultati in modo tecnico, chiaro ed efficace, sia oralmente che per iscritto;
è in grado di aggiornare le proprie competenze nel settore analitico attraverso fonti bibliografiche.

Aspetti generali:
Introduzione alla chimica analitica
Introduzione ai fenomeni di interazione radiazione - materia
Metodi classici: analisi gravimetriche (per precipitazione e per volatilizzazione) e volumetriche (titolazioni, metodo di Kjeldahl; metodi di Mohr e Volhard).
Metodi strumentali:
Spettroscopia UV-Vis e IR
Risonanza Magnetica Nucleare
Tecniche Cromatografiche
Spettrometria di massa
Il linguaggio della chimica analitica:
Analisi, determinazione e misura
Tecniche, metodi, procedure e protocolli
Classificazione delle tecniche analitiche
Selezione di un metodo analitico
Sviluppo della procedura
Stesura del protocollo
Valutazione dei dati analitici
Caratterizzazione delle misure e dei risultati
Caratterizzazione degli errori sperimentali
Esercitazioni di laboratorio su campioni reali e simulati, con elaborazione dati e stesura di relazioni tecniche

Prova scritta condizionata (a scelta del docente), senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
La preparazione dello studente sarà valutata tramite una tesina scritta e lo svolgimento di un esercizio di identificazione di un composto incognito, e da un colloquio orale.

Holle-Crouch, Fondamenti di Chimica Analitica, Editore: Edises, Anno edizione: 2023, ISBN: 9788879598651
D. C. Montgomery, Introduction to statistical quality control - VIII Ed., Editore: John Wiley and Sons, ISBN: 978-1119657118

The course is focused on the Life Cycle Assessment (LCA) methodology.
The aim is twofold: to introduce students to the theoretical fundamentals of the methodology and then to apply them to evaluate the environmental sustainability of materials and industrial processes.
A significant portion of the course will be devoted to applying the LCA methodology to representative real-life cases, mainly taken from chemical, food, and materials industries.
The course is organised as a computer laboratory. The open-source software, OpenLCA, is the tool adopted.
Lectures will be held in classrooms with electrical connections at every desk, and students are required to bring their own laptop computer.

Upon successful completion of the course, students will be able to:
explain the principles and methodological framework of Life Cycle Assessment (DdD1);
use OpenLCA software to perform Life Cycle Assessment studies (DdD2);
select appropriate environmental impact assessment methods and indicators for different assessment goals (DdD2);
apply the LCA methodology to simplified industrial case studies (DdD2);
interpret and critically discuss the results of Life Cycle Assessment studies (DdD2);
critically interpret and evaluate published LCA studies (DdD3).

Sustainability assessment: introductory concepts.
Fundamentals of Life Cycle Thinking (LCT) and Life Cycle Management (LCM)
Life Cycle Assessment (LCA): historical background, ISO standards, procedures, applications, data quality and data sources.
Eco-indicators: measurement methods, environmental and damage impact categories, impact quantification; carbon footprint and climate change.
Materials End-of-Life: open and closed-loop recycling, re-use, waste-to-energy, waste-to-materials, waste-to-chemicals, waste management processes.
Use of the software OpenLCA

Prova scritta obbligatoria, senza prove in itinere
The final assessment consists solely of a written examination, organised in two sections:
Part A: closed questions on theory fundamentals and one case study (half an hour)
Part B: numerical application of the LCA methodology to a simplified case study using the software OpenLCA (2 hours)
The final grade (maximum 33 points) is obtained by combining the scores of Part A (maximum 9 points) and Part B (maximum 24 points). Final grades are then converted to the Italian grading scale, with scores strictly higher than 31.5 awarded 30 cum Laude.
The test will last two and a half hours, with a short 15-minute interval between Part A and Part B.
Part A consists of multiple-choice questions and short-answer questions covering theoretical concepts and one simplified case study. During Part A, no electronic support or any other type of support is allowed.
In Part B, students will perform a simplified Life Cycle Assessment using OpenLCA and answer quantitative questions based on the obtained results. During Part B, students must use their own notebook computer. Printed notes, textbooks and other reference materials are permitted. Students may access online resources during Part B. Mobile phones are not allowed.
There is no limit to the number of examination sessions students may take, and there is no oral examination.
At the end of the course, students may take a voluntary mock examination under exam conditions. The simulation replicates the structure and timing of the official examination and offers an opportunity for self-assessment.
Students are required to bring their own notebook computer for the practical laboratory sessions and for Part B of the final examination.

Walter Klopffer and Birgit Grahl, Life Cycle Assessment (LCA) - A Guide to Best Practice, Editore: Wiley-VCH, Anno edizione: 2014, ISBN: 978-3-527-32986-1
Note: Textbook available in the Polimi library as e-book
Michael Z. Hauschild Ralph K. Rosenbaum Stig Irving Olsen, Life Cycle Assessment Theory and Practice, Editore: Springer, Anno edizione: 2018, ISBN: 978-3-319-56474-6 DOI 10.1007/978-3-319-56475-3
Reinout Heijungs - Sangwon Suh, The Computational Structure of Life Cycle Assessment, Editore: Springer, Anno edizione: 2002, ISBN: 978-94-015-9900-9

The course will describe the behavior of materials (with greater attention to metals) exposed to aggressive
environments, used in chemical plants, petrochemical industry. Both design phase and operation condition will
be considered. The main classes of materials are considered in relation to their use in real working condition.
The fundamental concepts related to the mechanisms of damage in operation, with reference to fracture
mechanics and degradation phenomena, are discussed. The course will give information useful in both the
design phase (material selection and use of prevention techniques), as well as in monitoring and inspection real
systems, with particular reference to NDT, i.e. non-destructive techniques. Finally, RBI will be briefly introduce
in order to define the risk matrix to obtain the priorities of intervention.

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

The objective of the course is to provide students with principles, methodologies and tools to design, analyze and improve manufacturing and service companies' operations, so to dramatically increase their competitive advantage.
Studenst will learn to deal with the multidimentional aspects of Operations at a strategic, tactical and operational level.
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
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
Develop new ideas and solutions in business and industrial scenarios evolving over time

The student succesfully taking this course is expected to be able to:
DdD1
classify the different Operations Systems
understand the functioning of such systems
match the system characteristics with its target market segment
DdD2 DdD3
generate alternative guidelines to improve the system, considering main goals, constraints and evolutionary trends
design and implement solutions to improve the Operations System through a thorough methodology, sound reasoning and, whenever possible, quantitative ananlysis
Check whether the resuls are in line with the expected ones and the goals achieved

Introduction
1. Operations’ objectives and decision areas.
2. Operations in primary processes, and in supporting processes. Operations in industrial companies and in service companies.
Operations strategy
1. Operations performances, levers, positioning
2. Development of an operations strategy in the broader context of a Business strategy considering the different areas of Operations in an integrated way
3. Structural decisions (resources sizing, system configuration, vertical integration, system international footprint, etc.) and Infrastrctural decisions (resource planning and control, organisational structure, target setting, customer management)
Service Operations Management
1. Distinctive characteristics of service companies. The service concept definition.
2. Designing, managing and improving the Service delivery system. Front office versus back office, demand and capacity management. Demand management in service companies with fixed capacity (Hotels, Airlines, Turist villages,...) Yield management.
3. Queue theory. Single and multiple customer-class systems; single and multiple resource systems.
4. Operations in different service industries
Operations improvement: innovative managerial approaches for OPerational EXcellence-
1. Lean philosophy and principles. Analysis of innovative aspect of Lean approach that allow to achieve such dramatic improvements. Going beyond Just In Time.
2. Lean methodologies and techniques: Value Stream Mapping. Variations reduction. 5S, SMED, Cell design, etc.
3. A new vision of human factor and the impact on operations' structure.
4. Advanced implementation of Lean approach: high variety low volume companies, make to order / engineer to order companies (manufacturing and services). Lean product development, Lean Healthcare, Lean Banking, Lean Insurance.
5. Lean Supply Chain: the impact of applying the Lean philosophy to the whole supply chain.
6. Six Sigma
7. Agile
8. OPEX and Industry 4.0

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
Final written exam.
The written exam is made of:
1-3 open questions to assess the knowledge of classifications, relationship between levers and performances, pros and cons of different alternatiove solutions for the positioning of the lever of Operations Strategy, etc. and on the functioning of complex systems
1-2 exercises presenting the quantitative analysis of a present situation in a company, and the student is requeted to take decisions on how to improve present situation and design the detailed future state configuration with a quantitative sizing if different aspects (e.g. amount of inventory; number of operators, etc.) following the 8 steps of the Lean Management approach presented doring the course, making sure that they meet the given target
The voluntary assignment is an assignment, where the student is expected to understand and present a product and market of her choice (respecting the few key characteristics required in the assignment) and design the operation system that is best to be successful with that product on such market segment (therefore showing to know how to align Market and Operations). Including the choiche of the Tecnology to use, the Sizing of the Capacity, definition of the position of the Customer Order Decopling Point, the incentive system, etc.
The proposed charateristics of the Operation system (positioning of the levers) should be justified in the light of their impact on the performance
The assignment is due around half of the semester

N. Slack, A. Brandon-Jones, R. Johnston, A. Betts, Operations and process management., Editore: Pearson ed. 4th ed
J. Bicheno, A. Portioli Staudacher, Metodologie e Tecniche per la Lean, Editore: Pitagora. J. Womack, D. Jones., Lean thinking, Editore: Free press, Anno edizione: 2003. J. Liker, The Toyota Way, Editore: McGraw Hill, Anno edizione: 2005
Terry Hill, Alex Hill, Manufacturing Strategy, Editore: Palgrave Macmillan, Anno edizione: 2009

This course deals with power systems analyzed from ethical and social perspectives. It is intended to give students a chance to reflect on the ethical, social, and cultural impacts of power systems by focusing on the issues faced by and brought about by electrical engineers.
This integrated course includes lectures by two instructors with complementary expertise, covering the issues of power systems at the intersection of technical and socio-ethical issues, and invited lecturers, covering specific topics at the forefront of research in the socio-technical management of power systems.
Class participation is expected, as classes will be organized as short workshop sessions in which experiences, and individual and group reflections are punctuated by Socratic discussions or microlectures.

Knowledge and understanding
Students will:
Acquire a broad perspective on the ethical and social impacts and implications of power systems;
Be acquainted with normative ethics and normative argumentation;
Learn how to recognize and analyze ethical and social aspects and issues inherent in development, control, and design of power systems;
Be able to understand how technical problems are inherently connected to a social dimension within a socio-technical perspective.
Applying knowledge and understanding
Students will:
Be able to use critical skills in clarifying and ethically analyzing case-studies involving power systems;
Be able to apply ethical theories to problems created, aggravated or transformed by smart grids;
Be able to explore and assess possibilities for solving or diminishing existing and emerging ethical and social problems of smart grids.
Making judgements
Students will be able:

• To autonomously analyze the ethical issues of a technology and to develop a critical analysis on that;
• To evaluate and select the appropriate knowledge in the effort of elaborating and justifying a philosophical argument on a topic autonomously selected.
  Communication
  Students will learn to:
• Work in small groups;
• Present in an effective way the results of their independent research, being able to justify their choices.
  Lifelong learning skills
  Students will:
  Be better prepared to their future professional life in an ethically and socially responsible way;
  Be able to analyze problems through an ethical lens.

The course will cover different topics from both a theoretical and a more practical point of view.
The following topics will be presented within the context of power systems development and technologies:
Privacy and privacy-preserving analysis of energy data: infrastructure components and consumer devices as data acquiring network devices.
Security both at the individual and national level: power disruption causing loss of infrastructure, endangering public safety and jeopardizing national security.
Equity: equitable pricing and affordability of access; fair distribution of costs and benefits; energy management burden on uniformed consumer; managing consumer behavior.
Environmental sustainability: future affordability of energy; intergenerational justice; possible conflict between reliability and environmental sustainability.
AI/ML techniques and Big Data analytics for the smart grid: their increasing role and critical issues (e.g., fair algorithmic decision making).
Social acceptance issues: effects of moral values on the acceptance of smart grid technologies; ethics of technology and technology acceptance models.
Professional codes of conduct: benefits and limits; how codes face innovation such as the smart grid.
Students will be supervised in the development of the final project (class presentation) in order to achieve the required standards.

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
Foreword: The program is the same for the both versions of the course (i.e, 5 ECTS, and 6 ECTS).
Grading will be on the following basis.
5 ECTS: 50% final project (team presentation in class); 50% written test on the course topics.
6 ECTS: 50% final project (team presentation in class + individual assignment); 50% written test on the course topics. The additional ECTS is accounted for by the individual assignment, which will be announced and agreed upon at the beginning of the course.

Chemical process design consists in finding a sustainable process that can convert the raw materials to the desired products cost effectively.
The objective of this course is to introduce students to systematic methods for process design, to provide an overview of the main steps involved in the typical life cycle of a process design and to make students understand the complexity of the design activity, considering the different types of industries and sectors with own domain specific equipment and standards. In addition to systematic approach for process design, other process design considerations (economics, heat exchangers, etc.) will be stressed in order to equip students with a flexible skillset to be able to design innovative, cost-competitive and sustainable processes in a wide range of process industries.
The course is taught in innovative teaching mode with approach “Blended Learning & Flipped Classroom” for 3 CFU. According to this approach, when dealing with some topics, students are introduced to the learning material before the lesson, and the classroom time is used to deepen the understanding through discussion with peers and problem-solving activities in small groups supported by the teacher. After the lesson, students think about the feedback they have received and use this to further improve their learning.
Moreover, through the Digital Twin Laboratory activity, students will also have the possibility of better understanding the development of separation processes starting from the analysis of phase equilibria by attending a demonstration with the experimental unit for collection of phase equilibria. The collected data will be then used for the thermodynamic modelling and the simulation of a given separation process.

The course will allow students to:
know how to draw the common diagrams daily used by the process engineer, how to formulate the objective for design, identify, gather and analyze necessary data for product-process of interest, which are the main issues in a process plant, how to manage a plant and how to perform an economic analysis, which are the service facilities and the systems out of battery limits of a process plant ( conoscenza e comprensione – knowledge and understanding );
be able to apply the acquired knowledge to design a process flowsheet complete with energy and mass balances for a given design problem and to evaluate the optimal layout of a plant considering safety, energy and economic issues ( capacità di applicare conoscenza e comprensione – applying knowledge and understanding );
know how to use the simulation software ASPEN HYSYS ® to solve and optimize flowsheets ( conoscenza e comprensione – knowledge and understanding );
be able to autonomously learn new topics and apply theoretical ideas to find solutions to problems referring to fields different from the one presented during the course ( capacità di apprendimento legata alla modalità di didattica innovativa – learning skills related to innovative teaching approach );
be able to clearly explain the strategy used for solving problems, to impressively communicate the obtained results and to write a technical report ( capacità di applicare conoscenza e comprensione legata alla modalità di didattica innovativa – applying knowledge and understanding related to innovative teaching approach ).

The course is based on lectures and selected case studies for which the analysis of process schemes and their representation by using process simulators commonly employed by engineering companies will be carried out. Part of the course (focusing on diagrams and on the main issues in process plants) will be taught in innovative teaching mode with a “Blended Learning & Flipped Classroom”.
The following topics will be covered:
Diagrams: process scheme, BFD, PFD, P&Is, utility diagram;
Main aspects for process design: design basis, selection of the process flowsheet considering the different stages of separation and reaction, technology options and key process stages with related products, design trade-offs and alternatives, sensitivity analysis and optimization applied to a process scheme;
Other process design considerations: economics, energy saving, degrees of freedom and factors affecting productions, plant flexibility in response of variations of production demand, safety, environmental, ethical and societal issues;
Common utility systems and “off-site” units, with description of schemes and criteria for use and design: fuel supply, fuel oil and fuel gas plants; water treatment; steam generation and condensate recovery (high-P, medium-P and low-P steam); cooling water (open loop, closed loop, open recirculating systems); instrument air system; safety system, venting from pressure vessels, systems for conveying discharge, flares; storage (atmospheric storage, pressure storage, refrigerated storage, heated storage); waste disposal system (hints); wastewater treatment (hints);
Use of process simulator (ASPEN HYSYS ® ) to solve flowsheets.
The exercises will focus on the application of the theory to case studies, with the use of the software ASPEN HYSYS ® to simulate the process and of Microsoft Excel to analyze the results.
The student will also have the possibility to attend a demonstration of collection of phase equilibria data with the experimental units in the Process Thermodynamics laboratory (PT lab), part of the Process Design & Process Thermodynamics laboratory (PD&PT lab) of Politecnico di Milano. For a chosen system, the student will understand the type of data needed, analyze the collected points of phase equilibrium and design the optimal process for obtaining the product of interest.

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 final evaluation of learning will be obtained through a written test with questions about all the topics covered during the course and, for students with a mark in the written test equal to or higher than 26, an oral test to further assess the student’s level of knowledge. Each student will prepare a short technical report on all the exercises and problems considered during the course, which will be provided to the teacher before the exam for the evaluation.
More details about the exam rules are made available on the WeBeep platform.
After having passed the examination, the student must be able to talk about and critically discuss all the topics presented during the course, showing the capabilities described in “Risultati di apprendimento attesi”.

The slides of the lessons will be shared on WeBeep platform early before the lesson.

Introduzione all'Ingegneria dei Sistemi di Processo.
Simulazione stazionaria e dinamica di processi industriali continui e discontinui. Stima dei costi. Valutazione economica dei termini CAPEX e OPEX.
Progettazione dinamica: analisi del prezzo/costo di materie prime e utilities. Valutazione economica dei termini CAPEX e OPEX.
Economia: costi fissi e variabili. Valutazione di investimenti.
Riconciliazione dei dati. Rilevamento di errori. Identificazione modello.
Ottimizzazione di processo: modalità di progettazione; modalità online; gestione/supervisione. Approccio gerarchico.
Digital twins: convenzionali e avanzati. Ambienti virtuali, realtà virtuale e realtà virtuale aumentata.

Batch processes remain a cornerstone of fine chemical and pharmaceutical manufacturing, offering flexibility and control in the synthesis of complex molecules. This course provides students with a comprehensive understanding of batch processing from a chemical engineering perspective. It bridges theoretical knowledge with practical tools essential for the design, analysis, and optimization of batch systems. Through a combination of lectures and applied case studies, students will develop the ability to critically assess process challenges, select appropriate technologies, and implement strategies for safe, sustainable, and efficient batch production. Emphasis is placed on real-world applications, integrating scientific principles with industrial pragmatism.

Lectures and exercises will enable the students to:
Understand the fundamental principles of batch chemical processing;
Analyze and design batch reactors and separation steps;
Apply scheduling and sequence control strategies to multi-step batch operations;
Identify and manage safety and environmental aspects of batch manufacturing;
Evaluate the role of equipment design and process intensification in batch systems.

Introduction: industrial background, product definitions, motivation for the use of batch processing.
Batch process design: process chemistry, process design, development of reliable process recipes, recipe implementation, pilot scale features, process scale-up.
Reactors: modeling and optimization of batch and semi-batch reactors, reaction kinetics and integration with process control, temperature control and heat transfer in reacting systems.
Agitation and mixing: principles of mixing and agitation in batch systems, scale-up challenges and mixing time estimation, impact of mixing on reaction selectivity and separation efficiency.
Solvents in batch production: solvent properties, solvent effects on reaction, solvent recovery and solvent destruction.
Separations: design and operation of batch separation units, including batch distillation, crystallization, and filtration.
Scheduling of batch processes: single and multiple product batch plants, transfer policies, parallel/intermediate units, sizing of vessels, inventory, NLP design of single- and multi-product plants optimization.
Safety and environmental aspects: hazard identification, selection of safety measures, waste minimization, waste treatment and solvent management.

Prova scritta obbligatoria, senza prove in itinere
The final assessment will be conducted through a written exam. Students will be required to answer questions covering all topics discussed during the lectures and solve exercises related to the industrial case studies.

slides of lectures and study cases (available via WeBeep) https://webeep.polimi.it/login/index.php
P.N. Sharrat, Ed., Handbook of Batch Process Design, Editore: Chapman & Hall, Anno edizione: 1997
E. Korovessi & A. A. Linninger, Eds., Batch Processes, Editore: CRC Press, Anno edizione: 2006

This course is designed to provide participants with a foundational understanding of the objectives of business entities, the principles of financial accounting, and the core tools used to support informed business decision-making.

Upon successful completion of the course, the student will be able to:
1) Understand and explain the objectives and purposes of a business entity.
2) Understand the purpose and structure of financial statements.
3) Understand and apply cost analysis techniques and investment evaluation tools.

Introduction
Business objectives and sustainability; Key stakeholders and their roles; Business structures and types of business entities.
Financial accounting
Nature and purpose of financial accounting; Balance sheet; Income statment; Analysis and interpretation of financial statements.
Management accounting
Cost behavior and classification; Cost allocation methods; Cost-Volume-Profit (CVP) analysis for short-term decision making.
Capital budgeting
Strategic and financial considerations in long-term investment decisions; Discounting principles and time value of money; Capital budgeting techniques: Net Present Value (NPV), Profitability Index (PI), Payback Period, and Internal Rate of Return (IRR).
Please note that the Business Organization course is integrated with the Production Systems course, for a total of 10 ECTS credits (5+5 credits). The teaching activities are divided in two sequential parts: September–October is dedicated to Business Organization; November–December focuses on Production Systems.

Prova scritta obbligatoria, con prove in itinere
Prova orale condizionata (a scelta del docente)
Student assessment is based on a mandatory written examination that includes both theoretical questions and numerical exercises, covering the two components of the course: Business Organization and Production Systems. To successfully pass the exam, students must obtain a minimum overall score of 18 out of 30, and earn at least 5 points in each of the two components (Business Organization and Production Systems).
An oral examination is also part of the assessment process, with the following conditions:

• It is mandatory for students who score 28/30 or above in the written exam, to confirm the final grade.
• It is optional, upon request, for students scoring between 24/30 and 27/30.
• It is not permitted for students who score below 24/30 on the written exam.
  Students may also opt to take the final exam in the form of two midterm exams:
• The first midterm (November) will cover the Business Organization module.
• The second midterm (during the first official winter exam session) will cover the Production Systems module.
• The same rules regarding the oral exam apply to the combined score of the two midterms.
• Please note: Partial scores from the midterm exams are only valid until the first winter exam session.
  Note: Students who are enrolled only in the 5-credit Business Organization course are subject to the same rules as above. In this case, it is strongly recommended to contact the course instructor to clarify administrative and assessment procedures.

Guerini Massimiliano, Slides and materials provided by the instructors during the course (available on WeBeep)
Birt, Brooks, Chalmers, Maloney, Oliver, Accounting. Business Reporting for Decision Making., Editore: Wiley, Anno edizione: 2018, ISBN: 978-0-730-36295-1
Note: 6th Edition

Understand the nature and peculiarities of projects, programme and portfolios. Understand role of projects in society and workplace and the difference between project management success and project success. Understand the sustainability and unsustainability aspects of project management.
Identify, in the context of projects: stakeholders, cost elements, risk and opportunities, options to plan and deliver projects.
Design strategies to engage stakeholders, financial structures, risk management frameworks.
Develop the scope of the project, project plans, strategies to plan and deliver sustainable projects.

After successful completion of this module students:
Will gain a holistic understanding of project business and project ecology (Knowledge and understanding);
Will be able to understand key project management concepts, their evaluation and application (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative project management tools, processes and methods at the different project and system life cycle stages (Applying knowledge and evaluating);
Will be able to critically assess projects and programmes considering scope, risk, stakeholders, sustainability (Applying knowledge and evaluating)
Will be able to propose delivery models considering the different dimensions of project success. (Evaluating and creating)

Projects are the key elements of our time; they are needed to plan and deliver infrastructure, address a global pandemic like COVID-19, or deal with climate change. Projects span across industries and economic sectors, including construction projects, the development of new major software, making movies, but also humanitarian projects. This course aims at transferring to students theoretical and practical knowledge about Project Management, Business, and Ecology. The course addresses the state-of-the-art approaches, methods and models for deciding, planning, and delivery projects and programmes. Including traditional “Project Management” topics, the course covers the essentials of project business (e.g. the governance of the organisations involved in projects) and the most recent elements of the project ecology. More specifically:
Introduction to Project Management, Project Business and Project Ecology: Introduction of key concepts such as project, programme, portfolio, project-based company. Managing for stakeholders, stakeholders relationship maps, project governance and project Ecology
Traditional Project Management models, tools and techniques: Scope management including WBS and other structures, Economic and Financial (with exercise on NPV, IRR, Project Balance), Planning and scheduling, Critical Path Method and its limitations (with numerical exercises), Cost Estimating, Project Controlling and its implications for re-planning; Risk Management (definition, identification, evaluation, mitigation, contingency, reporting),
Modern topics of Project management: Mega and complex project, human biases, Project management success vs project success, Sustainability (including SDG) & Dark side (modern slavery, corruption, sexism etc.),
This module's learning experience includes face-to-face lectures, numerical exercises, case discussions, real examples.

Prova scritta obbligatoria, senza prove in itinere
Written test: focused on assessing the learning outcomes. It will include a mix of theoretical questions and numerical exercises. Exemples of test and solutions are available in WeBeep

Jeffery Pinto, Project Management: Achieving Competitive Advantage - 5th edition, Anno edizione: 2019

La Radioprotezione è una disciplina che trova applicazione in ogni pratica in cui viene fatto uso delle radiazioni ionizzanti: dall’impianto nucleare, al reparto ospedaliero di medicina nucleare.
L’obiettivo l'insegnamento si propone è quello di fornire i fondamenti della Radioprotezione. Gli studenti devono acquisire familiarità con nuove grandezze fisiche non incontrate in altri insegnamenti e deve crescere in loro la sensibilità verso le problematiche associate alle misure ed alle valutazioni radioprotezionistiche. Per questi motivi agli studenti verranno illustrati i principi di funzionamento degli strumenti più diffusi nell'ambito della radioprotezione con particolare enfasi alle corrette modalità d’impiego. Le considerazioni e valutazioni dosimetriche saranno infine confrontate con i limiti ed i vincoli imposti dalla normativa nazionale. Nell'ambito dell'iniziativa "Green Ambassador", nelle lezioni verrà illustrato l'impatto radiologico legato alla dispersione nell'ambiente di contaminanti radioattivi rilasciati da un impianto nucleare in normale operatività o in situazione incidentale. Analoghe considerazioni verranno estese a gravi incidenti radiologici.
L'insegnamento viene offerto sia a studenti dei corsi di laurea triennale, generalmente come propedeutico per la successiva laurea magistrale in Ingegneria Nucleare, sia a quelli delle lauree magistrali, per particolari corsi di laurea, quali Ingegneria Biomedica, Ingegneria della Prevenzione e della Sicurezza nell'industria di processo, Ingegneria Elettrica, ecc.

lo studente:
conosce le nozioni teoriche fondamentali della radioprotezione.
ha proprietà di linguaggio, conosce il lessico specialistico utilizzato e non confonde tra loro le numerose grandezze fisiche utilizzate in radioprotezione.
è in grado di analizzare un problema reale e di impostarne la soluzione utilizzando gli strumenti teorici acquisiti nelle lezioni e gli esempi illustrati.
è in grado di valutare correttamente il rischio in caso di presenza di campi di radiazioni ionizzanti o di contaminanti radioattivi nell'ambiente.

Le radiazioni ionizzanti e grandezze fisiche correlate. Le prime ore di lezione costituiscono una sorta di introduzione agli argomenti trattati nel corso. Verranno descritte le principali sorgenti di radiazioni: radionuclidi naturali ed artificiali, le macchine radiogene. Saranno illustrate le grandezze fisiche fondamentali per la caratterizzazione di dette sorgenti.
Interazioni della radiazione con la materia. Verranno illustrati i principali fenomeni di interazione della radiazione ionizzante con la materia finalizzati alla descrizione del danno biologico.
Grandezze radiometriche e dosimetriche. In questa parte del corso verranno presentate le grandezze fisiche fondamentali per la dosimetria e le relazioni che intercorrono tra esse.
Strumentazione per la rivelazione delle radiazioni ionizzanti. Verranno presi in rassegna i principali strumenti utilizzati per la rivelazione delle radiazioni ionizzanti e i dosimetri maggiormente impiegati per la valutazione delle dosi individuali.
Tecniche di protezione dalle radiazioni. Saranno illustrate le tecniche di protezione dalle radiazioni ionizzanti che devono essere impiegate per limitare l’esposizione dei lavoratori e della popolazione.
Calcolo delle schermature. Verrà fatto un breve cenno alle tecniche utilizzate per la progettazione delle schermature richieste nell’impiego di macchine radiogene e sorgenti radioattive di varia natura.

Prova orale obbligatoria
La prova finale consiste in un esame orale articolato generalmente su domande relative agli aspetti teorici o a casi realistici per i quali si chiede di descrivere il corretto approccio dal punto di vista radioprotezionistico. Durante l'esame viene valutata la capacità di esposizione e l'uso appropriato del linguaggio tecnico. In tal caso potrebbe essere richiesta qualche semplice valutazione numerica, finalizzata all'accertamento della padronanza delle tecniche illustrate a lezione.L'esame inizia sempre con l'esposizione da parte del candidato di un argomento a sua scelta tra quelli trattati nel corso delle lezioni.

Campi F., dispense del docente
Note: scaricabili in WeBeep
Polvani Carlo, Elementi di radioprotezione, Editore: ENEA, Anno edizione: 1993 https://www.pubblicazioni.enea.it/component/jdownloads/?task=download.send&id=403&catid=3&m=0&Itemid=101
Note: scaricabile in internet
Pelliccioni Maurizio, Fondamenti fisici della Radioprotezione, Editore: Pitagora
Knoll G. F., Radiation Detection and Measurement, Editore: John Wiley & Sons

Compared to the past, the chemical industry (not only in Italy) is nowadays characterized by the much more significant presence of highly diversified sectors, such as fine chemicals, specialty chemicals and pharmaceuticals. In such industrial sectors, plants and processes are typically discontinuous. Moreover, some of the reactions performed are significantly fast and exothermic, thus implying potential safety issues, which can be even more critical for discontinuous reactors. This because, for the same plant productivity, a discontinuous reactor is normally larger than a continuously operated one to compensate the idle times burdening the production cycle. The reaction mass hold-up is therefore higher, as well as the potential magnitude of its uncontrolled decomposition or release in the environment.
After an introductory but fundamental section dedicated to the macrokinetic characterization of heterogeneous reaction systems, the first part of the course aims to provide Students with useful criteria for selecting and monitoring safe and productive conditions of a discontinuous reactor in which a potentially runaway reaction is performed, even in the absence of all the necessary information to address the problem using standard simulation approaches. This is particularly important when dealing with fine chemical processes, for which a detailed characterization of each reaction system is normally unavailable, because of the huge process fragmentation and the constant evolution towards ever-new products.
The second part of the course addresses the reactor protection against overpressures resulting from incidental conditions.
The third part of the course deals with environmental safety problems, such as carbon capture and storage.
Finally, the objective of the last part of the course is providing Students with the ability to perform the analysis of a real discontinuous process, from its lab design to the safe industrial scale-up.

The Student:

• has a practical understanding of the influence of mass-transfer phenomena on the conversion rate in heterogeneous reaction systems, with reference to the main involved plant parameters under the operator’s control,
• has a complete knowledge of the safety criteria for selecting the operating conditions of discontinuous reactors in which potentially runaway reactions are performed;
• is able to select, starting from the lab recipe, safe and productive operating conditions of the industrial reactor monitoring them during the normal reactor operation;
• is able to properly select and size pressure relief systems for the protection of the reactor against overpressures due to the loss of control of potentially runaway reaction systems;
• is able to deal with environmental safety problems;
• is able to analyze a real discontinuous process, with a full confidence of the involved quantities and expected orders of magnitude.

Macroscopic mass and energy balances for discontinuous and semi-continuous reaction systems (single-phase systems and two-phase liquid-liquid systems): definition and characterization of the slow reaction, fast reaction, and instantaneous reaction regimes, correlations for the estimation of physical and transport parameters; dimensionless balance equations and physical meaning of the arising model parameters. Methods for identifying and monitoring safe and productive operating conditions of semi-continuous exothermic reaction systems (the boundary diagram method; the temperature diagram method; kinetic-free methods). Thermal instability of substances and mixtures. Decomposition temperature and its experimental significance. Thermal analysis: TG, DTA, DSC; adiabatic calorimetry: ARC, Phi TEC II; reaction calorimetry: RC1. Selection and sizing of emergency pressure relief systems in chemical reactors (PSV and RD; vapor, gassy and hybrid systems; single-phase and multi-phase reliefs; sizing and rating criteria for PSV and RD; Omega method for calculating the flow capacity of the relief system). Analysis of a selected set of discontinuous processes of industrial relevance

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, senza revisioni periodiche, con presentazione/discussione finale
A few weeks before the end of the lectures, a real industrial case will be assigned to the students.
The oral exam begins with the request to present and discuss the assigned industrial case in approximately 10 minutes. During these first 10 minutes of the oral exam, the examiner does not intervene. At the end of these first 10 minutes, two different situations may occur, described below:
1. The student's presentation was seriously insufficient. In this case, the exam ends with the result "Rimandato."
2. The student's presentation was sufficient. In this case, the exam continues (and then ends with a grade between "Rimandato" and "30 Lode") with questions aimed to verify the practical understanding of the topics covered all along the Course, with particular emphasis on the physical significance of the methods and tools and their industrial application.
For each official exam period, a few data will be defined for the project discussion and oral exam; the students are required to enroll on one of the available data through WeBeep and to confirm their choiche in presence at the official date/hour available on the Online Service.
Enrolling through the official Online Service is mandatory to give the oral examination.

K.R. Westerterp, W.P.M. van SwaaiJ, A.A.C.M. Beenackers, Chemical Reactor Design and Operation, Editore: John Wiley and Sons, Anno edizione: 2001
J. Etchells, J. Wilday, Workbook for chemical reactor relief system sizing, Editore: Health and safety executive, Anno edizione: 1998, ISBN: 0717613895
Paolo Cardillo, Incidenti in ambiente chimico - guida allo studio e alla valutazione delle reazioni fuggitive, Editore: Stazione Sperimentale per i Combustibili - San Donato Milanese, Anno edizione: 1998
Note: in Italian
F. Maestri, R. Rota, Thermally safe operation of liquid-liquid semibatch reactors. Part I. Slow reactions, Editore: Elsevier, Anno edizione: 2005, Fascicolo: Chem. Eng. Sci. 60, 3309-3322
F. Maestri, R. Rota, Thermally safe operation of liquid-liquid semibatch reactors. Part II. Fast reactions, Editore: Elsevier, Anno edizione: 2005, Fascicolo: Chem. Eng. Sci. 2005, 60, 5590-5602
F. Maestri, R. Rota, Temperature diagrams for preventing decomposition or side reactions in liq.-liq. semibatch reactors, Editore: Elsevier, Anno edizione: 2006, Fascicolo: Chem. Eng. Sci. 2006, 61, 3068-3078
F. Maestri, R. Rota, Kinetic-free safe operation of fine chemical runaway reactions: a general criterion, Editore: Elsevier, Anno edizione: 2016, Fascicolo: Ind. Eng. Chem. Res. 55, 925-933
F. Maestri, R. Rota, Simple Monitoring of Semibatch Polymerization Processes: An Integrated Criterion, Editore: Elsevier, Anno edizione: 2017, Fascicolo: Ind. Eng. Chem. Res. 56, 7434-7444

The goals of the course are:
To provide the students with methods and procedures to build summaries and graphical representations of a set of data
To introduce the students to the tools (technical language and models) to represent and analyze random phenomena
To introduce the students to the fundamental methods of statistical inference
To enable the students to apply the statistical methods and techniques object of the course to real data through the use of an appropriate statistical software

Knowledge and understanding.
Having successfully taken the course examination, the students are expected to
know the foundational principles of probability and statistics;
know the correct terminology of probability and statistics and to be able to correctly argument the theory.
The students’ knowledge and comprehension is expected not be limited to the enunciation of definitions and results and to the solution of standard exercises, but rather to be critical and enabling to distinguish among different situations and to take appropriate choices, justifying the followed procedures.
Ability of applying knowledge and understanding.
Having successfully taken the course examination, the students are expected to
be able to apply the attained knowledge to specific problems of data analysis;
be able to select the principles which are useful to obtain the solutions to the problems at hand;
be able to elicit relevant indicators and summaries from large amounts of data.

Summarizing data and descriptive analysis. Types of data, frequency distributions, position and shape indexes (mean, median, quantiles, variance, standard deviation, range, interquartile range,..), histograms, boxplots and other frequency graphs. Summary statistics and visualization of pair of random variables; covariance and correlation.
Probability and random variables. Properties of probability, conditional probability and independence. Random variables, mean and variance, properties of means and variances, covariance between two random variables. Family of discrete random variables (Bernoulli, Binomial, Poisson, Hypergeometric distributions), family of continuous random variables (Exponential, Gaussian, t-Student distributions). Central Limit Theorem.
Estimation and testing. Sampling distributions, properties of estimators (bias and MSE), confidence intervals, testing a hypothesis, principles of significance tests, significance levels and types of error, power of a test. Test for the mean of a Gaussian sample (z-test, t-test).
Comparing samples. Comparing the means of two independent Gaussian samples (t-test), comparing the means of two dependent Gaussian samples (paired t-test).
Regression models. Univariate and multivariate linear models, least squares estimators of the parameters of a linear models, tests and confidence intervals for the parameters of a linear model, prediction of a new observation, goodness of fit methods, analysis of the residuals

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course assessment will consist of two parts, namely a written exam and a team project. Both parts are mandatory.
The written exam will be taken in one of the dates scheduled by the School within the academic year; it will consist of 2 exercises, to be solved autonomously in maximum 2:00 hours. At the end of the exam the student will decide whether or not to have their exam evaluated. The written exam will be evaluated with a score expressed in a scale from 0 to 30, the maximum evaluation being 32/30. The written exam will be passed upon obtaining a score greater than or equal to 18/30. The exam evaluation will account for the degree of clarity of the exposition and for the correctness of computations. During the examination, the students will not be allowed to use books or notes, nor to use the mobile phone or other electronic devices. The students will be allowed to use the calculator, the statistical tables and a formulary of A4 format containing any material deemed useful by the student.
The team project will consist of an analysis of a real dataset, to be conducted in teams of 2 to 4 students, using the models and methods introduced in the course. The team projects will be presented at the end of the course in a seminar during an open workshop that will take place after the end of the semester. Each team will receive an evaluation in a scale from 0 to 30.
The final evaluation of the course will be obtained as a weighted average of the scores obtained by the student in the two parts of the assessment, with weights 0.7 (written exam) and 0.3 (team project).
During the exam, the students will have to
Demonstrate the degree of knowledge and comprehension of the key aspects of the course, presenting the used methodologies in a clear and exhaustive way;
Demonstrate their ability to apply the learned notions to solve exercises and real problems, on any of the topics covered in the course.

Montgomery D.C., Runger G.C., Hubele N.F., Engineering Statistics, Editore: Wiley, Anno edizione: 2010
Note: 5th edition
Ieva F., Masci C., Paganoni A.M., Laboratorio di Statistica con R, Editore: Pearson, Anno edizione: 2016

Industries play the crucial role in enabling and accelerating the transition towards the sustainable development. While this transition is an imperative for abating the climate change and ensure the livable future, it also becomes an indispensable condition for companies to retain competitive advantage and to remain at the market. The course is designed to provide students with concepts and instruments necessary for understanding and analysing industrial practices in terms of their sustainability performance (with a particular focus on environmental performance). The course starts with the principles of industrial ecology, sustainable development, and circular economy concepts. Then, technologies and production practices at company and industrial system levels are introduced and the approaches for their deployment are discussed.
The course is organised in lectures, in-class exercises, and project work.

Identify and analyse opportunities for improving sustainability of industrial processes
Examine the impact of identified measures on sustainability performance of industrial processes
Present solutions and ideas in a professional and constructive way, fostering the value of the teamwork, and using a language adequate to both managers and fellow students

The role of sustainable development and circular economy in transforming production practices and industrial systems
Industrial Symbiosis

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final exam will be based on the public presentation of the group work. Students will face periodic reviews of their project during the whole semester.

The global energy transition is reshaping the way energy is produced, transported, and consumed. This course explores the value chains of natural gas and emerging low-carbon energy carriers, providing students with the engineering knowledge needed to understand the technologies that will shape future energy systems.
The first part of the course examines the natural gas value chain, covering resource production, gas treatment processes, and transportation technologies. As the world's leading transition fuel, natural gas is examined from both technological and environmental perspectives, highlighting its contribution to energy security and its role in supporting the integration of renewable energy sources.
Building on this foundation, the second part of the course explores the value chains of the most promising low-carbon energy carriers, examining their production routes, infrastructure requirements, and end-use applications. Their technological maturity, advantages, and limitations are critically compared with those of natural gas, enabling students to assess their potential role in achieving a secure and net-zero energy system.
A distinctive feature of the course is its strong connection with industrial practice. Delivered through the innovative Co-tutela con mondo esterno teaching format, the course is co-developed with experts from Saipem, one of the world's leading engineering and construction companies in the energy sector, providing students with direct exposure to real-world engineering projects, industrial challenges, and state-of-the-art technologies shaping the global energy transition.

Upon completion of the course, students will be able to:
demonstrate a comprehensive understanding of the technologies, processes, and challenges associated with the natural gas value chain ( conoscenza e comprensione – knowledge and understanding );
apply the acquired knowledge to analyze engineering problems and select appropriate technologies for the production, treatment, and transportation of natural gas ( capacità di applicare conoscenza e comprensione – applying knowledge and understanding );
use the process simulation software ASPEN HYSYS ® to develop and analyze process flowsheets ( conoscenza e comprensione – knowledge and understanding );
critically evaluate and compare the value chains of natural gas and emerging low-carbon energy carriers, assessing their role in the energy transition ( autonomia di giudizio – making judgements );
independently apply the acquired knowledge to new case studies by integrating information from technical literature, textbooks, and industrial reports ( capacità di apprendimento – learning skills ).

The course is based on lectures and on development and discussion of real-life case studies, taught in innovative teaching mode in collaboration with experts from Saipem.
In the main part of the course, all the key technical aspects in the gas production and transportation value chain will be covered:
Key players: gas companies, oilfield service providers, EPC general contractors, gas transportation players;
Gas supply and demand: growth prospects; role of gas in overall global energy picture; conventional and unconventional reserves; natural gas liquids and associated gas, energy transition;
Gas production technologies: from traditional gas fields onshore to offshore; emphasis on fracking to produce shale gas; gas from offshore fields; deepwater exploitation and associate subsea production technologies; challenges of Arctic fields current permitting scenarios;
Design of gas purification processes: acid gas removal technologies (amine washing, physical absorption, PSA, membranes); conventional CO 2 removal processes cryogenic ones; treatment of ultra-sour gas, handling and valorization of gas fields by-products, dehydration, mercury removal and Natural Gas Liquids (NGLs) recovery;
Transportation and storage: key design criteria and challenges in gas transportation via long-distance pipelines, onshore and offshore; LNG (Liquefied Natural Gas) value chain, liquefaction processes and technologies, specialized LNG vessels and carriers, regasification terminals, onshore and offshore;
Gas applications for energy: power production, pivotal role in balancing electric grids with power generation also from renewable sources; domestic and industrial gas usage; direct use of LNG or CNG (Compressed Natural Gas) as clean fuels in automotive and marine transportation;
Biogas as a peculiar natural gas: biogas characteristics; biogas cleaning and upgrading; biomethane distribution through the existing gas grids, LBG production.
Then, taking natural gas as a reference, a general description of the value chain of the most relevant energy carriers (hydrogen, ammonia, methanol, liquid organic hydrogen carriers, e-fuels and biofuels), possible substitute of natural gas on the long-term, will be carried out and a comparison with the natural gas value chain will be performed.
Exercises will focus on case studies in accordance with Saipem. The simulation software (Aspen HYSYS ® ), commonly employed by engineering companies, will be used to solve flowsheets, by simulation of the process and related analyses.

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
Assessment is based on a written examination covering all the topics addressed during the course. Students who achieve a mark ≥ 26 in the written exam will also be required to take an oral examination to further assess the depth of their knowledge and understanding.
In addition, each student is required to prepare a short technical report summarizing the exercises and case studies discussed throughout the course. The report must be submitted to the instructor before the examination.
Detailed information on the examination procedures is available on the WeBeep platform.
Upon successfully completing the course, students are expected to demonstrate a thorough understanding of the course topics, discuss them critically using appropriate engineering terminology, and show that they have achieved the intended learning outcomes described in the “ Risultati di apprendimento attesi ” section.

The slides of the lessons and additional material provided by Saipem will be shared on WeBeep platform early before the lesson.

We are in the era of large, decentralized, distributed environments where the amount of devices and data, and their heterogeneity, is getting out of control.
Organizations capture billions of bytes of data about their activities, users, operators, customers and suppliers, but their ability to collect, manage and interpret this information could be an obstacle to its use. The web is widening the range of data providers and consumers. Sensors, mobile devices, and, in general, the IoT generate additional data that needs to be integrated and harmonized with the rest to create value.
Decision-making is based on information, not just on data. More accurate information leads to better decisions and provides competitive advantages; hence processing, manipulating, and organizing data in a way that adds new knowledge has become a necessary issue.
The goal of the course is to enable students to master the engineering methods and processes that are necessary to manage modern information systems, and especially data-intensive systems, to operate on large data collections, and to understand the utility and methods of data analytics (i.e., business analysis and machine learning algorithms), obtaining useful knowledge to improve decision-making processes.
As a consequence, we expose the students to some of the most advanced methodologies adopted to understand the conceptual and technological problems encountered in the design and implementation of "data products": tangible results based on analyses for complex systems, concentrating, as raw material, on collections of data that must be integrated, organized and analyzed mainly through automatic tools.
In the belief that understanding is boosted by communication, this course is “Communication-Intensive”, in the sense that it aims at enhancing the students’ communication skills as applied to the technical content of the course, with a special emphasis on clarity and common ground (i.e. being able to take the interlocutors’ body of knowledge into proper account).

Dublin Descriptors
Expected learning outcomes
1. Knowledge and understanding
The students will learn how to:
Identify the phases of Big Data management, from the choice of the data sources to the production of a “data product”
Analyze the data sources and design a data integration system
Design a data warehouse
Identify the data quality problems encountered when managing heterogeneous collections of data
2. Applying knowledge and understanding
Given specific project cases, students will be able to:
Detail the corresponding requirements
Analyze and comment on specific conceptual and architectural choices
Apply the theory to decide the most appropriate ones
Develop data integration and data warehouse solutions fulfilling the high-level and design specifications.
3. Making judgements
Given a relatively complex problem, students will be able to:
Analyze and understand the goals, assumptions and requirements associated with that problem and model them
Define the type of architecture of the corresponding system
Identify the appropriate conceptual and logical design methodology
Estimate the system and the resources needed for its development
4. Communication
The students will learn to clearly explain a technological or methodological issue at the correct level of abstraction, considering the common ground with the interlocutor.
5. Lifelong learning skills
The students will learn how to develop a realistic data product

Information System Architectures and Heterogeneous Data Integration: structured and non-structured data:
Introduction to the architectures of modern information systems
Basics of Data Integration: model heterogeneity, semantic heterogeneity at the schema level, heterogeneity at the data level
Dynamic and lightweight data integration: the use of wrappers, mediators, meta-models, ontologies, etc
The future of data integration
Data Quality
Data Warehousing:
Data Warehouse Architecture and querying
Data Warehouse Conceptual Design
Data Warehouse Logical Design
New research trends
Communication Skills
Basic elements of Communication Sciences (how to be clear)
Common-ground Theory
Writing skills
NOTES:

• The bibliography includes useful references and is by no means exhaustive of the topics covered in the course. More readings will be mentioned during the lectures. The students are advised to attend the lectures, ask the professor for explanations and read the articles. For each of the books, only the part included in the lectures is mandatory.

Prova scritta obbligatoria, senza prove in itinere
The assessment will be based on a written exam and a homework communication assignment. The exam is considered as passed if both parts have been passed. If the student does not pass one of these two parts in the same exam call, the mark of the passed part will be saved; in a future call, the student will need to retake only the failed part.
The written exam consists of (i) an exercise/design part, consisting in the design of an integration system or of a data warehouse; (ii) a theoretical part, in which the students will be asked to explain clearly, in their own words, two of the subjects illustrated during the lectures. The scores of the two written parts will be summed up to compute the total score. Students can take the written part at any exam session during the same academic year.
The homework communication assignment requires the students to summarize a technical text, having in mind a non-technical reader. The assignment will be evaluated by the communication instructor. The evaluation will be “pass/non-pass”; in case of excellence, one additional point will be assigned to the student in the overall score of the exam.
The following table provides a detailed overview of the elements that will be considered in the various assessment activities.
Type of assessment
Description
Dublin descriptor
Written test
Exercises focusing on design aspects:
Design of a data integration system based on the requirements provided
or
Design of a data warehouse based on the requirements provided
Three theoretical questions on the course topics
Communication assignment: summarization of a research paper in words understandable by a non-technical reader.
1,2,3,5
1, 2, 3, 4, 5

The course provides the fundamental principles of thermodynamics to be applied in the study of single and multicomponent systems resembling the main scenarios occurring in process industry and industrial equipment (e.g., separation of products, production of components via chemical reactions). In particular, the aim is to give an overview of the principles to be applied in the estimation of liquid-vapor equilibrium and phase separation, reaction equilibrium and rate.

Passing the exam, the student will:
know the fundamental principles of mass and energy balance equations, phase equilibrium and phase equilibrium in presence of chemical reaction
apply the theoretical aspects to specific problems, mimicking industrial processes
provide a critical analysis and comment the obtained outcomes, eventually proposing alternatives

Introduction to thermodynamics: meaning of thermodynamics. Definition of isolated, closed and open systems. Extensive and intensive state variables. First and second law of thermodynamics.
Perfect gas and correlated properties. Phase diagrams (P-v, P-T, T-v)
Equations of state: Van der Waals, introduction to cubic equations, corresponding state. Estimation of Gibbs energy and residual properties.
Direct and indirect methods to calculate the properties of liquid phase.
Phase equilibrium: characteristic thermodynamic variables, Clausius Clapeyron equation, Antoine equation, concept of fugacity
Mixtures: properties, definition of partial molar property, Gibbs theorem for perfect gases and evaluation of the ideal gas mixture properties
Liquid mixtures: definition of ideal mixture and calculation of the thermodynamic properties. Indirect methods, Lewis-Randall rule. Definition of excess properties. Activity coefficient.
Vapor-liquid equilibrium (VLE): Gibbs phase rule, qualitative evaluation of liquid-vapor equilibrium and phase diagram (T-P-composition). Azeotrope definition. Boiling point and dew point. Rault laws.
Supercritical compounds: definition and fundamental properties. Henry constant.
Multicomponent systems: mass balance, energy balance and reaction conditions

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
The final evaluation consists of two parts: a written exam and an oral exam.
The written exam is aimed to test and verify the problem-solving ability of the student in specific thermodynamic contests. The correct use of equations, the correct results and critical comments of the outcomes will be evaluated.
The oral exam consists in two questions regarding the topics of the course. The student should demonstrate the knowledge of the discussed argument, using the technical vocabulary and showing the ability to support an oral independent discussion.
The oral exam can be performed only following an evaluation of at least 18/30 in the written part.
The final mark will be the average of the written and oral parts.

R. Rota, Fondamenti di termodinamica dell'ingegneria chimica, Editore: Pitagora edizioni Bologna
C. Borgnakke, R. E. Sonntag, Fundamentals of Thermodynamics, International Adaptation, Editore: John Wiley & Sons Inc, Anno edizione: 2022
R.E. Sonntag, C. Borgnakke, Fundalmentals of thermodynamics, Editore: John Wiley & Sons Inc, Anno edizione: 2003
Notes of the lecturer

The course provides the fundamental principles of thermodynamics to be applied in the study of single and multicomponent systems resembling the main scenarios occurring in process industry and industrial equipment (e.g., separation of products, production of components via chemical reactions). In particular, the aim is to give an overview of the principles to be applied in the estimation of liquid-vapor equilibrium and phase separation, reaction equilibrium and rate.

Passing the exam, the student will:
know the fundamental principles of mass and energy balance equations, phase equilibrium and phase equilibrium in presence of chemical reaction
apply the theoretical aspects to specific problems, mimicking industrial processes
provide a critical analysis and comment the obtained outcomes, eventually proposing alternatives

Introduction to thermodynamics: meaning of thermodynamics. Definition of isolated, closed and open systems. Extensive and intensive state variables. First and second law of thermodynamics.
Perfect gas and correlated properties. Phase diagrams (P-v, P-T, T-v)
Equations of state: Van der Waals, introduction to cubic equations, corresponding state. Estimation of Gibbs energy and residual properties.
Direct and indirect methods to calculate the properties of liquid phase.
Phase equilibrium: characteristic thermodynamic variables, Clausius Clapeyron equation, Antoine equation, concept of fugacity
Mixtures: properties, definition of partial molar property, Gibbs theorem for perfect gases and evaluation of the ideal gas mixture properties
Liquid mixtures: definition of ideal mixture and calculation of the thermodynamic properties. Indirect methods, Lewis-Randall rule. Definition of excess properties. Activity coefficient.
Vapor-liquid equilibrium (VLE): Gibbs phase rule, qualitative evaluation of liquid-vapor equilibrium and phase diagram (T-P-composition). Azeotrope definition. Boiling point and dew point. Rault laws.
Supercritical compounds: definition and fundamental properties. Henry constant.
Multicomponent systems: mass balance, energy balance and reaction conditions

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
The final evaluation consists of two parts: a written exam and an oral exam.
The written exam is aimed to test and verify the problem-solving ability of the student in specific thermodynamic contests. The correct use of equations, the correct results and critical comments of the outcomes will be evaluated.
The oral exam consists in two questions regarding the topics of the course. The student should demonstrate the knowledge of the discussed argument, using the technical vocabulary and showing the ability to support an oral independent discussion.
The oral exam can be performed only following an evaluation of at least 18/30 in the written part.
The final mark will be the average of the written and oral parts.

R. Rota, Fondamenti di termodinamica dell'ingegneria chimica, Editore: Pitagora edizioni Bologna
C. Borgnakke, R. E. Sonntag, Fundamentals of Thermodynamics, International Adaptation, Editore: John Wiley & Sons Inc, Anno edizione: 2022
R.E. Sonntag, C. Borgnakke, Fundalmentals of thermodynamics, Editore: John Wiley & Sons Inc, Anno edizione: 2003
Notes of the lecturer

The course provides an introduction to mass and energy transport. Particular attention is devoted to analogy between the two phenomena. The presence of chemical reactions is also accounted for.
1. Heat transport. Energy balance equation. Conduction. Fourier's Law. Conductivity. Forced convection. Laminar and turbulent flow. Free convection. Heat exchangers and overall heat transfer coefficient. Radiative heat transfer.
2. Mass transport. Mass balance equation. Diffusion. Fick's law. Diffusion coefficients and their estimation. Mass convection. Diffusion at high transfer rates. Penetration theory
3. Chemical kinetics. Mass and energy balance of reacting systems.