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Scheda Riassuntiva
Anno Accademico 2019/2020
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Docente Zio Enrico
Cfu 10.00 Tipo insegnamento Monodisciplinare
Didattica innovativa L'insegnamento prevede  2.0  CFU erogati con Didattica Innovativa come segue:
  • Cotutela con mondo esterno
  • Blended Learning & Flipped Classroom

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing - Civ (Mag.)(ord. 270) - MI (489) INGEGNERIA PER L'AMBIENTE E IL TERRITORIO - ENVIRONMENTAL AND LAND PLANNING ENGINEERING*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Ing Ind - Inf (1 liv.)(ord. 270) - MI (347) INGEGNERIA CHIMICA*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Ing Ind - Inf (Mag.)(ord. 270) - BV (478) NUCLEAR ENGINEERING - INGEGNERIA NUCLEARE*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Ing Ind - Inf (Mag.)(ord. 270) - MI (422) INGEGNERIA DELLA PREVENZIONE E DELLA SICUREZZA NELL'INDUSTRIA DI PROCESSO*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Ing Ind - Inf (Mag.)(ord. 270) - MI (472) CHEMICAL ENGINEERING - INGEGNERIA CHIMICA*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B
Ing Ind - Inf (Mag.)(ord. 270) - MI (487) MATHEMATICAL ENGINEERING - INGEGNERIA MATEMATICA*AZZZZ054248 - RELIABILITY ENGINEERING AND QUANTITATIVE RISK ANALYSIS A+B

Obiettivi dell'insegnamento

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.


Risultati di apprendimento attesi

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.


Argomenti trattati

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.


Prerequisiti

Probability and Statistics


Modalità di valutazione

 

Modalità di valutazione

The evaluation consists in an exam consisting in a written and an oral part.

The written exam 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). This part of the exam serves as an “entrance gate” for being admitted at the oral exam.

The oral exam aims at 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 oral exam will define the final grade (100%).


Bibliografia
Risorsa bibliografica obbligatoriaEnrico Zio, Introduction to the basics of reliability and risk analysis, Editore: World scientific, Anno edizione: 2007
Note:

Part I of the course

Risorsa bibliografica obbligatoriaEnrico Zio, Computational methods for reliability and risk analysis, Editore: World Scientific, Anno edizione: 2009
Note:

Note: Part II of the course

Risorsa bibliografica facoltativaPiero Baraldi, Francesco Cadini, Enrico Zio, Introduction to reliability and risk analysis: worked out problems, Editore: World Scientific, Anno edizione: 2011
Note:

Exercises, useful for preparing the written test for the exam

Risorsa bibliografica facoltativaEnrico Zio, The Monte Carlo Simulation Method for System Reliability and Risk Analysis, Editore: Springer, Anno edizione: 2012
Note:

Monte Carlo simulation methods for reliability and availability analysis

Risorsa bibliografica facoltativaTerje Aven, Piero Baraldi, Roger Flage and Enrico Zio, Uncertainty in risk assessment, Editore: Wiley, Anno edizione: 2014
Risorsa bibliografica facoltativaEmanuele Borgonovo, Sensitivity Analysis: An Introduction for the Management Scientist, Editore: Springer, Anno edizione: 2019

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
65:00
97:30
Esercitazione
35:00
52:30
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 100:00 150:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
02/04/2020