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.

I

PART A

Basics of probability theory for applications to reliability analysis and risk assessment (ELO A.1);

Estimation of reliability parameters from field data (ELO A.3);

Reliability of simple systems: series, parallel, redundancies, standby (ELO A.3);

Reliability and availability of complex systems subject 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 B

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.

The evaluation consists in an exam consisting in a written and an oral part, and in the development and presentation of a project.

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%).

For the first part A of the course

For the second part B of the course

Exercises, useful for preparing the written test for the exam

For the specific part on Monte Carlo methods, in the first part A of the course