RELIABILITY, SAFETY AND RISK ANALYSIS

INSTRUCTOR: PIERO BARALDI

LECTURES

Lecture 1: Introduction to the Course

Lecture 2: Interpretation of Probability in Reliability and Risk Analysis

(Lecture 3: Flipped Class)

Lecture 4: Basic Notions of Probability Theory – Continuos PD

Lecture 5: Reliability of Simple Systems

Lecture 6: Availability and Maintainability

Lecture 7: Markov chain discrete time

Lecture 8: Markov chain continuous time

Lecture 9: Monte Carlo Simulation for Reliability and Availability Analyses

Lecture 10: Maintenance, Basic Concepts

Lecture 11: Estimation of reliability parameters from experimental data: Frequentist approach

Lecture 12: Estimation of components failure rates from statistical data: Bayesian approach

Lecture 13: Risk (Francesco Di Maio)

Lecture 14: Fault Tree Analysis

Lecture 15: Event Tree Analysis

Lecture 16: Dependent Failures

Lecture 17: Importance Measures

Lecture 18a: Artificial Intelligence (AI) for Safety

Lecture 18b: Laboratory of Analysis of Signals & Analysis of Risk


EXERCISE SESSIONS

Exercise Session 1: Probability

Exercise Session 2: Availability and Maintainability

Exercise Session 3: Markov Chain

Exercise Session 4a: Monte Carlo (Reliability and Availability estimation)

Exercise Session 4b: Monte Carlo (Definite integrals)

Exercise Session 5: Estimation of Reliability Parameters

Exercise Session 6: Fault Tree Analysis

Exercise Session 7: Event Tree Analysis

FLIPPED CLASS

Flipped Class 1 – Basic Notions of Probability Theory – Discrete PD

Flipped Class 1 – Exercises

Flipped Class 1 – Exercises Solutions

Flipped Class 2 – Bayesian Networks Slides

Flipped Class 2 – Material

Flipped Class 2 – Solutions


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