Complex systems fiability

The aim of the module is to introduce learners to reliability analysis and synthesis. Quantifying the reliability of systems has become a major objective in the design of complex systems. Reliability is a key aspect of product and system quality. The complexity of these systems extends the range of failure modes to which they are exposed. In a context where uncertainties are significant, it is important to develop the tools needed to predict and optimise the reliability of complex systems. The presentation used in this module is original, combining tools from stochastic mechanics and artificial intelligence. The combination of these two approaches makes it possible to deal with systems based on knowledge models (equations of motion, conservation equations, etc.) and 'black box' type systems based on learning techniques. This second family greatly extends the range of possible reliable syntheses.

• Part I: Failure modes and basic concepts o Concepts of safety and quality o Standards in force o Failure classification o Notions of failure probabilities o Usual laws o ...
• Part II: Reliability analysis techniques o Probabilistic approaches o FORM method o SORM method o Finite elements and reliability o System reliability testing o Reliability optimisation
• Part III: Reliability synthesis techniques o Learning techniques o Reliability diagrams and networks o Bayesian approaches o Advanced approaches to reliability synthesis o Reliability and databases