Monte Carlo Simulation in Dependability Analysis (ISTE Invoiced)

System dependability is a complex task to grasp and analyze since it encompasses reliability, maintainability, availability, failure mode analysis and feared events. For operational safety analyses, reliability is a quantitative basis for the other disciplines of maintainability, availability and safety. Reliability metrics such as failure rate or MTBF are often misused as they are only valid for low-maintenance applications, and wrongly for others, as MTBF is only relevant for availability. In addition, in operational safety, many equations do not have explicit solutions, and Monte Carlo simulations are a little-used way of obtaining and/or confirming the solution obtained by numerical methods.

Monte Carlo Simulation in Dependability Analysis fills this gap as best as we can. This task is a difficult one, since operational safety is a cross-disciplinary activity in the engineering sciences – cross-disciplinary in that it must be present throughout a product’s life cycle.

Franck Bayle trained as an electronic engineer. He has practiced for almost 15 years, working at Crouzet and then at Thalès in Valence, France. He has also worked as Design Authority in reliability and maturity.

Laurent Denis is the CEO of StatXpert, a consulting, training, and software company specializing in statistics and operational reliability based in Pessac, France.

Adrien Gigliati is Dependability Engineer at Thalès in Valence, France.