Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation

G Merle (1) , J.-M Roussel (1) , J.-J Lesage (1) , V Perchet (2) , N Vayatis (3)

1 LURPA - Laboratoire Universitaire de Recherche en Production Automatisée
2 LPMA - Laboratoire de Probabilités et Modèles Aléatoires
3 CMLA - Centre de Mathématiques et de Leurs Applications

This paper focuses on the quantitative analysis of Dynamic Fault Trees (DFTs) by means of Monte Carlo simulation. In a previous article, we defined an algebraic framework allowing to determine the structure function of DFTs. We exploit this structure function and the minimal cut sequences that it allows to determine, to know the failure mode configuration of the system, which is an input of Monte Carlo simulation. We show that the results obtained are in good accordance with theoretical results and that some results, such as importance measures and sensitivity indexes, are not provided by common quantitative analysis and yet interesting. We finally illustrate our approach on a DFT example from the literature.

Mots clés: Dynamic Fault Tree; quantitative analysis; Monte Carlo simulation

Domaines: Automatique / Robotique

G Merle, J.-M Roussel, J.-J Lesage, V Perchet, N Vayatis. Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation. Quality and Reliability Engineering International, 2014, 32 (1), pp.7-18. ⟨10.1002/qre.1728⟩. ⟨hal-01282160⟩