Monte Carlo Methods for Reliability Estimation and Failure Prognostics

Enrico Zio (1, 2, 3)

1 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec
2 LGI - Laboratoire Génie Industriel - EA 2606
3 Dipartimento di Energia [Milano]

Monte Carlo Simulation (MCS) offers a powerful means for modeling the stochastic failure behaviour of engineered structures, systems and components (SSC). This paper summarises current work on advanced MCS methods for reliability estimation and failure prognostics.

Mots clés: Monte Carlo simulation; reliability; subset sampling; line sampling; failure prognostics; particle filtering

Enrico Zio. Monte Carlo Methods for Reliability Estimation and Failure Prognostics. COMPLEX DATA MODELING AND COMPUTATIONALLY INTENSIVE STATISTICAL METHODS, Springer, pp.138-151, 2010, Contributions to Statistics. ⟨hal-00609116⟩