Journal of Failure Analysis and Prevention

, Volume 14, Issue 3, pp 426–434 | Cite as

Unification of Common Cause Failures’ Parametric Models Using a Generic Markovian Model

Technical Article---Peer-Reviewed

Abstract

The main objective of this paper is to provide a unified Markov model which could implement any parametric models devoted to the treatment of common cause failures (CCFs), namely: beta factor, multiple greek letter, alpha factor, multiple beta factor, and binomial failure rate. The choice of the Markovian representation is motivated by the fact that classical reliability approaches (e.g., Fault trees) are not able to catch the dynamic aspect induced by CCF events. The proposed Markovian model is also capable of dealing with any M-out-of-N configuration. It is illustrated on the basis of a system made up of four identical components (N = 4) in order to quantitatively examine the differences between the first four mentioned parametric models. For that purpose, the considered performance indicators are the average unavailability (U avg) and the average unconditional failure intensity (i.e., failure frequency) (w avg).

Keywords

Common cause failures Parametric models Unified Markov model MooN architectures 

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Copyright information

© ASM International 2014

Authors and Affiliations

  1. 1.IHSI-LRPIBatna UniversityBatnaAlgeria

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