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

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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).

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Authors and Affiliations

  1. IHSI-LRPI, Batna University, 05 Avenue Chahid Mohamed Boukhlouf, 05000, Batna, Algeria

    Mourad Chebila & Fares Innal

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  1. Mourad Chebila
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  2. Fares Innal
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Correspondence to Mourad Chebila.

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Chebila, M., Innal, F. Unification of Common Cause Failures’ Parametric Models Using a Generic Markovian Model. J Fail. Anal. and Preven. 14, 426–434 (2014). https://doi.org/10.1007/s11668-014-9828-0

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  • DOI: https://doi.org/10.1007/s11668-014-9828-0

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