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Importance factors of coherent systems: A review

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  • Yves Dutuit
  • Antoine Rauzy

Abstract

Importance factors are indicators of the risk significance of the components of a system. They are widely used in probabilistic safety analyses to rank components according to their contribution to the global risk. In this article, we review definitions and interpretations of importance factors in the case the support model is a coherent fault tree, and failures of components are described by basic events of that fault tree. First, we show that each importance factor characterizes the probability of a certain set of minterms. The notion of critical states, that is, minterms in which failing/repairing the component suffices to fail/repair the system, plays a central role in this process. Then, we discuss assessment algorithms for the two main technologies at hand: minimal cutsets and binary decision diagrams. Finally, we draw some practical conclusions from these developments. This article thus contributes to clarify mathematical and algorithmic foundations of importance factors.

Suggested Citation

  • Yves Dutuit & Antoine Rauzy, 2014. "Importance factors of coherent systems: A review," Journal of Risk and Reliability, , vol. 228(3), pages 313-323, June.
  • Handle: RePEc:sae:risrel:v:228:y:2014:i:3:p:313-323
    DOI: 10.1177/1748006X13512296
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    References listed on IDEAS

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    1. Vaurio, Jussi K., 2010. "Ideas and developments in importance measures and fault-tree techniques for reliability and risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 99-107.
    2. Contini, Sergio & Matuzas, Vaidas, 2011. "Analysis of large fault trees based on functional decomposition," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 383-390.
    3. Natvig, Bent, 1979. "A suggestion of a new measure of importance of system components," Stochastic Processes and their Applications, Elsevier, vol. 9(3), pages 319-330, December.
    4. Barlow, Richard E. & Proschan, Frank, 1975. "Importance of system components and fault tree events," Stochastic Processes and their Applications, Elsevier, vol. 3(2), pages 153-173, April.
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