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Uncertainty analysis of common cause failure in safety instrumented systems

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  • W Mechri
  • C Simon
  • K Ben Othman

Abstract

This paper analyses the problem of epistemic uncertainty in assessing the performance of safety instrumented systems (SIS) using fault trees. The imperfect knowledge concerns the common cause failure (CCF) involved in the SIS in low demand mode. The point-valued CCF factors are replaced by fuzzy numbers, allowing experts to express their uncertainty about the CCF values. This paper shows how these uncertainties propagate through the fault tree and how this induces an uncertainty to the values of the SIS failure probability on demand and to the safety integrity level of the SIS. For the sake of verification and comparison, and to show the exactness of the approach, a Monte Carlo sampling approach is proposed, where by a uniform or triangular second-order probability distribution of CCF factors is considered.

Suggested Citation

  • W Mechri & C Simon & K Ben Othman, 2011. "Uncertainty analysis of common cause failure in safety instrumented systems," Journal of Risk and Reliability, , vol. 225(4), pages 450-460, December.
    • Handle: RePEc:sae:risrel:v:225:y:2011:i:4:p:450-460
    DOI: 10.1177/1748007810395668
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    References listed on IDEAS

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    1. Dutuit, Y. & Innal, F. & Rauzy, A. & Signoret, J.-P., 2008. "Probabilistic assessments in relationship with safety integrity levels by using Fault Trees," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1867-1876.
    2. Vaurio, Jussi K., 2007. "Consistent mapping of common cause failure rates and alpha factors," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 628-645.
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    Cited by:

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    2. Simon, Christophe & Bicking, Frédérique, 2017. "Hybrid computation of uncertainty in reliability analysis with p-box and evidential networks," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 629-638.

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