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Predictive inference for system reliability after common-cause component failures

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  • Coolen, Frank P.A.
  • Coolen-Maturi, Tahani

Abstract

This paper presents nonparametric predictive inference for system reliability following common-cause failures of components. It is assumed that a single failure event may lead to simultaneous failure of multiple components. Data consist of frequencies of such events involving particular numbers of components. These data are used to predict the number of components that will fail at the next failure event. The effect of failure of one or more components on the system reliability is taken into account through the system׳s survival signature. The predictive performance of the approach, in which uncertainty is quantified using lower and upper probabilities, is analysed with the use of ROC curves. While this approach is presented for a basic scenario of a system consisting of only a single type of components and without consideration of failure behaviour over time, it provides many opportunities for more general modelling and inference, these are briefly discussed together with the related research challenges.

Suggested Citation

  • Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2015. "Predictive inference for system reliability after common-cause component failures," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 27-33.
    • Handle: RePEc:eee:reensy:v:135:y:2015:i:c:p:27-33
    DOI: 10.1016/j.ress.2014.11.005
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    References listed on IDEAS

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    1. Abdullah H Al-nefaiee & Frank PA Coolen, 2013. "Nonparametric predictive inference for system failure time based on bounds for the signature," Journal of Risk and Reliability, , vol. 227(5), pages 513-522, October.
    2. D M Rasmuson & D L Kelly, 2008. "Common-cause failure analysis in event assessment," Journal of Risk and Reliability, , vol. 222(4), pages 521-532, December.
    3. Frank PA Coolen & Tahani Coolen-Maturi & Abdullah H Al-nefaiee, 2014. "Nonparametric predictive inference for system reliability using the survival signature," Journal of Risk and Reliability, , vol. 228(5), pages 437-448, October.
    4. Debón, A. & Carrión, A. & Cabrera, E. & Solano, H., 2010. "Comparing risk of failure models in water supply networks using ROC curves," Reliability Engineering and System Safety, Elsevier, vol. 95(1), pages 43-48.
    5. Troffaes, Matthias C.M. & Walter, Gero & Kelly, Dana, 2014. "A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 13-21.
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    7. Kelly, Dana & Atwood, Corwin, 2011. "Finding a minimally informative Dirichlet prior distribution using least squares," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 398-402.
    8. P Coolen-Schrijner & S C Shaw & F P A Coolen, 2009. "Opportunity-based age replacement with a one-cycle criterion," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1428-1438, October.
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    Cited by:

    1. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.
    2. Huang, Xianzhen & Aslett, Louis J.M. & Coolen, Frank P.A., 2019. "Reliability analysis of general phased mission systems with a new survival signature," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 416-422.
    3. Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2016. "The structure function for system reliability as predictive (imprecise) probability," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 180-187.
    4. Yongquan, Sun & Xi, Chen & He, Ren & Yingchao, Jin & Quanwu, Liu, 2016. "Ordering decision-making methods on spare parts for a new aircraft fleet based on a two-sample prediction," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 40-50.
    5. Rychlik, Tomasz, 2017. "Evaluations of quantiles of system lifetime distributions," European Journal of Operational Research, Elsevier, vol. 256(3), pages 935-944.
    6. Mi, Jinhua & Beer, Michael & Li, Yan-Feng & Broggi, Matteo & Cheng, Yuhua, 2020. "Reliability and importance analysis of uncertain system with common cause failures based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    7. Walter, Gero & Flapper, Simme Douwe, 2017. "Condition-based maintenance for complex systems based on current component status and Bayesian updating of component reliability," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 227-239.
    8. Reed, Sean, 2017. "An efficient algorithm for exact computation of system and survival signatures using binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 257-267.
    9. Zarezadeh, Somayeh & Asadi, Majid, 2019. "Coherent systems subject to multiple shocks with applications to preventative maintenance," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 124-132.
    10. Hindolo George-Williams & Geng Feng & Frank PA Coolen & Michael Beer & Edoardo Patelli, 2019. "Extending the survival signature paradigm to complex systems with non-repairable dependent failures," Journal of Risk and Reliability, , vol. 233(4), pages 505-519, August.
    11. Jinlei Qin & Zheng Li, 2019. "Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure," Complexity, Hindawi, vol. 2019, pages 1-8, May.

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