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Assessment of redundant systems with imperfect coverage by means of binary decision diagrams

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  • Myers, Albert F.
  • Rauzy, Antoine

Abstract

In this article, we study the assessment of the reliability of redundant systems with imperfect fault coverage. We term fault coverage as the ability of a system to isolate and correctly accommodate failures of redundant elements. For highly reliable systems, such as avionic and space systems, fault coverage is in general imperfect and has a significant impact on system reliability. We review here the different models of imperfect fault coverage. We propose efficient algorithms to assess them separately (as k-out-of-n selectors). We show how to implement these algorithms into a binary decision diagrams engine. Finally, we report experimental results on real life test cases that show on the one hand the importance of imperfect coverage and on the other hand the efficiency of the proposed approach.

Suggested Citation

  • Myers, Albert F. & Rauzy, Antoine, 2008. "Assessment of redundant systems with imperfect coverage by means of binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 1025-1035.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:7:p:1025-1035
    DOI: 10.1016/j.ress.2007.05.002
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    Citations

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    Cited by:

    1. Anil Kr. Aggarwal & Sanjeev Kumar & Vikram Singh, 2016. "Mathematical modeling and fuzzy availability analysis of skim milk powder system of a dairy plant," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(1), pages 322-334, December.
    2. Briš, Radim, 2010. "Exact reliability quantification of highly reliable systems with maintenance," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1286-1292.
    3. Qingqing Zhai & Rui Peng & Liudong Xing & Jun Yang, 2013. "Binary decision diagram-based reliability evaluation of k-out-of-(n + k) warm standby systems subject to fault-level coverage," Journal of Risk and Reliability, , vol. 227(5), pages 540-548, October.
    4. Peng, Rui & Zhai, Qingqing & Xing, Liudong & Yang, Jun, 2014. "Reliability of demand-based phased-mission systems subject to fault level coverage," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 18-25.
    5. Peng, Rui & Mo, Huadong & Xie, Min & Levitin, Gregory, 2013. "Optimal structure of multi-state systems with multi-fault coverage," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 18-25.
    6. Wang, Yujie & Xing, Liudong & Levitin, Gregory & Huang, Ning, 2018. "Probabilistic competing failure analysis in phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 37-51.
    7. Levitin, Gregory & Xing, Liudong & Luo, Liang, 2019. "Influence of failure propagation on mission abort policy in heterogeneous warm standby systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 29-38.
    8. Radim Briš & Petr Byczanski, 2017. "On innovative stochastic renewal process models for exact unavailability quantification of highly reliable systems," Journal of Risk and Reliability, , vol. 231(6), pages 617-627, December.
    9. R Briš & P Byczanski, 2010. "Direct unavailability computation of a maintained highly reliable system," Journal of Risk and Reliability, , vol. 224(3), pages 159-170, September.

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