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Binary decision diagram-based reliability evaluation of k-out-of-(n + k) warm standby systems subject to fault-level coverage

Author

Listed:
  • Qingqing Zhai
  • Rui Peng
  • Liudong Xing
  • Jun Yang

Abstract

Warm standby sparing is a fault-tolerance technique that attempts to improve system reliability while compromising the system energy consumption and recovery time. However, when the imperfect fault coverage effect (an uncovered component fault can propagate and cause the whole system to fail) is considered, the reliability of a warm standby sparing can decrease with an increasing level of the redundancy. This article studies the reliability of a warm standby sparing subject to imperfect fault coverage, in particular, fault level coverage where the coverage probability of a component depends on the number of failed components in the system. The suggested approach is combinatorial and based on a generalized binary decision diagrams technique. The complexity for the binary decision diagram construction is analyzed, and several case studies are given to illustrate the application of the approach.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:risrel:v:227:y:2013:i:5:p:540-548
    DOI: 10.1177/1748006X13485562
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    References listed on IDEAS

    as
    1. 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.
    2. Yun, Won Young & Cha, Ji Hwan, 2010. "Optimal design of a general warm standby system," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 880-886.
    3. Levitin, Gregory & Amari, Suprasad V., 2008. "Multi-state systems with multi-fault coverage," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1730-1739.
    4. Hsu, Ying-Lin & Lee, Ssu-Lang & Ke, Jau-Chuan, 2009. "A repairable system with imperfect coverage and reboot: Bayesian and asymptotic estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2227-2239.
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    Cited by:

    1. Huang, Wei & Loman, James & Song, Thomas, 2015. "A reliability model of a warm standby configuration with two identical sets of units," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 237-245.
    2. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Heterogeneous 1-out-of-N warm standby systems with online checkpointing," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 127-136.
    3. Dui, Hongyan & Li, Shumin & Xing, Liudong & Liu, Hanlin, 2019. "System performance-based joint importance analysis guided maintenance for repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 162-175.
    4. Shin, Sung Min & Jeon, In Seop & Kang, Hyun Gook, 2015. "Surveillance test and monitoring strategy for the availability improvement of standby equipment using age-dependent model," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 100-106.
    5. Levitin, Gregory & Jia, Heping & Ding, Yi & Song, Yonghua & Dai, Yuanshun, 2017. "Reliability of multi-state systems with free access to repairable standby elements," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 192-197.
    6. Mo, Yuchang & Xing, Liudong & Zhong, Farong & Pan, Zhusheng & Chen, Zhongyu, 2014. "Choosing a heuristic and root node for edge ordering in BDD-based network reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 83-93.
    7. Hu, Bin & Seiler, Peter, 2015. "Pivotal decomposition for reliability analysis of fault tolerant control systems on unmanned aerial vehicles," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 130-141.

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