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Computational method for importance measure of the k-out-of-n system based on stress–strength interference

Author

Listed:
  • Dong Lyu
  • Shubin Si
  • Zhiqiang Cai
  • Liyang Xie

Abstract

Importance measures, which are used to evaluate the relative significance of various components to system reliability, have been widely applied in system reliability designs and risk assessments. This article deals with the importance measure for the k -out-of- n system of which components are loaded by common stress. Based on system-level stress–strength interference model, a new computational method for the Birnbaum importance measure is proposed for the k -out-of- n system. Then, two numerical examples are presented to further illustrate the proposed method and some key contents are discussed particularly as follows: (1) the importance measures for the system with s -identical components and nonidentical components are developed, (2) component importance changes as its own strength distribution parameters change and (3) the new method corrects the errors caused by ignoring the failure dependency.

Suggested Citation

  • Dong Lyu & Shubin Si & Zhiqiang Cai & Liyang Xie, 2020. "Computational method for importance measure of the k-out-of-n system based on stress–strength interference," Journal of Risk and Reliability, , vol. 234(1), pages 27-40, February.
    • Handle: RePEc:sae:risrel:v:234:y:2020:i:1:p:27-40
    DOI: 10.1177/1748006X19872680
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    References listed on IDEAS

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    1. Eryilmaz, Serkan, 2018. "The number of failed components in a k-out-of-n system consisting of multiple types of components," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 246-250.
    2. Davies, Katherine & Dembińska, Anna, 2019. "On the number of failed components in a k-out-of-n system upon system failure when the lifetimes are discretely distributed," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 47-61.
    3. An, Zong-Wen & Huang, Hong-Zhong & Liu, Yu, 2008. "A discrete stress–strength interference model based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1485-1490.
    4. Godoy, David R. & Pascual, Rodrigo & Knights, Peter, 2013. "Critical spare parts ordering decisions using conditional reliability and stochastic lead time," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 199-206.
    5. 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.
    6. Cui, Lirong & Li, Haijun, 2007. "Analytical method for reliability and MTTF assessment of coherent systems with dependent components," Reliability Engineering and System Safety, Elsevier, vol. 92(3), pages 300-307.
    7. Zhang, Nan & Fouladirad, Mitra & Barros, Anne, 2019. "Reliability-based measures and prognostic analysis of a K-out-of-N system in a random environment," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1120-1131.
    8. Wang, Chaonan & Xing, Liudong & Levitin, Gregory, 2014. "Explicit and implicit methods for probabilistic common-cause failure analysis," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 175-184.
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