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Reliability and covariance estimation of weighted k-out-of-n multi-state systems

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  • Wang, Yong
  • Li, Lin
  • Huang, Shuhong
  • Chang, Qing

Abstract

In the literature of reliability engineering, reliability of the weighted k-out-of-n system can be calculated using component reliability based on the structure function. The calculation usually assumes that the true component reliability is completely known. However, this is not the case in practical applications. Instead, component reliability has to be estimated using empirical sample data. Uncertainty arises during this estimation process and propagates to the system level. This paper studies the propagation mechanism of estimation uncertainty through the universal generating function method. Equations of the complete solution including the unbiased system reliability estimator and the corresponding unbiased covariance estimator are derived. This is a unified approach. It can be applied to weighted k-out-of-n systems with multi-state components, to weighted k-out-of-n systems with binary components, and to simple series and parallel systems. It may also serve as building blocks to derive estimators of system reliability and uncertainty measures for more complicated systems.

Suggested Citation

  • Wang, Yong & Li, Lin & Huang, Shuhong & Chang, Qing, 2012. "Reliability and covariance estimation of weighted k-out-of-n multi-state systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 138-147.
    • Handle: RePEc:eee:ejores:v:221:y:2012:i:1:p:138-147
    DOI: 10.1016/j.ejor.2012.02.037
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    References listed on IDEAS

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    Cited by:

    1. Jorgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2021. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Papers 2112.10672, arXiv.org.
    2. Aboalkhair, Ahmad M. & Coolen, Frank P.A. & MacPhee, Iain M., 2013. "Nonparametric predictive reliability of series of voting systems," European Journal of Operational Research, Elsevier, vol. 226(1), pages 77-84.
    3. Serkan Eryilmaz & Ali Riza Bozbulut, 2019. "Reliability analysis of weighted- k -out-of- n system consisting of three-state components," Journal of Risk and Reliability, , vol. 233(6), pages 972-977, December.
    4. Xiaojun Liang & Yinghui Tang, 2019. "The improvement upon the reliability of the k-out-of-n:F system with the repair rates differentiation policy," Operational Research, Springer, vol. 19(2), pages 479-500, June.
    5. Nizar Mannai & Soufiane Gasmi, 2020. "Optimal design of k-out-of-n system under first and last replacement in reliability theory," Operational Research, Springer, vol. 20(3), pages 1353-1368, September.
    6. Qianru Ge & Willem van Jaarsveld & Zümbül Atan, 2020. "Optimal redesign decisions through failure rate estimates," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 254-271, June.
    7. Jing Li & Guodong Wang & Haofei Zhou & Honggen Chen, 2023. "Redundancy allocation optimization for multi-state system with hierarchical performance requirements," Journal of Risk and Reliability, , vol. 237(6), pages 1031-1047, December.
    8. Jørgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2023. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03634370, HAL.
    9. Eryilmaz, Serkan, 2015. "Capacity loss and residual capacity in weighted k-out-of-n:G systems," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 140-144.
    10. Faghih-Roohi, Shahrzad & Xie, Min & Ng, Kien Ming & Yam, Richard C.M., 2014. "Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 57-62.
    11. Jørgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2023. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Post-Print hal-03634370, HAL.
    12. Jørgen Vitting Andersen & Roy Cerqueti & Giulia Rotundo, 2017. "Rational expectations and stochastic systems," Documents de travail du Centre d'Economie de la Sorbonne 17060, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2019.
    13. Roy Cerqueti, 2022. "A new concept of reliability system and applications in finance," Annals of Operations Research, Springer, vol. 312(1), pages 45-64, May.
    14. Serkan Eryilmaz & Kadir Sarikaya, 2014. "Modeling and analysis of weighted-k-out-of-n: G system consisting of two different types of components," Journal of Risk and Reliability, , vol. 228(3), pages 265-271, June.
    15. 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.
    16. Fernández, Arturo J., 2015. "Optimum attributes component test plans for k-out-of-n:F Weibull systems using prior information," European Journal of Operational Research, Elsevier, vol. 240(3), pages 688-696.
    17. Jorgen-Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2023. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Annals of Operations Research, Springer, vol. 326(1), pages 295-316, July.
    18. Yonit Barron, 2018. "Group maintenance policies for an R-out-of-N system with phase-type distribution," Annals of Operations Research, Springer, vol. 261(1), pages 79-105, February.

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