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MDD-based performability analysis of multi-state linear consecutive-k-out-of-n: F systems

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  • Mo, Yuchang
  • Xing, Liudong
  • Cui, Lirong
  • Si, Shubin

Abstract

A multi-state linear consecutive-k-out-of-n: F system, MLC(k,n) consists of n components ordered in a line, which fails if at least k consecutive components have failed. It abounds in real-world applications such as wireless sensor networks, microwave station networks, and oil pipeline systems. Performability of an MLC(k,n) system is concerned with probability that the system performs at a performance state characterized in terms of the largest number of consecutive failed components. This paper proposes a multi-valued decision diagram (MDD)-based approach to model and evaluate performability of an MLC(k,n) system with heterogeneous components following arbitrary lifetime distributions. The proposed approach encompasses a novel and efficient MDD model generation procedure. Both complexity analysis and illustrative examples are provided to show efficiency of the proposed MDD approach. As demonstrated through examples, the proposed MDD approach is also applicable to MLC(k,n) systems with non-identical reparable components and component importance analysis.

Suggested Citation

  • Mo, Yuchang & Xing, Liudong & Cui, Lirong & Si, Shubin, 2017. "MDD-based performability analysis of multi-state linear consecutive-k-out-of-n: F systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 124-131.
    • Handle: RePEc:eee:reensy:v:166:y:2017:i:c:p:124-131
    DOI: 10.1016/j.ress.2016.08.027
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    References listed on IDEAS

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    1. Mo, Yuchang & Xing, Liudong & Amari, Suprasad V. & Bechta Dugan, Joanne, 2015. "Efficient analysis of multi-state k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 95-105.
    2. Borgonovo, E., 2007. "Differential, criticality and Birnbaum importance measures: An application to basic event, groups and SSCs in event trees and binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1458-1467.
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    Cited by:

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    2. Mo, Yuchang & Xing, Liudong & Zhang, Lejun & Cai, Shaobin, 2020. "Performability analysis of multi-state sliding window systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    3. Sheng, Yuhong & Ke, Hua, 2020. "Reliability evaluation of uncertain k-out-of-n systems with multiple states," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    4. Chen, Yiming & Liu, Yu & Jiang, Tao, 2021. "Optimal maintenance strategy for multi-state systems with single maintenance capacity and arbitrarily distributed maintenance time," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Eryilmaz, Serkan & Devrim, Yilser, 2019. "Reliability and optimal replacement policy for a k-out-of-n system subject to shocks," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 393-397.
    6. Tian-yuan, Ye & Lin-lin, Liu & He-wei, Pang & Yuan-zi, Zhou, 2023. "Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    7. Zaitseva, Elena & Levashenko, Vitaly & Rabcan, Jan, 2023. "A new method for analysis of Multi-State systems based on Multi-valued decision diagram under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    8. Lu, Shaoqi & Shi, Daimin & Xiao, Hui, 2019. "Reliability of sliding window systems with two failure modes," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 366-376.
    9. Zhai, Qingqing & Xing, Liudong & Peng, Rui & Yang, Jun, 2018. "Aggregated combinatorial reliability model for non-repairable parallel phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 242-250.
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    11. Wang, Chaonan & Wang, Shuli & Xing, Liudong & Guan, Quanlong, 2023. "Efficient performability analysis of dynamic multi-state k-out-of-n: G systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    12. Zhou, Kai-Li & Cheng, De-Jun & Zhang, Han-Bing & Hu, Zhong-tai & Zhang, Chun-Yan, 2023. "Deep learning-based intelligent multilevel predictive maintenance framework considering comprehensive cost," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    13. Dui, Hongyan & Tian, Tianzi & Zhao, Jiangbin & Wu, Shaomin, 2022. "Comparing with the joint importance under consideration of consecutive-k-out-of-n system structure changes," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

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