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Reliability analysis in uncertain random system

Author

Listed:
  • Meilin Wen

    (Science and Technology on Reliability and Environmental Engineering Laboratory
    Beihang University)

  • Rui Kang

    (Science and Technology on Reliability and Environmental Engineering Laboratory
    Beihang University)

Abstract

Reliability analysis of a system based on probability theory has been widely studied and used. Nevertheless, it sometimes meets with one problem that the components of a system may have only few or even no samples, so that we cannot estimate their probability distributions via statistics. Then reliability analysis of a system based on uncertainty theory has been proposed. However, in a general system, some components of the system may have enough samples while some others may have no samples, so the reliability of the system cannot be analyzed simply based on probability theory or uncertainty theory. In order to deal with this type systems, this paper proposes a method of reliability analysis based on chance theory which is a generalization of both probability theory and uncertainty theory. In order to illustrate the method, some common systems are considered such as series system, parallel system, k-out-of-n system and bridge system.

Suggested Citation

  • Meilin Wen & Rui Kang, 2016. "Reliability analysis in uncertain random system," Fuzzy Optimization and Decision Making, Springer, vol. 15(4), pages 491-506, December.
    • Handle: RePEc:spr:fuzodm:v:15:y:2016:i:4:d:10.1007_s10700-016-9235-y
    DOI: 10.1007/s10700-016-9235-y
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    Citations

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    Cited by:

    1. Kuei-Hu Chang, 2022. "A novel reliability calculation method under neutrosophic environments," Annals of Operations Research, Springer, vol. 315(2), pages 1599-1615, August.
    2. Gao, Rong & Zhang, Shijie, 2024. "Reliability importance analysis of uncertain random k-out-of-n systems with multiple states," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Xu, Qinqin & Zhu, Yuanguo, 2022. "Reliability modeling of uncertain random fractional differential systems with competitive failures," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    4. Hu, Lunhu & Kang, Rui & Pan, Xing & Zuo, Dujun, 2020. "Risk assessment of uncertain random system—Level-1 and level-2 joint propagation of uncertainty and probability in fault tree analysis," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    5. Xinxin Wang & Zeshui Xu & Yong Qin, 2022. "Structure, trend and prospect of operational research: a scientific analysis for publications from 1952 to 2020 included in Web of Science database," Fuzzy Optimization and Decision Making, Springer, vol. 21(4), pages 649-672, December.
    6. Chen, Xin & Zhu, Yuanguo, 2021. "Optimal control for uncertain random singular systems with multiple time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    7. Rong Gao & Yan Sun & Dan A. Ralescu, 2017. "Order statistics of uncertain random variables with application to k-out-of-n system," Fuzzy Optimization and Decision Making, Springer, vol. 16(2), pages 159-181, June.
    8. Chen, Xin & Zhu, Yuanguo & Sheng, Linxue, 2021. "Optimal control for uncertain stochastic dynamic systems with jump and application to an advertising model," Applied Mathematics and Computation, Elsevier, vol. 407(C).

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