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Component state-based integrated importance measure for multi-state systems

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  • Si, Shubin
  • Levitin, Gregory
  • Dui, Hongyan
  • Sun, Shudong

Abstract

Importance measures in reliability engineering are used to identify weak components and/or states in contributing to the reliable functioning of a system. Traditionally, importance measures do not consider the possible effect of groups of transition rates among different component states, which, however, has great effect on the component probability distribution and should therefore be taken into consideration. This paper extends the integrated importance measure (IIM) to estimate the effect of a component residing at certain states on the performance of the entire multi-state systems. This generalization of IIM describes in which state it is most worthy to keep the component to provide the desired level of system performance, and which component is the most important to keep in some state and above for improving the performance of the system. An application to an oil transportation system is presented to illustrate the use of the suggested importance measure.

Suggested Citation

  • Si, Shubin & Levitin, Gregory & Dui, Hongyan & Sun, Shudong, 2013. "Component state-based integrated importance measure for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 75-83.
    • Handle: RePEc:eee:reensy:v:116:y:2013:i:c:p:75-83
    DOI: 10.1016/j.ress.2013.02.023
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    References listed on IDEAS

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    Cited by:

    1. Dui, Hongyan & Si, Shubin & Yam, Richard C.M., 2017. "A cost-based integrated importance measure of system components for preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 98-104.
    2. Fan, Dongming & Zhang, Aibo & Feng, Qiang & Cai, Baoping & Liu, Yiliu & Ren, Yi, 2021. "Group maintenance optimization of subsea Xmas trees with stochastic dependency," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    4. Dui, Hongyan & Si, Shubin & Wu, Shaomin & Yam, Richard C.M., 2017. "An importance measure for multistate systems with external factors," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 49-57.
    5. Hu, Yishuang & Lin, Yu & Ding, Yi & Chen, Xingying & Zeng, Zhiguo, 2021. "Screening of optimal structure among large-scale multi-state weighted k-out-of-n systems considering reliability evaluation," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    6. Lu, H.W. & Pan, H.Y. & He, L. & Zhang, J.Q., 2016. "Importance analysis of off-grid wind power generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 999-1007.
    7. Fangyu Liu & Hongyan Dui & Ziyue Li, 2022. "Reliability analysis for electrical power systems based on importance measures," Journal of Risk and Reliability, , vol. 236(2), pages 317-328, April.
    8. Dui, Hongyan & Wei, Xuan & Xing, Liudong, 2023. "A new multi-criteria importance measure and its applications to risk reduction and safety enhancement," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    9. Dui, Hongyan & Si, Shubin & Yam, Richard C.M., 2018. "Importance measures for optimal structure in linear consecutive-k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 339-350.
    10. Jiangbin Zhao & Mengtao Liang & Rongyu Tian & Zaoyan Zhang & Xiangang Cao, 2023. "Reliability Optimization of Hybrid Systems Driven by Constraint Importance Measure Considering Different Cost Functions," Mathematics, MDPI, vol. 11(20), pages 1-21, October.
    11. Wu, Shaomin & Chen, Yi & Wu, Qingtai & Wang, Zhonglai, 2016. "Linking component importance to optimisation of preventive maintenance policy," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 26-32.
    12. Chen, Liwei & Cheng, Chunchun & Dui, Hongyan & Xing, Liudong, 2022. "Maintenance cost-based importance analysis under different maintenance strategies," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    13. Lyu, Dong & Si, Shubin, 2020. "Dynamic importance measure for the K-out-of-n: G system under repeated random load," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    14. Liu, Mingli & Wang, Dan & Si, Shubin, 2024. "Solving algorithm design for the cost minimization reliability optimization model driven by a novel cost-based importance measure," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    15. Hongyan Dui & Kaixin Liu & Shaomin Wu, 2024. "Data-driven reliability and resilience measure of transportation systems considering disaster levels," Annals of Operations Research, Springer, vol. 340(1), pages 217-243, September.
    16. Vaisman, Radislav & Sun, Yuting, 2021. "Reliability and importance measure analysis of networks with shared risk link groups," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    17. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    18. Liu, Mingli & Wang, Dan & Zhao, Jiangbin & Si, Shubin, 2022. "Importance measure construction and solving algorithm oriented to the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 222(C).

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