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Performability analysis of multi-state sliding window systems

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  • Mo, Yuchang
  • Xing, Liudong
  • Zhang, Lejun
  • Cai, Shaobin

Abstract

This paper models and evaluates the performability of a sliding window system (SWS) with multi-state components. Different components may have different numbers of states, characterized by state probability and performance rate distributions. Multiple consecutive components form groups with identical or different sizes. The accumulation (sum) of performance rates of components within the same group defines the group performance; the minimum of the group performance defines the system performance. The performability of an SWS is concerned with the probability that the system performs at a particular system performance. In this paper, a multi-valued decision diagram (MDD)-based analytical approach is proposed for the performability analysis of SWSs. The approach encompasses a compact system MDD generation based on the group MDD generation and combination, and evaluation of the resultant MDD model to obtain the system performability measures. Case studies are performed to demonstrate the proposed MDD approach as well as effects of component allocation on the system performability.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s0951832020305044
    DOI: 10.1016/j.ress.2020.107003
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    References listed on IDEAS

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    1. Hui Xiao & Rui Peng & Gregory Levitin, 2016. "Optimal replacement and allocation of multi‐state elements in k‐within‐m‐from‐r/n sliding window systems," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 32(2), pages 184-198, March.
    2. Konak, Abdullah & Kulturel-Konak, Sadan & Levitin, Gregory, 2012. "Multi-objective optimization of linear multi-state multiple sliding window system," Reliability Engineering and System Safety, Elsevier, vol. 98(1), pages 24-34.
    3. 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.
    4. Xiao, Hui & Shi, Daimin & Ding, Yi & Peng, Rui, 2016. "Optimal loading and protection of multi-state systems considering performance sharing mechanism," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 88-95.
    5. Levitin, Gregory & Ben-Haim, Hanoch, 2011. "Consecutive sliding window systems," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1367-1374.
    6. 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.
    7. Levitin, Gregory & Xing, Liudong & Ben-Haim, Hanoch & Huang, Hong-Zong, 2019. "Dynamic demand satisfaction probability of consecutive sliding window systems with warm standby components," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 397-405.
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    Cited by:

    1. Xiao, Hui & Lin, Chen & Kou, Gang & Peng, Rui, 2022. "Reliability modeling and configuration optimization of a photovoltaic based electric power generation system," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    2. Wang, Wei & Fang, Chao & Liu, Shan & Xiang, Yisha, 2021. "Reliability analysis and optimization of multi-state sliding window system with sequential demands and time constraints," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    3. Wang, Wei & Fang, Chao & Wang, Yan & Li, Jin, 2022. "Reliability Modeling and Optimization of Circular Multi-State Sliding Time Window System with Sequential Demands," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

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