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Efficient performability analysis of dynamic multi-state k-out-of-n: G systems

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  • Wang, Chaonan
  • Wang, Shuli
  • Xing, Liudong
  • Guan, Quanlong

Abstract

A dynamic multi-state k-out-of-n: G system, denoted by DMS(k, n, G) is a system where the system and its components exhibit multiple performance levels, and the system has different requirements on the number of working components in different states. DMS(k, n, G) abounds in both industrial and military applications. In this paper, a novel and efficient analytical method based on multi-valued decision diagrams (MDDs) is proposed for performability assessment of DMS(k, n, G) with non-identical components. Unlike existing approaches where multiple combination operations between models of lower performance levels are needed for constructing the model of a higher performance level, the proposed MDD generation algorithm constructs the system performability MDD in a top-down manner by considering multiple system state requirements simultaneously. A smart home lighting control system is analyzed to demonstrate the application of the proposed method. A detailed case study of an oil supply system is provided to verify the correctness of the proposed method and illustrate component sensitivity analysis. Complexity analysis and comprehensive empirical studies are performed to demonstrate that the efficiency of the proposed model construction is greatly improved as compared to the existing method, enabling fast model generation and efficient analysis of large-scale DMS(k, n, G).

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:237:y:2023:i:c:s0951832023002983
    DOI: 10.1016/j.ress.2023.109384
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    References listed on IDEAS

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    2. Oszczypała, Mateusz & Konwerski, Jakub & Ziółkowski, Jarosław & Małachowski, Jerzy, 2024. "Reliability analysis and redundancy optimization of k-out-of-n systems with random variable k using continuous time Markov chain and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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