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Dynamic assessment of multi-state systems using phase-type modeling

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  • Eryilmaz, Serkan

Abstract

Multi-state systems have attracted great attention due to their wide applications in engineering. They have been effectively used in modeling various systems such as power supply systems and transportation systems. In this paper, phase type modeling is proposed for dynamic assessment of nonrepairable multi-state systems when the system degrades according to a Markov process. The utility of phase type modeling is demonstrated in the computation of mean lifetimes, mean residual lifetimes, and derivation of survival functions of series and parallel systems. A stochastic comparison result between two systems is also obtained using phase representations of survival functions. Extensive numerical results are presented to illustrate the applicability of the approach.

Suggested Citation

  • Eryilmaz, Serkan, 2015. "Dynamic assessment of multi-state systems using phase-type modeling," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 71-77.
  • Handle: RePEc:eee:reensy:v:140:y:2015:i:c:p:71-77
    DOI: 10.1016/j.ress.2015.03.037
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    References listed on IDEAS

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    1. Anatoly Lisnianski, 2012. "L z -Transform for a Discrete-State Continuous-Time Markov Process and its Applications to Multi-State System Reliability," Springer Series in Reliability Engineering, in: Anatoly Lisnianski & Ilia Frenkel (ed.), Recent Advances in System Reliability, chapter 0, pages 79-95, Springer.
    2. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, March.
    3. Faghih-Roohi, Shahrzad & Xie, Min & Ng, Kien Ming & Yam, Richard C.M., 2014. "Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 57-62.
    4. Eryilmaz, Serkan & Rıza Bozbulut, Ali, 2014. "An algorithmic approach for the dynamic reliability analysis of non-repairable multi-state weighted k-out-of-n:G system," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 61-65.
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    Cited by:

    1. Funda Iscioglu & Aysegul Erem, 2021. "Reliability analysis of a multi-state system with identical units having two dependent components," Journal of Risk and Reliability, , vol. 235(2), pages 241-252, April.
    2. Jafary, Bentolhoda & Fiondella, Lance, 2016. "A universal generating function-based multi-state system performance model subject to correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 16-27.
    3. Tavangar, Mahdi & Bairamov, Ismihan, 2015. "On conditional residual lifetime and conditional inactivity time of k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 225-233.
    4. Funda Iscioglu, 2017. "Dynamic performance evaluation of multi – state systems under non – homogeneous continuous time Markov process degradation using lifetimes in terms of order statistics," Journal of Risk and Reliability, , vol. 231(3), pages 255-264, June.
    5. Li, Jingkui & Lu, Yuze & Liu, Xiaona & Jiang, Xiuhong, 2023. "Reliability analysis of cold-standby phased-mission system based on GO-FLOW methodology and the universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Eryilmaz, Serkan, 2016. "A reliability model for a three-state degraded system having random degradation rates," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 59-63.
    7. Min Gong & Serkan Eryilmaz & Min Xie, 2020. "Reliability assessment of system under a generalized cumulative shock model," Journal of Risk and Reliability, , vol. 234(1), pages 129-137, February.

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