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Reliability assessment of a discrete time cold standby repairable system

Author

Listed:
  • Cihangir Kan

    (Xi’an Jiaotong-Liverpool University)

  • Serkan Eryilmaz

    (Atilim University)

Abstract

This paper is concerned with the study of a discrete time repairable system consisting of one active and one standby component. The lifetime and repair time are assumed to have discrete phase-type distributions. The system’s lifetime is represented as a compound random variable. A matrix-based expression for the probability generating function of the system’s lifetime is obtained based on the phase characteristics of lifetime and repair time distributions. The probability generating function is then used to obtain the distribution of the system’s lifetime. Reliability and hazard rate functions are computed and evaluated for some particular choices of lifetime and repair time distributions. The limiting behavior of the hazard rates is also investigated.

Suggested Citation

  • Cihangir Kan & Serkan Eryilmaz, 2021. "Reliability assessment of a discrete time cold standby repairable system," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 613-628, October.
  • Handle: RePEc:spr:topjnl:v:29:y:2021:i:3:d:10.1007_s11750-020-00586-7
    DOI: 10.1007/s11750-020-00586-7
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    References listed on IDEAS

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    1. Bebbington, Mark & Lai, Chin-Diew & Wellington, Morgan & Zitikis, RiÄ ardas, 2012. "The discrete additive Weibull distribution: A bathtub-shaped hazard for discontinuous failure data," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 37-44.
    2. Jorge Navarro, 2016. "Stochastic comparisons of generalized mixtures and coherent systems," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 150-169, March.
    3. Attahiru Alfa, 2002. "Discrete time queues and matrix-analytic methods," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(2), pages 147-185, December.
    4. Cui, Lirong & Wu, Bei, 2019. "Extended Phase-type models for multistate competing risk systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 1-16.
    5. Miaomiao Yu & Yinghui Tang, 2017. "Optimal replacement policy based on maximum repair time for a random shock and wear model," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 80-94, April.
    6. Serkan Eryilmaz, 2016. "Discrete time cold standby repairable system: Combinatorial analysis," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(24), pages 7399-7405, December.
    7. Eisele, Karl-Theodor, 2006. "Recursions for compound phase distributions," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 149-156, February.
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    Cited by:

    1. Eryilmaz, Serkan & Yalcin, Femin, 2022. "The number of failed components upon system failure when the lifetimes are discretely distributed," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    2. Serkan Eryilmaz & Fatih Tank, 2023. "Optimal age replacement policy for discrete time parallel systems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 475-490, October.

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