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Reliability of maintained systems under a semi-Markov setting

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  • Malefaki, Sonia
  • Limnios, Nikolaos
  • Dersin, Pierre

Abstract

A semi-Markov setting is considered in order to study the main dependability measures of a repairable continuous time system under the hypothesis that the evolution in time of its components is described by a continuous time semi-Markov process. Moreover, the main dependability measures of a periodically maintained system are studied. Finally, all the above systems are compared with the corresponding Markov systems where the general repair time distribution is replaced by the exponential distribution with the same mean which is the most commonly used approximation of the original system in practice.

Suggested Citation

  • Malefaki, Sonia & Limnios, Nikolaos & Dersin, Pierre, 2014. "Reliability of maintained systems under a semi-Markov setting," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 282-290.
    • Handle: RePEc:eee:reensy:v:131:y:2014:i:c:p:282-290
    DOI: 10.1016/j.ress.2014.05.003
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    References listed on IDEAS

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    1. M. Luz Gámiz & K. B. Kulasekera & Nikolaos Limnios & Bo Henry Lindqvist, 2011. "Applied Nonparametric Statistics in Reliability," Springer Series in Reliability Engineering, Springer, number 978-0-85729-118-9, February.
    2. Taghipour, Sharareh & Banjevic, Dragan & Jardine, Andrew K.S., 2010. "Periodic inspection optimization model for a complex repairable system," Reliability Engineering and System Safety, Elsevier, vol. 95(9), pages 944-952.
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    Cited by:

    1. Liang, Qingzhu & Yang, Yinghao & Zhang, Hang & Peng, Changhong & Lu, Jianchao, 2022. "Analysis of simplification in Markov state-based models for reliability assessment of complex safety systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    2. Salim Bouzebda & Chrysanthi Papamichail & Nikolaos Limnios, 2018. "On a multidimensional general bootstrap for empirical estimator of continuous-time semi-Markov kernels with applications," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 49-86, January.
    3. Dhulipala, Somayajulu L.N. & Flint, Madeleine M., 2020. "Series of semi-Markov processes to model infrastructure resilience under multihazards," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

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