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1-out-of-N multi-state standby systems with state-dependent random replacement times

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  • Gregory Levitin
  • Heping Jia
  • Yi Ding
  • Yonghua Song

Abstract

Research on analysis of replacement time in standby systems has focused on systems with binary-state standby components. However, when the standby components are multi-state, the replacement time depends on the state of the standby component when it is activated for replacement. This article considers the impacts of state-dependent random replacement times on 1-out-of- N systems consisting of multi-state standby components. Numerical algorithms for evaluating the multi-state standby system’s instantaneous availability, expected availability over system mission time and the expected mission completion time are proposed. A Markov state transition model is used to describe the component behaviour in standby mode. The time-to-failure of the operating component and the replacement time of the standby component can obey arbitrary types of distributions. Illustrative examples are provided to demonstrate the proposed numerical algorithms. The effects of the number of standby components, different replacement time distributions and activation sequences are also discussed.

Suggested Citation

  • Gregory Levitin & Heping Jia & Yi Ding & Yonghua Song, 2017. "1-out-of-N multi-state standby systems with state-dependent random replacement times," Journal of Risk and Reliability, , vol. 231(6), pages 750-760, December.
  • Handle: RePEc:sae:risrel:v:231:y:2017:i:6:p:750-760
    DOI: 10.1177/1748006X17734951
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    References listed on IDEAS

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    1. Levitin, Gregory & Jia, Heping & Ding, Yi & Song, Yonghua & Dai, Yuanshun, 2017. "Reliability of multi-state systems with free access to repairable standby elements," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 192-197.
    2. Du, Shijia & Zeng, Zhiguo & Cui, Lirong & Kang, Rui, 2017. "Reliability analysis of Markov history-dependent repairable systems with neglected failures," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 134-142.
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    5. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, January.
    6. 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.
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    Cited by:

    1. Wu, Bei & Cui, Lirong & Fang, Chen, 2019. "Reliability analysis of semi-Markov systems with restriction on transition times," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.

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