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Performance analysis and control F-policy for fault-tolerant system with working vacation

Author

Listed:
  • Madhu Jain

    (IIT Roorkee)

  • Chandra Shekhar

    (Birla Institute of Technology and Science, Pilani Campus)

  • Rakesh Kumar Meena

    (Hansraj College University of Delhi)

Abstract

This investigation presents a Markov model for the performance analysis of the fault tolerant machining system with failure-prone server and supported by warm standbys. To utilize the server’s idle time, provision of server’s working vacation has been done which make the system cost effective. The online and warm standby machines may fail and can be repaired by a single skilled repairman. Due to capacity constraint, when the system reaches its full capacity, no more jobs for repairing of failed machines are allowed until the workload of repair jobs reduces to a threshold level ‘F’. Before initiating the repair of the failed machines in case of coming back from the vacation state, the server requires the setup time. To make system fault tolerable, apart from standby provisioning and repairing of failed machines, the concepts of reboot and recovery are included for the formulation of Markov model. The various performance measures including the reliability indices are derived by using the transient probabilities which are computed using Runge–Kutta method. By taking a suitable numerical illustration, various system indices are examined with respect to different parameters. The computational tractability and sensitivity analysis carried out for the established metrics will provides valuable insights for the maintainability and up-gradation of the existing machining systems.

Suggested Citation

  • Madhu Jain & Chandra Shekhar & Rakesh Kumar Meena, 2019. "Performance analysis and control F-policy for fault-tolerant system with working vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 409-431, June.
    • Handle: RePEc:spr:opsear:v:56:y:2019:i:2:d:10.1007_s12597-019-00369-0
    DOI: 10.1007/s12597-019-00369-0
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    References listed on IDEAS

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    1. Kuo-Hsiung Wang & Cheng-Dar Liou & Ya-Lin Wang, 2014. "Profit optimisation of the multiple-vacation machine repair problem using particle swarm optimisation," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(8), pages 1769-1780, August.
    2. Kuo, Ching-Chang & Ke, Jau-Chuan, 2016. "Comparative analysis of standby systems with unreliable server and switching failure," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 74-82.
    3. Liu, Baoliang & Cui, Lirong & Wen, Yanqing & Shen, Jingyuan, 2015. "A cold standby repairable system with working vacations and vacation interruption following Markovian arrival process," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 1-8.
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    Cited by:

    1. Soheil Azizi & Milad Mohammadi, 2023. "Strategy selection for multi-objective redundancy allocation problem in a k-out-of-n system considering the mean time to failure," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 1021-1044, June.
    2. Mridula Jain & Anamika Jain, 2022. "Genetic algorithm in retrial queueing system with server breakdown and caller intolerance with voluntary service," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 582-598, April.
    3. Shekhar, Chandra & Kumar, Amit & Varshney, Shreekant, 2020. "Load sharing redundant repairable systems with switching and reboot delay," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

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