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Load sharing redundant repairable systems with switching and reboot delay

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  • Shekhar, Chandra
  • Kumar, Amit
  • Varshney, Shreekant

Abstract

Industry 4.0 depicts the fourth industrial revolution which prompts an insightful, associated and decentralized manufacturing. The prime viewpoint is an uninterrupted linkage between decision-makers, machines, and products during the manufacturing process empowered by the digital framework. The prime objective is to analyze the optimal design of fault-tolerant machining system with various types of machining hindrance. In this article, we investigate fault-tolerant redundant repairable machining system which is an indispensable part of computer and communication systems, manufacturing and production systems, security systems, etc. Besides the random failure of operating units and standby units, probabilistic common cause failure of the machining system, an automatic switch of the available standby unit in place of a failed operating unit with a significant switching lag is a key concern in the present study with unpredictable switching failure and reboot delay. The workload is shared in general with M operating units but continues in short mode as overload until there are at least M−K units in the system with the degradable failure rate. Numerical simulation, comparative analyses and optimal analyses of queue characteristics are also performed significantly and the conclusion is drawn for system designers and decision-makers to develop state-of-the-art maintenance and repair policies.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:193:y:2020:i:c:s0951832019305174
    DOI: 10.1016/j.ress.2019.106656
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    Cited by:

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    2. Quintanilha, Igor M. & Elias, Vitor R.M. & da Silva, Felipe B. & Fonini, Pedro A.M. & da Silva, Eduardo A.B. & Netto, Sergio L. & Apolinário, José A. & de Campos, Marcello L.R. & Martins, Wallace A., 2021. "A fault detector/classifier for closed-ring power generators using machine learning," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2022. "Optimal preventive switching of components in degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    4. Shekhar, Chandra & Kumar, Neeraj & Gupta, Amit & Kumar, Amit & Varshney, Shreekant, 2020. "Warm-spare provisioning computing network with switching failure, common cause failure, vacation interruption, and synchronized reneging," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    5. Gao, Shan & Wang, Jinting & Zhang, Jie, 2023. "Reliability analysis of a redundant series system with common cause failures and delayed vacation," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    6. Qin, Shuidan & Wang, Bing Xing & Tsai, Tzong-Ru & Wang, Xiaofei, 2023. "The prediction of remaining useful lifetime for the Weibull k-out-of-n load-sharing system," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    7. Gao, Shan, 2023. "Reliability analysis and optimization for a redundant system with dependent failures and variable repair rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 637-659.
    8. Cheng, Dawei & Lu, Zhong & Zhou, Jia & Liang, Xihui, 2023. "An optimizing maintenance policy for airborne redundant systems operating with faults by using Markov process and NSGA-II," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    9. Yang, Dong-Yuh & Wu, Chia-Huang, 2021. "Evaluation of the availability and reliability of a standby repairable system incorporating imperfect switchovers and working breakdowns," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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