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Analysis of k-Out-of-N-Systems with Different Units under Simultaneous Failures: A Matrix-Analytic Approach

Author

Listed:
  • Delia Montoro-Cazorla

    (Department of Statistics and Operational Research, University of Jaén, 23071 Jaén, Spain)

  • Rafael Pérez-Ocón

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain)

Abstract

An N-system with different units submitted to shock and wear is studied. The shocks cause damage and, eventually, simultaneous failures of several units. The units can also fail due to internal failures. At random times, the system is inspected, and the down units are simultaneously replaced by identical ones. The arrival of shocks is governed by a Markovian arrival process. The operational times and the interarrival times between inspections follow phase-type distributions. The generator of the multidimensional Markov process modeling the system is constructed. This is performed introducing indicator functions for the different transition rates among the units using the algorithm of Kronecker. This is a general Markov process that can be applied for modeling different reliability systems depending on the structure of the units and how the systems operate. The general model is applied to the study of k-out-of-N systems, calculating the main performance measures. A practical example is presented showing the approximation of the model to a system with units following different Weibull distributions.

Suggested Citation

  • Delia Montoro-Cazorla & Rafael Pérez-Ocón, 2022. "Analysis of k-Out-of-N-Systems with Different Units under Simultaneous Failures: A Matrix-Analytic Approach," Mathematics, MDPI, vol. 10(11), pages 1-13, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1902-:d:830334
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    References listed on IDEAS

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    1. Marcel F. Neuts & Manish C. Bhattacharjee, 1981. "Shock models with phase type survival and shock resistance," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 28(2), pages 213-219, June.
    2. Bei Wu & Brenda Ivette Garcia Maya & Nikolaos Limnios, 2021. "Using Semi-Markov Chains to Solve Semi-Markov Processes," Methodology and Computing in Applied Probability, Springer, vol. 23(4), pages 1419-1431, December.
    3. Ruiz-Castro, Juan Eloy, 2020. "A complex multi-state k-out-of-n: G system with preventive maintenance and loss of units," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    4. Zhi‐Sheng Ye & Min Xie, 2015. "Rejoinder to ‘Stochastic modelling and analysis of degradation for highly reliable products’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(1), pages 35-36, January.
    5. Sweta Dey & T. G. Deepak, 2019. "A matrix analytic approach to study the queuing characteristics of nodes in a wireless network," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 477-496, June.
    6. Zhi‐Sheng Ye & Min Xie, 2015. "Stochastic modelling and analysis of degradation for highly reliable products," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(1), pages 16-32, January.
    7. Gut, Allan & Hüsler, Jürg, 2005. "Realistic variation of shock models," Statistics & Probability Letters, Elsevier, vol. 74(2), pages 187-204, September.
    8. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability models for a nonrepairable system with heterogeneous components having a phase-type time-to-failure distribution," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 37-46.
    9. Tina Song, Wheyming & Lin, Peisyuan, 2018. "System reliability of stochastic networks with multiple reworks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 258-268.
    10. Hongdong Fan & Zhe Xu & Shiwei Chen, 2015. "Optimally maintaining a multi-state system with limited imperfect preventive repairs," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(10), pages 1729-1740, July.
    11. Finkelstein, Maxim, 2007. "Shocks in homogeneous and heterogeneous populations," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 569-574.
    12. Montoro-Cazorla, Delia & Pérez-Ocón, Rafael & del Carmen Segovia, Maria, 2009. "Replacement policy in a system under shocks following a Markovian arrival process," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 497-502.
    13. Søren Asmussen, 2000. "Matrix‐analytic Models and their Analysis," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(2), pages 193-226, June.
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