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New insights on multi-state component criticality and importance

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  • Ramirez-Marquez, Jose E.
  • Rocco, Claudio M.
  • Gebre, Bethel A.
  • Coit, David W.
  • Tortorella, Michael

Abstract

In this paper, new importance measures for multi-state systems with multi-state components are introduced and evaluated. These new measures complement and enhance current work done in the area of multi-state reliability. In general, importance measures are used to evaluate and rank the criticality of component or component states with respect to system reliability. The focus of the study is to provide intuitive and clear importance measures that can be used to enhance system reliability from two perspectives: (1) how a specific component affects multi-state system reliability and (2) how a particular component state or set of states affects multi-state system reliability. The first measure unsatisfied demand index, provides insight regarding a component or component state contribution to unsatisfied demand. The second measure multi-state failure frequency index, elaborates on an approach that quantifies the contribution of a particular component or component state to system failure. Finally, the multi-state redundancy importance identifies where to allocate component redundancy as to improve system reliability. The findings of this study indicate that both perspectives can be used to complement each other and as an effective tool to assess component criticality. Examples illustrate and compare the proposed measures with previous multi-state importance measures.

Suggested Citation

  • Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Gebre, Bethel A. & Coit, David W. & Tortorella, Michael, 2006. "New insights on multi-state component criticality and importance," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 894-904.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:8:p:894-904
    DOI: 10.1016/j.ress.2005.08.009
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    References listed on IDEAS

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    1. David A. Butler, 1977. "Technical Note—An Importance Ranking for System Components Based upon Cuts," Operations Research, INFORMS, vol. 25(5), pages 874-879, October.
    2. Avinash Agrawal & Richard E. Barlow, 1984. "A Survey of Network Reliability and Domination Theory," Operations Research, INFORMS, vol. 32(3), pages 478-492, June.
    3. Richard E. Barlow & Alexander S. Wu, 1978. "Coherent Systems with Multi-State Components," Mathematics of Operations Research, INFORMS, vol. 3(4), pages 275-281, November.
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    Cited by:

    1. Dui, Hongyan & Si, Shubin & Yam, Richard C.M., 2017. "A cost-based integrated importance measure of system components for preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 98-104.
    2. Huseby, Arne B. & Natvig, Bent, 2013. "Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 186-198.
    3. Shumin Li & Shubin Si & Liudong Xing & Shudong Sun, 2014. "Integrated importance of multi-state fault tree based on multi-state multi-valued decision diagram," Journal of Risk and Reliability, , vol. 228(2), pages 200-208, April.
    4. Rocco S., Claudio M. & Ramirez-Marquez, Jose Emmanuel, 2012. "Innovative approaches for addressing old challenges in component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 123-130.
    5. Shi, Yue & Zhu, Weihang & Xiang, Yisha & Feng, Qianmei, 2020. "Condition-based maintenance optimization for multi-component systems subject to a system reliability requirement," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    6. Dui, Hongyan & Si, Shubin & Wu, Shaomin & Yam, Richard C.M., 2017. "An importance measure for multistate systems with external factors," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 49-57.
    7. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    8. Kakadia, Deepak & Ramirez-Marquez, Dr. Jose Emmanuel, 2020. "Quantitative approaches for optimization of user experience based on network resilience for wireless service provider networks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    9. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    10. Natvig, Bent & Huseby, Arne B. & Reistadbakk, Mads O., 2011. "Measures of component importance in repairable multistate systems—a numerical study," Reliability Engineering and System Safety, Elsevier, vol. 96(12), pages 1680-1690.
    11. Baroud, Hiba & Barker, Kash, 2018. "A Bayesian kernel approach to modeling resilience-based network component importance," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 10-19.
    12. Tyrväinen, T., 2013. "Risk importance measures in the dynamic flowgraph methodology," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 35-50.
    13. Zio, Enrico & Marella, Marco & Podofillini, Luca, 2007. "Importance measures-based prioritization for improving the performance of multi-state systems: application to the railway industry," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1303-1314.

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