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Resilience analysis: A formulation to model risk factors on complex system resilience

Author

Listed:
  • Adel Mottahedi

    (Shahrood University of Technology)

  • Farhang Sereshki

    (Shahrood University of Technology)

  • Mohammad Ataei

    (Shahrood University of Technology)

  • Ali Nouri Qarahasanlou

    (Imam Khomeini International University)

  • Abbas Barabadi

    (UiT The Arctic University of Norway)

Abstract

Resilience is about the ability of the system to resist, adapt to, and expeditiously recover from a disruptive event. The first and maybe the crucial step of resilience management is known as resilience analysis. However, there are many obstacles in front of the analyzers to analyze the resilience of systems. One of these obstacles is precise resilience data accessibility. Conventional resilience analysis methods frequently only consider historical data (e.g., time to repair and time to failure). However, to analyze the system resilience more precisely, the effect of the risk factors, which are known as observed and unobserved covariates, should be considered in the collected resilience database. These covariates will lead to the observed and unobserved heterogeneities among the collected database. Ignoring the effect of covariate may lead to erroneous conclusion about the resilience level of the system. Since it is hard to find a homogeneous operating condition, in this study, a formulation is proposed to model the effect of these covariates on complex system resilience. Finally, it is applied to a transportation system of a surface mine.

Suggested Citation

  • Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "Resilience analysis: A formulation to model risk factors on complex system resilience," 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. 12(5), pages 871-883, October.
  • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:5:d:10.1007_s13198-021-01131-w
    DOI: 10.1007/s13198-021-01131-w
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    Cited by:

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