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Quantitative representation of the functional resonance analysis method for risk assessment

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  • Kim, Yoo Chan
  • Yoon, Wan Chul

Abstract

Resilience engineering understands that risks are emergent from the complexity of socio-technical systems. In this perspective, the risk assessment needs to analyze possibilities of potential risks emerging from system variabilities and interactions under hypothetical scenarios. While the Functional Resonance Analysis Method (FRAM) is a well-established method for analyzing system behavior in terms of variability, assessing relative risk levels requires more specific representation and handling of the quantitative aspects of variabilities to allow for comparative analysis and decision-making. This study proposed and examined a quantitative scheme to use FRAM for risk assessment by defining rules for variability propagation and aggregation. The proposed method represents the system more realistically with quantitative values, taking into account interactions and the adaptive operation of functions. The approach was tested via a walk-through application to an emergency response system for infectious disease. Three progressive scenarios are used in relation to managing crisis response for the 2019 coronavirus pandemic (COVID-19), and the results demonstrate the usefulness of the proposed method for assessing the relative importance of potential risks and critical conditions. Although the test example focused on a disease containment case, the proposed method can generally support strategic decision making during the governance of large-scale crisis response.

Suggested Citation

  • Kim, Yoo Chan & Yoon, Wan Chul, 2021. "Quantitative representation of the functional resonance analysis method for risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:reensy:v:214:y:2021:i:c:s0951832021002763
    DOI: 10.1016/j.ress.2021.107745
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    References listed on IDEAS

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    1. Patriarca, Riccardo & Bergström, Johan & Di Gravio, Giulio, 2017. "Defining the functional resonance analysis space: Combining Abstraction Hierarchy and FRAM," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 34-46.
    2. George E. Apostolakis, 2004. "How Useful Is Quantitative Risk Assessment?," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 515-520, June.
    3. Herrera, I.A. & Woltjer, R., 2010. "Comparing a multi-linear (STEP) and systemic (FRAM) method for accident analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1269-1275.
    4. Aven, Terje, 2016. "Risk assessment and risk management: Review of recent advances on their foundation," European Journal of Operational Research, Elsevier, vol. 253(1), pages 1-13.
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    Cited by:

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    4. Huang, Wencheng & Yin, Dezhi & Xu, Yifei & Zhang, Rui & Xu, Minhao, 2022. "Using N-K Model to quantitatively calculate the variability in Functional Resonance Analysis Method," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Zhou, Zhengshu & Matsubara, Yutaka & Takada, Hiroaki, 2023. "Resilience analysis and design for mobility-as-a-service based on enterprise architecture modeling," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    6. Mahdieh Delikhoon & Esmaeil Zarei & Osiris Valdez Banda & Mohammad Faridan & Ehsanollah Habibi, 2022. "Systems Thinking Accident Analysis Models: A Systematic Review for Sustainable Safety Management," Sustainability, MDPI, vol. 14(10), pages 1-28, May.
    7. Li, Jue & Wang, Hongwei, 2023. "Modeling and analyzing multiteam coordination task safety risks in socio-technical systems based on FRAM and multiplex network: Application in the construction industry," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    8. Yu, Jianxing & Zeng, Qingze & Yu, Yang & Zhang, Baolei & Ma, Wentao & Wu, Shibo & Ding, Hongyu & Li, Zhenmian, 2025. "Resilience assessment of FPSO leakage emergency response based on quantitative FRAM," Reliability Engineering and System Safety, Elsevier, vol. 253(C).

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