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Incorporating assumption deviation risk in quantitative risk assessments: A semi-quantitative approach

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  • Khorsandi, Jahon
  • Aven, Terje

Abstract

Quantitative risk assessments (QRAs) of complex engineering systems are based on numerous assumptions and expert judgments, as there is limited information available for supporting the analysis. In addition to sensitivity analyses, the concept of assumption deviation risk has been suggested as a means for explicitly considering the risk related to inaccuracies and deviations in the assumptions, which can significantly impact the results of the QRAs. However, challenges remain for its practical implementation, considering the number of assumptions and magnitude of deviations to be considered. This paper presents an approach for integrating an assumption deviation risk analysis as part of QRAs. The approach begins with identifying the safety objectives for which the QRA aims to support, and then identifies critical assumptions with respect to ensuring the objectives are met. Key issues addressed include the deviations required to violate the safety objectives, the uncertainties related to the occurrence of such events, and the strength of knowledge supporting the assessments. Three levels of assumptions are considered, which include assumptions related to the system's structural and operational characteristics, the effectiveness of the established barriers, as well as the consequence analysis process. The approach is illustrated for the case of an offshore installation.

Suggested Citation

  • Khorsandi, Jahon & Aven, Terje, 2017. "Incorporating assumption deviation risk in quantitative risk assessments: A semi-quantitative approach," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 22-32.
    • Handle: RePEc:eee:reensy:v:163:y:2017:i:c:p:22-32
    DOI: 10.1016/j.ress.2017.01.018
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    References listed on IDEAS

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    4. Vinnem, Jan Erik, 2013. "On the development of failure models for hydrocarbon leaks during maintenance work in process plants on offshore petroleum installations," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 112-121.
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    Cited by:

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    5. Tasneem Bani-Mustafa & Nicola Pedroni & Enrico Zio & Dominique Vasseur & Francois Beaudouin, 2020. "A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models," Journal of Risk and Reliability, , vol. 234(6), pages 748-763, December.

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