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Composite multilinearity, epistemic uncertainty and risk achievement worth

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  • Borgonovo, E.
  • Smith, C.L.

Abstract

Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.

Suggested Citation

  • Borgonovo, E. & Smith, C.L., 2012. "Composite multilinearity, epistemic uncertainty and risk achievement worth," European Journal of Operational Research, Elsevier, vol. 222(2), pages 301-311.
    • Handle: RePEc:eee:ejores:v:222:y:2012:i:2:p:301-311
    DOI: 10.1016/j.ejor.2012.05.008
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    1. Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.
    2. Emanuele Borgonovo & Alessandra Cillo & Curtis L. Smith, 2018. "On the Relationship between Safety and Decision Significance," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1541-1558, August.
    3. Martorell, S. & Martón, I. & Villamizar, M. & Sánchez, A.I. & Carlos, S., 2014. "Evaluation of risk impact of changes to Completion Times addressing model and parameter uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 190-201.
    4. Borgonovo, Emanuele & Aliee, Hananeh & Glaß, Michael & Teich, Jürgen, 2016. "A new time-independent reliability importance measure," European Journal of Operational Research, Elsevier, vol. 254(2), pages 427-442.

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