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A Study of Interactions in the Risk Assessment of Complex Engineering Systems: An Application to Space PSA

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  • E. Borgonovo

    (Department of Decision Sciences and ELEUSI Research Center, Bocconi University, 20136 Milan, Italy)

  • C. L. Smith

    (Idaho National Laboratory, Idaho Falls, Idaho 83415)

Abstract

Risk managers are often confronted with the evaluation of operational policies in which two or more system components are simultaneously affected by a change. In these instances, the decision-making process should be informed by the relevance of interactions. However, because of system and model complexity, a rigorous study for determining whether and how interactions quantitatively impact operational choices has not been developed yet. In light of the central role played by the multilinearity of the decision support models, we investigate the presence of interactions in multilinear functions first. We identify interactions that can be a priori excluded from the analysis. We introduce sensitivity measures that apportion the model output change to individual factors and interaction contributions in an exact fashion. The sensitivity measures are linked to graphical representation methods as tornado diagrams and Pareto charts, and a systematic way of inferring managerial insights is presented. We then specialize the findings to reliability and probabilistic safety assessment (PSA) problems. We set forth a procedure for determining the magnitude of changes that make interactions relevant in the analysis. Quantitative results are discussed by application to a PSA model developed at NASA to support decision making in space mission planning and design. Numerical findings show that suboptimal decisions concerning the components on which to focus managerial attention can be made, if the decision-making process is not informed by the relevance of interactions.

Suggested Citation

  • E. Borgonovo & C. L. Smith, 2011. "A Study of Interactions in the Risk Assessment of Complex Engineering Systems: An Application to Space PSA," Operations Research, INFORMS, vol. 59(6), pages 1461-1476, December.
    • Handle: RePEc:inm:oropre:v:59:y:2011:i:6:p:1461-1476
    DOI: 10.1287/opre.1110.0973
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    References listed on IDEAS

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    Cited by:

    1. Toppila, Antti & Salo, Ahti, 2017. "Selection of risk reduction portfolios under interval-valued probabilities," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 69-78.
    2. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    3. Emanuele Borgonovo & Marco Pangallo & Jan Rivkin & Leonardo Rizzo & Nicolaj Siggelkow, 2022. "Sensitivity analysis of agent-based models: a new protocol," Computational and Mathematical Organization Theory, Springer, vol. 28(1), pages 52-94, March.
    4. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    5. Emanuele Borgonovo & Veronica Cappelli & Fabio Maccheroni & Massimo Marinacci, 2015. "Risk Analysis and Decision Theory: Foundations," Working Papers 556, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Kondakci, Suleyman, 2015. "Analysis of information security reliability: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 275-299.
    7. Terje Aven, 2020. "Risk Science Contributions: Three Illustrating Examples," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1889-1899, October.
    8. Borgonovo, Emanuele & Rabitti, Giovanni, 2023. "Screening: From tornado diagrams to effective dimensions," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1200-1211.
    9. 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.
    10. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    11. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.
    12. 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.
    13. Marisa Faggini & Bruna Bruno & Anna Parziale, 2022. "Toward Reverse Engineering to Economic Analysis: An Overview of Tools and Methodology," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 1414-1432, June.
    14. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
    15. 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.
    16. Tianyang Wang & James S. Dyer & Warren J. Hahn, 2017. "Sensitivity analysis of decision making under dependent uncertainties using copulas," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 117-139, November.
    17. Borgonovo, Emanuele & Tonoli, Fabio, 2014. "Decision-network polynomials and the sensitivity of decision-support models," European Journal of Operational Research, Elsevier, vol. 239(2), pages 490-503.

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