IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v95y2010i2p127-133.html

On the use of uncertainty importance measures in reliability and risk analysis

Author

Listed:
  • Aven, T.
  • Nøkland, T.E.

Abstract

This paper discusses the use of uncertainty importance measures in reliability and risk analysis. Such measures are used to rank the importance of components (activities) of complex systems. The measures reflect to what degree the uncertainties on the component level influence the uncertainties on the system level. An example of such a measure is the change in the variance of the reliability of the system when ignoring the uncertainties in the component reliability. The measures are traditionally based on a Bayesian perspective as knowledge-based (subjective) probabilities express the epistemic uncertainties about the reliability and risk parameters introduced. In this paper we carry out a rethinking of the rationale for such measures. What information do they provide compared to the traditional importance measures such as the improvement potential and the Birnbaum measure? To discuss these issues we distinguish between two situations: (A) the key quantities of interest are observable quantities such as the occurrence of a system failure and the number of failures and (B) the key quantities of interest are fictional parameters constructed to reflect the aleatory uncertainties. A new type of combined sets of measures are introduced based on an integration of a traditional measure and a related uncertainty importance measure. A simple reliability example is used to illustrate the analysis and findings.

Suggested Citation

  • Aven, T. & Nøkland, T.E., 2010. "On the use of uncertainty importance measures in reliability and risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 127-133.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:2:p:127-133
    DOI: 10.1016/j.ress.2009.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832009002221
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2009.09.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    2. Zio, Enrico & Podofillini, Luca, 2006. "Accounting for components interactions in the differential importance measure," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1163-1174.
    3. Andrea Saltelli, 2002. "Sensitivity Analysis for Importance Assessment," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 579-590, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.
    2. Roger Flage & Terje Aven & Piero Baraldi & Enrico Zio, 2012. "An imprecision importance measure for uncertainty representations interpreted as lower and upper probabilities, with special emphasis on possibility theory," Journal of Risk and Reliability, , vol. 226(6), pages 656-665, December.
    3. Xu, Ming & Chen, Tao & Yang, Xianhui, 2012. "The effect of parameter uncertainty on achieved safety integrity of safety system," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 15-23.
    4. 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.
    5. Bodda, Saran Srikanth & Gupta, Abhinav & Dinh, Nam, 2020. "Enhancement of risk informed validation framework for external hazard scenario," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. 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.
    7. Hao, Wenrui & Lu, Zhenzhou & Tian, Longfei, 2012. "Importance measure of correlated normal variables and its sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 151-160.
    8. Hao, Wenrui & Lu, Zhenzhou & Wei, Pengfei, 2013. "Uncertainty importance measure for models with correlated normal variables," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 48-58.
    9. Amundrud, Øystein & Aven, Terje, 2015. "On how to understand and acknowledge risk," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 42-47.
    10. Felipe Aguirre & Mohamed Sallak & Walter Schön & Fabien Belmonte, 2013. "Application of evidential networks in quantitative analysis of railway accidents," Journal of Risk and Reliability, , vol. 227(4), pages 368-384, August.
    11. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    12. Zdeněk Kala, 2022. "Quantification of Model Uncertainty Based on Variance and Entropy of Bernoulli Distribution," Mathematics, MDPI, vol. 10(21), pages 1-19, October.
    13. Michele Compare & Michele Bellora & Enrico Zio, 2017. "Aggregation of importance measures for decision making in reliability engineering," Post-Print hal-01652234, HAL.
    14. Martorell, S. & Villamizar, M. & Martón, I. & Villanueva, J.F. & Carlos, S. & Sánchez, A.I., 2014. "Evaluation of risk impact of changes to surveillance requirements addressing model and parameter uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 153-165.
    15. Zhang, Hua & Li, Zongkun & Ge, Wei & Zhang, Yadong & Wang, Te & Sun, Heqiang & Jiao, Yutie, 2024. "An extended Bayesian network model for calculating dam failure probability based on fuzzy sets and dynamic evidential reasoning," Energy, Elsevier, vol. 301(C).
    16. Øystein Amundrud & Terje Aven & Roger Flage, 2017. "How the definition of security risk can be made compatible with safety definitions," Journal of Risk and Reliability, , vol. 231(3), pages 286-294, June.
    17. Xianzhen Huang & Frank PA Coolen, 2018. "Reliability sensitivity analysis of coherent systems based on survival signature," Journal of Risk and Reliability, , vol. 232(6), pages 627-634, December.
    18. Pesenti, Silvana M. & Millossovich, Pietro & Tsanakas, Andreas, 2019. "Reverse sensitivity testing: What does it take to break the model?," European Journal of Operational Research, Elsevier, vol. 274(2), pages 654-670.
    19. Zdeněk Kala, 2021. "New Importance Measures Based on Failure Probability in Global Sensitivity Analysis of Reliability," Mathematics, MDPI, vol. 9(19), pages 1-20, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    2. Zio, E. & Pedroni, N., 2012. "Monte Carlo simulation-based sensitivity analysis of the model of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 90-106.
    3. Cui, Lijie & Lu, Zhenzhou & Wang, Pan & Wang, Weihu, 2014. "The ordering importance measure of random variable and its estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 105(C), pages 132-143.
    4. Yu, W. & Harris, T.J., 2009. "Parameter uncertainty effects on variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 596-603.
    5. Wang, Pan & Lu, Zhenzhou & Ren, Bo & Cheng, Lei, 2013. "The derivative based variance sensitivity analysis for the distribution parameters and its computation," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 305-315.
    6. 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.
    7. Liu, Qiao & Homma, Toshimitsu, 2009. "A new computational method of a moment-independent uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1205-1211.
    8. Allaire, Douglas L. & Willcox, Karen E., 2012. "A variance-based sensitivity index function for factor prioritization," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 107-114.
    9. Zhou, Yuekuan & Zheng, Siqian, 2020. "Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method," Energy, Elsevier, vol. 193(C).
    10. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    11. Helton, Jon C. & Johnson, Jay D. & Sallaberry, Cédric J., 2011. "Quantification of margins and uncertainties: Example analyses from reactor safety and radioactive waste disposal involving the separation of aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1014-1033.
    12. 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.
    13. Saurbayeva, Assemgul & Memon, Shazim Ali & Kim, Jong, 2023. "Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones," Energy, Elsevier, vol. 278(PB).
    14. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    15. Kunz, Nathan & Chesney, Thomas & Trautrims, Alexander & Gold, Stefan, 2023. "Adoption and transferability of joint interventions to fight modern slavery in food supply chains," International Journal of Production Economics, Elsevier, vol. 258(C).
    16. Petropoulos, G. & Wooster, M.J. & Carlson, T.N. & Kennedy, M.C. & Scholze, M., 2009. "A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation," Ecological Modelling, Elsevier, vol. 220(19), pages 2427-2440.
    17. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    18. Guo, Zehua & Dailey, Ryan & Feng, Tangtao & Zhou, Yukun & Sun, Zhongning & Corradini, Michael L & Wang, Jun, 2021. "Uncertainty analysis of ATF Cr-coated-Zircaloy on BWR in-vessel accident progression during a station blackout," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    19. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    20. Gonnet, Gaston H. & Stewart, John & Lafleur, Joseph & Keith, Stephen & McLellan, Mark & Jiang-Gorsline, David & Snider, Tim, 2021. "Analysis of feature influence on Covid-19 Death Rate Per Country Using a Novel Orthogonalization Technique," MetaArXiv 4kw2n, Center for Open Science.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:95:y:2010:i:2:p:127-133. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.