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Improving the foundation and practice of reliability engineering

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  • Terje Aven

Abstract

Reliability engineering is today a well-established field, accounting for many scientific journals and conferences, educational programmes and courses, academic positions and societies. There are also many standards which guide the practice of reliability engineering, and every year a number of scientific papers are published which address reliability engineering issues. Yet the area faces many challenges, in particular when addressing systems characterised by large uncertainties, and accurate prediction models are not easily established. We see alternative analysis perspectives being advocated, with varying degrees of theoretical justification. This article argues that there is potential for improvements to be made in terms of both theoretical frameworks and the practice of reliability engineering to meet these challenges and guide reliability engineers and decision-makers. Examples relate to the understanding and treatment of uncertainties, and the use of ideas and methods from risk management. Clear recommendations are provided on how to obtain such improvements.

Suggested Citation

  • Terje Aven, 2017. "Improving the foundation and practice of reliability engineering," Journal of Risk and Reliability, , vol. 231(3), pages 295-305, June.
    • Handle: RePEc:sae:risrel:v:231:y:2017:i:3:p:295-305
    DOI: 10.1177/1748006X17699478
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    References listed on IDEAS

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    1. Bjerga, Torbjørn & Aven, Terje & Zio, Enrico, 2014. "An illustration of the use of an approach for treating model uncertainties in risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 46-53.
    2. Zio, E., 2009. "Reliability engineering: Old problems and new challenges," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 125-141.
    3. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    4. Emanuele Borgonovo, 2006. "Measuring Uncertainty Importance: Investigation and Comparison of Alternative Approaches," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1349-1361, October.
    5. Saleh, J.H. & Marais, K., 2006. "Highlights from the early (and pre-) history of reliability engineering," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 249-256.
    6. Aven, Terje, 2016. "Supplementing quantitative risk assessments with a stage addressing the risk understanding of the decision maker," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 51-57.
    7. Elisabeth Paté‐Cornell, 2012. "On “Black Swans” and “Perfect Storms”: Risk Analysis and Management When Statistics Are Not Enough," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1823-1833, November.
    8. Roger Flage & Terje Aven & Enrico Zio & Piero Baraldi, 2014. "Concerns, Challenges, and Directions of Development for the Issue of Representing Uncertainty in Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1196-1207, July.
    9. Aven, T., 2011. "Interpretations of alternative uncertainty representations in a reliability and risk analysis context," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 353-360.
    10. Bo Bergman, 2009. "Conceptualistic Pragmatism: A framework for Bayesian analysis?," IISE Transactions, Taylor & Francis Journals, vol. 41(1), pages 86-93.
    11. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
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    1. Flage, Roger & Aven, Terje & Berner, Christine L., 2018. "A comparison between a probability bounds analysis and a subjective probability approach to express epistemic uncertainties in a risk assessment context – A simple illustrative example," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 1-10.

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