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Uncertainty assessment of reliability estimates for safety-instrumented systems

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  • Hui Jin
  • Mary Ann Lundteigen
  • Marvin Rausand

Abstract

Reliability estimates play a crucial role in decision making related to the design and operation of safety-instrumented systems. A safety-instrumented system is often a complex system whose performance is seldom fully understood. The safety-instrumented system reliability estimation is influenced by several simplifications and assumptions, both about the safety-instrumented system and its operating context, and therefore subject to uncertainty. If the decision makers are not aware of the level of uncertainty, they may misinterpret the results and select a safety-instrumented system design that is either too complex or too simple, or with an inadequate testing strategy, to provide the required risk reduction. This article elucidates the uncertainties related to safety-instrumented system reliability estimation. The article is limited to safety-instrumented systems that are operated in a low-demand mode, for which the probability of failure on demand is the standard reliability measure. The uncertainty of the probability of failure on demand estimate is classified as completeness uncertainty, model uncertainty, and parameter uncertainty and each category is thoroughly discussed. It is argued that the completeness uncertainty is the most important for safety-instrumented system reliability analyses, followed by parameter and model uncertainty. It is further argued that uncertainty assessment should be an integrated part of any safety-instrumented system reliability analysis, and that the analyst should communicate her judgment about the uncertainty to the decision-makers as part of the analysis results.

Suggested Citation

  • Hui Jin & Mary Ann Lundteigen & Marvin Rausand, 2012. "Uncertainty assessment of reliability estimates for safety-instrumented systems," Journal of Risk and Reliability, , vol. 226(6), pages 646-655, December.
  • Handle: RePEc:sae:risrel:v:226:y:2012:i:6:p:646-655
    DOI: 10.1177/1748006X12462780
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    References listed on IDEAS

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    1. Enrique López Droguett & Ali Mosleh, 2008. "Bayesian Methodology for Model Uncertainty Using Model Performance Data," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1457-1476, October.
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    Cited by:

    1. Alizadeh, Siamak & Sriramula, Srinivas, 2018. "Impact of common cause failure on reliability performance of redundant safety related systems subject to process demand," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 129-150.
    2. Rachid Sal & Rachid Nait-Said & Mouloud Bourareche, 2017. "Dealing with uncertainty in effect analysis of test strategies on safety instrumented system performance," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1945-1958, November.
    3. Meng, Huixing & Kloul, Leïla & Rauzy, Antoine, 2018. "Modeling patterns for reliability assessment of safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 111-123.

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