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Common cause failures in safety-instrumented systems: Using field experience from the petroleum industry

Author

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  • Hauge, S.
  • Hokstad, P.
  • HÃ¥brekke, S.
  • Lundteigen, M.A.

Abstract

Safety instrumented systems often employ redundancy to enhance reliability, but the intended effect may be reduced when common cause failures are taken into account. It is often assumed that a certain fraction of component failures will occur close in time, due to a shared cause. Unfortunately, few attempts have been made to systematically investigate field experience on common cause failures, with the exception of the nuclear industry which has been in the forefront of research in this area. This paper presents selected results from a research project carried out in the Norwegian oil and gas industry to collect and analyze reported failures. This includes the presentation and derivation of generic (i.e. industry average) values of beta-factors for typical components in the oil and gas industry, and the demonstration of how failure data may be used to construct checklists for updating the value of beta in operation. The results are based on a review of some 12.000 maintenance notifications from six different onshore and offshore petroleum facilities. It is found that the new beta-values are higher than what is seen in many data sources, and some possible explanations are discussed.

Suggested Citation

  • Hauge, S. & Hokstad, P. & HÃ¥brekke, S. & Lundteigen, M.A., 2016. "Common cause failures in safety-instrumented systems: Using field experience from the petroleum industry," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 34-45.
    • Handle: RePEc:eee:reensy:v:151:y:2016:i:c:p:34-45
    DOI: 10.1016/j.ress.2015.09.018
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    Cited by:

    1. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system considering common cause failure: Based on a beta-factor and continuous-time bayesian network model," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    2. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "The ETH Zurich curated nuclear events database: Layout, event classification, and analysis of contributing factors," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. H. Metatla & M. Rouainia, 2022. "Functional and dysfunctional analysis of a safety instrumented system (SIS) through the common cause failures (CCFs) assessment. Case of high integrity protection pressure system (HIPPS)," 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. 13(4), pages 1932-1954, August.
    4. Siwar Kriaa & Marc Bouissou & Youssef Laarouchi, 2019. "A new safety and security risk analysis framework for industrial control systems," Journal of Risk and Reliability, , vol. 233(2), pages 151-174, April.
    5. Wu, Shengnan & Zhang, Laibin & Zheng, Wenpei & Liu, Yiliu & Lundteigen, Mary Ann, 2019. "Reliability modeling of subsea SISs partial testing subject to delayed restoration," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Colombo, Danilo & Lima, Gilson Brito Alves & Pereira, Danillo Roberto & Papa, João P., 2020. "Regression-based finite element machines for reliability modeling of downhole safety valves," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    7. 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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