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Failure mode and effects analysis using a fuzzy-TOPSIS method: a case study of subsea control module

Author

Listed:
  • Athanasios J. Kolios
  • Anietie Umofia
  • Mahmood Shafiee

Abstract

Failure mode and effects analysis (FMEA) is one of the most common reliability engineering techniques used for identifying, evaluating and mitigating the engineering risks. In this paper, the potential failure modes of a subsea control module (SCM) are identified based on industry experts' opinions and experiences. This is followed by a comprehensive component based FMEA study using the risk-priority-number (RPN) where the most critical failure modes in the SCM are revealed. A fuzzy TOPSIS-based multiple criteria decision making methodology is then proposed to analyse and prioritise the most critical failure modes identified by the FMEA study. To this aim, a distinct ten-parameter criticality model is developed and, for the first time, is applied to evaluate the risks associated with SCM failures. The results indicate that the proposed fuzzy TOPSIS model can significantly improve the performance and applicability of the conventional FMEA technique in offshore oil and gas industry.

Suggested Citation

  • Athanasios J. Kolios & Anietie Umofia & Mahmood Shafiee, 2017. "Failure mode and effects analysis using a fuzzy-TOPSIS method: a case study of subsea control module," International Journal of Multicriteria Decision Making, Inderscience Enterprises Ltd, vol. 7(1), pages 29-53.
    • Handle: RePEc:ids:ijmcdm:v:7:y:2017:i:1:p:29-53
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    Citations

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    Cited by:

    1. Tao, Haohan & Jia, Peng & Wang, Xiangyu & Wang, Liquan, 2024. "Reliability analysis of subsea control module based on dynamic Bayesian network and digital twin," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    3. Ahmad, Shafi & Masood, Sarfaraz & Khan, Noor Zaman & Badruddin, Irfan Anjum & Ompal, & Ahmadian, Ali & Khan, Zahid A. & Khan, Amil Hayat, 2023. "Analysing the impact of COVID-19 pandemic on the psychological health of people using fuzzy MCDM methods," Operations Research Perspectives, Elsevier, vol. 10(C).

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