IDEAS home Printed from https://ideas.repec.org/a/ids/ijmcdm/v7y2017i1p29-53.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=85154
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. 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.
    2. 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).

    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:ids:ijmcdm:v:7:y:2017:i:1:p:29-53. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=350 .

    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.