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Intuitionistic fuzzy hamming distance model for failure detection in a slewing gear system

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  • Daniel O. Aikhuele

    (University of Port Harcourt)

Abstract

Failure mode and effect analysis (FMEA) is a popular method for system reliability study and for carrying out predictive estimates of failures in complex systems. The traditional FMEA which uses the risk priority numbers (RPNs) for the prioritization of failure modes, has been found to have some deficiency in its computation, and has inherently limited its applications for complex products and system reliability study. In this paper however, a multi-criteria decision-making model which is based on a triangular intuitionistic fuzzy hamming distance and a flexibility function have been proposed for the identification, analysis, and ranking of the root cause(s) of failure in complex products and system (Slewing gear system). In applying the model for slewing gear system reliability evaluation, four failure modes A1, A2, A3, and A4, were identified, and evaluated with respect to the criteria; Severity (C1), Occurrence (C2), Detection (C3), Maintenance (C4), and Environmental conditions (C5). The results from the sensitivity analysis shows that, when the flexibility function in the model is $$\beta =0.2\mathrm{ and }0.8,$$ β = 0.2 and 0.8 , the reliability results were in consensus such that the failure modes $${A}_{1}$$ A 1 and $${A}_{4}$$ A 4 respectively were found to have the highest risk concerns. The main advantage of the proposed model is that it allows the reliability evaluator to identity, analyse and prioritize more than one failure modes with high risk concerns during a reliability study (flexibility), which is not possible in currently existing reliability models. Also, the model addresses not only the hesitation of the experts associated with the reliability and prediction study, but their fuzziness by using the Triangular intuitionistic fuzzy number (TIFN) which is considered an improved platform for expressing imprecise information.

Suggested Citation

  • Daniel O. Aikhuele, 2021. "Intuitionistic fuzzy hamming distance model for failure detection in a slewing gear system," 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. 12(5), pages 884-894, October.
    • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:5:d:10.1007_s13198-021-01132-9
    DOI: 10.1007/s13198-021-01132-9
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    References listed on IDEAS

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    1. Hossein Safari & Zahra Faraji & Setareh Majidian, 2016. "Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 475-486, April.
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