A manufacturing failure mode and effect analysis based on fuzzy and probabilistic risk analysis

Gul M., Yucesan M., ÇELİK E.

Applied Soft Computing Journal, vol.96, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 96
  • Publication Date: 2020
  • Doi Number: 10.1016/j.asoc.2020.106689
  • Journal Name: Applied Soft Computing Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: Fuzzy sets, Bayesian network, Best-worst method, Rule-based, FMEA, BAYESIAN NETWORK, FMEA, DECISION, PRIORITIZATION, ENVIRONMENT, ENERGY
  • Istanbul University Affiliated: Yes


© 2020 Elsevier B.V.This study proposes an improved failure mode and effect analysis (FMEA) with fuzzy Bayesian Network (FBN) and fuzzy best-worst method (FBWM) to assess failures in plastic production. To eliminate the drawbacks of the classical risk priority number (RPN) computation of FMEA, this approach is developed. Unlike classical RPN, a new parameter hierarchy is constructed, and three sub-parameters are injected into the approach. These parameters are weighted by the aid of FBWM. Hereafter, a fuzzy rule-based system is constructed by incorporating Bayesian Network (BN). Also, a sensitivity analysis is performed to observe the final FMEA score changes in accordance with the change of subjective probability values. Finally, a comparative analysis with two approaches of classical FMEA and FBWM-based FMEA (without a fuzzy rule-based system incorporating BN) is fulfilled. The results of the study are strengthened with the experts’ opinions regarding the importance of failure modes for the final product and the whole system and supported them by experience feedback in the observed facility.