Risk Assessment and Ranking through Integration Failure Mode and Effects Analysis and Multiple-Criteria Decision-Making in an Interval Valued Fuzzy Environment: A Case Study in Hydraulic Pump Industry

Abstract

Background and Objective: Nowadays with the increase of global competition, companies apply several scientific methods to identify, assess, and remove potential failures in the production process. In this regard, the present study aimed to identify and analyze the potential failure modes in a hydraulic pump manufacturing company by using a combination of interval valued fuzzy analytic network process (IVF-ANP), interval valued fuzzy failure mode effect and analysts (IVF-FMEA), and interval valued fuzzy TOPSIS (IVF-TOPSIS). Materials and Methods: For the purposes of the study, first, the potential failure modes of the production process were identified using the opinion of experts. Then, the failure modes were prioritized based on the proposed method. The proposed approach applied the IVF-ANP to determine the weight of each risk assessment factor and a combination of IVF-FMEA and IVF-TOPSIS to rank the potential failure modes. Results: In total, 30 failure modes were identified in the present study. The highest-ranking failure mode was inappropriate feed rate with a relative closeness of 0.83. On the other hand, the lowest-ranking failure mode was the large size of the bush with a relative closeness of 0.015. Conclusion: The results showed that the proposed approach is applicable for the assessment and ranking of failure modes. In addition, consideration of some issues like the cost, interdependence of risk assessment factors, and also modeling the method under the condition of interval valued fuzzy uncertainty, affected the final ranking of failure modes.

Keywords

• anp
• fmea
• interval valued fuzzy uncertainty
• risk assessment
• topsis