A Spherical Fuzzy TOPSIS Entropy Weighted for Failure Mode and Effects Analysis

The aim of this paper is to implement a Spherical Fuzzy Sets (SFS) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach in the Failure Mode and Effects Analysis (FMEA) process. The SFS can provide a larger domain for decision-makers to assign independent membership degrees, non-membership degrees, and hesitancy degrees. The SFS are combined with TOPSIS to obtain the rank all of the failure modes with respect to their distances to ideal solutions and relative closeness ratios. In addition, the entropy objective weight for SFS is integrated into SFS TOPSIS for determining the risk factors weights. The proposed approach is utilized to prioritize and rank the potential failure of an injection molding machine. The implementation of SFS-TOPSIS and entropy objective weight approach can overcome the vagueness and uncertainty of data during FMEA evaluation process and improve FMEA to be more flexible and reasonable.