The m-polar fuzzy TOPSIS hybrid method for manufacturing decisions

In this study, problems in the manufacturing environment were solved using the multicriteria group decision-making (MCGDM) approach with the recently developed m-polar fuzzy (mF) paradigm. This is a useful strategy when applied to various industrial selection issues. Numerous multi-criteria decision-making (MCDM) approaches are currently in use, each with distinctive features and results. The mF set combined with the technique for order performance by similarity to the ideal solution (TOPSIS) method is a methodology for solving MCGDM issues. Compared to the current and well-established MCDM techniques, the mF TOPSIS method is accurate in its performance, easy to calculate, and can address MCDM and MCGDM problems. The rank performances of the two MCDM approaches were compared using the Spearman’s rank correlation coefficient. This study compares the rank performance acquired by the mF TOPSIS technique to the rank performance obtained by earlier plans to assess the rank performance of industrial selection problems, such as cutting fluid selection, flexible manufacturing system (FMS) selection, and robot selection. It was found that the m-polar fuzzy TOPSIS method, which was developed to solve MCGDM problems, can be used to calculate MCDM problems from the manufacturing environment.