The m-polar fuzzy ELECTRE-I integrated AHP approach for selection of non-traditional machining processes

Abstract

In the literature, there are a number of decision-making strategies that can be used to choose the best NTM processes. Chen (Citation2014) introduced a novel method to handle fuzzy data that includes multipolar uncertainty, referred to as the m-polar fuzzy set (mFS) approach. The mFS method, along with other multi-criteria decision-making (MCDM) techniques, is a good way to choose between options. An illustration of such a combination is the mFS elimination and choice translating reality-I (ELECTRE-I) . A criteria weight approach is also needed to increase the accuracy of the mFS ELECTRE-I method. The mFS ELECTRE-I method and the analytical hierarchy process (AHP) criteria weight calculation method are combined in the current work. The unique thing about this method is that it can be used to solve both MCDM and MCGDM problems by combining the mFS ELECTRE-I with the AHP criteria weight method. A single-dimensional weight sensitivity analysis is performed to confirm the technique’s stability for different criterion weights for the AHP method on alternative rank performance. The results of the NTM process selection are validated by previous research findings. EDM turned out to be the best way to create machine precise holes on duralumin alloy, and ECM turned out to be the best alternative to generate the surface of revolution in stainless steel. A C++-based soft solution that uses the mFS ELECTRE-I technique to analyze various MCDM and MCGDM problems has been developed. With the soft solution, you can fix problems with selecting the FMS, the robot, and so on.