Investigation of machinability criteria during micro-abrasive finishing of SUS-304L steel using fuzzy combined with WASPAS approach

Abstract

This article deals with the optimization of process parameters involving in the magnetic abrasive finishing (MAF) process to achieve the optimum responses. In order to choose to the best decisive course of action, we have used the weighted aggregated sum product assessment (WASPAS) method. This method is a multi-criteria decision-making process; here, it optimizes the six process parameters of the MAF process. The WASPAS is used to find the optimum parametric setting of the process parameter for the combined effect of the output responses, i.e., percentage improvement in surface finish (PISF) and material removal rate (MRR) in terms of total relative importance index Q i. The process parameters are namely rotational speed, working gap, particle size of abrasive, quantity of abrasive, finishing time and magnetic flux density, and responses are PISF and MRR. The analysis of variance is implemented not only to find out the percentage contribution of each of the process parameters but also to know the effect of interaction between any two process parameters. Finally, a regression equation is developed as per the backward propagation method and the predicted values are estimated from the equation. Those values are further compared with the experimental values.

A consensus-based Fermatean fuzzy WASPAS methodology for selection of healthcare waste treatment technology selection

“…Dorfeshan & Mousavi (2020) assessed critical paths of aircraft maintenance planning using a coordinated MABAC and WASPAS under the interval type-two setting. Sharma & Pradhan (2020) examined the machinability criteria for SUS-304L steel using the WASPAS model for fuzzy sets to address the doctor recruitment issue. resolved a sustainable project portfolio problem using the WASPAS model with interval-valued Pythagorean fuzzy sets.…”