Application of the TOPSIS Method for Solving Multi-Response Optimization Problem

Abstract

This study aims to apply the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to solve multi-response optimization (MRO) problems, which are inherently complex due to the potential conflicts among response variables. The research employs TOPSIS to aggregate multiple responses into a single response, which is then used to determine the optimal parameters using Minitab Version 19. The aggregation of the two responses using TOPSIS yielded a maximum closeness coefficient (CC) of 0.8007 and a minimum of 0.2150, indicating the efficiency of each parameter setting. These coefficients were subsequently input into Minitab Version 19 to identify the optimal parameters, which were found to be a cutting speed of 140 m/min, a feed rate of 0.071 mm/rev, and a depth of cut of 0.6 mm. The TOPSIS method proved to be an effective tool for solving MRO problems. When compared with other methods, such as MOORA and WASPAS, TOPSIS demonstrated comparable performance in determining optimal parameter settings. The TOPSIS approach can be applied in various fields requiring multi-criteria decision-making, such as optimizing parameters in manufacturing processes, experimental design, or data analysis involving multiple response variables to achieve the best possible outcomes. Additionally, applying this method can effectively reduce time and costs in the search for optimal values across various processes.