Evaluation of Optimal Wire Electrical Discharge Machining Parametric Scenarios of AZ91 Magnesium Alloy Based on AHP-Taguchi Analyses-Genetic Algorithms

doi: 10.14456/mijet.2023.15

Abstract

In this article, three robust parametric optimization schemes for the electrical discharge machining of AZ91 magnesium alloy are proposed using a hybrid analytic hierarchy process, Taguchi schemes and a genetic algorithm. The three methods are the AHP-T-GA (analytical hierarchy process-Taguchi method-genetic algorithm approach), AHP-TP-GA and AHP-TAPC-GA, where TP and TABC are Taguchi-Pareto and Taguchi-ABC methods, respectively. The methods were used as the cornerstone approaches to evaluate the parameters and classify them according to their importance. The parameters are namely the pulse on time, pulse off time, pulse current, gap voltage, wire feed and wire tension. The coupled models of AHP-T, AHP-TP and AHP-TABC already exist in the literature. However, the genetic algorithm is coupled with each of these methods to moderate the adverse economic and decision outcomes. Although the coupling of the Taguchi, Taguchi-Pareto and Taguchi-ABC method to AHP reduces errors, the provision of less information in a large-scale decision variable problem may lead to wrong decision making. However, introducing a mechanism capable of producing a large set of solution space, and multiple optimal and global solutions may moderate the tendency to make wrong decisions. The introduction of a genetic algorithm having these preceding features differentiates the three methods proposed in this article from previous research. Results suggest that the proposed robust methods have helped to improve the parametric performance of the wire EDM process and yielded higher values in a maximization scheme pursued in this article. However, the pulse current exhibited the highest value in the analysis. The results adequately represented the parametric scores obtained from ranks of parameters using data from the literature.