Multi-response optimization in wire electrical discharge machining (WEDM) of D₂steel using utility approach

Abstract

Wire electrical discharge machining (WEDM) is a popular non-conventional machining process used particularly for making extrusion dies, blanking punches, and tools especially requiring tight dimensional tolerances. Because of the process limitation, the rate of cutting and maintenance of close dimensional tolerance is a challenging task. Given the above facts, the present work has been focused on achieving the maximum possible cutting rate (VC) maintaining good dimensional accuracy and corner radius (RC). In the present research work, a multi-response optimization method (i.e. Taguchi based Utility approach) has been used to obtain an optimum set of input parameters such as pulse on time (TON), pulse off time (TOFF), servo voltage (SV), and wire feed rate (WF) resulting into a best overall cutting performance. Analysis of variance (ANOVA) is also used to find out the significant effect of each machining parameter on the cutting performance. The analysis reported in this paper will be helpful for industry personnel to select the best set of process parameters for achieving a good result without the use of any software or statistical analysis.

Study on Optimization of WEDM Process Parameters on Stainless Steel

“…As a result, research on WEDM over nickel-based alloys and stainless steel offers potential [58,59]. The investigations on nontraditional machining, Taguchi method, and grey relational analysis can be carried out to find the best optimum solutions [60][61][62][63].…”

Multi-objects optimization in μ-EDM using AlCrN coated tungsten carbide electrode by Deng's method

“…Some research results have shown the effectiveness of the combination of the Taguchi method with some multi-objective decision techniques. And the simplicity of the combination of Taguchi À Utility in the multi-objective decision in EDM has contributed to overcome the above limitations [26]. The single-objective and multi-objective optimization problems in EDM are solved by Taguchi method and Taguchi À Grey relational analysis (GRA) [27].…”