OPTIMIZATION OF THE DIE-SINKING MICRO-EDM PROCESS FOR MULTIPLE PERFORMANCE CHARACTERISTICS USING THE TAGUCHI-BASED GREY RELATIONAL ANALYSIS

In modem industries, the expectation is to manufacture high-quality products with a low cost within a short duration. In order to produce any product with a desired quality by machining, the influence of various parameters such as the material-removal rate (MRR), the tool-wear ratio (TWR) and the surface roughness (R-a) should be considered. This paper presents the methodology of the Taguchi method and grey relational analysis to find the optimum parameters for obtaining a higher MRR, a lower TWR and the minimum surface roughness in the die-sinking micro-EDM process. The experiments were carried out as per L-16 orthogonal array with each experiment performed under different conditions of the gap voltage, capacitance, feed rate and threshold. Additionally, an analysis of variance (ANOVA) was also applied to identify the most significant factor. The capacitance and the gap voltage were found to be the most significant controlled factors influencing the performance of the machining process.