Multi-response optimization of the electrical discharge machining of insulating zirconia

Abstract

In this study, electrical discharge machining has been used to machine insulating zirconia via the assisting electrode method. The process parameter optimization was investigated by combining the Taguchi method with grey relational analysis. The application of Taguchi–grey relational analysis is proven to effectively improve the performance of electrical discharge machining in drilling insulating zirconia. The results of this analysis indicate that the final optimal process parameters are a peak current of 8 A, a pulse duration of 16 µs, a duty cycle of 0.5, and a flushing pressure of 6 MPa. Additionally, the material removal rate, electrode wear rate, and hole taper ratio increase by 39%, 1.5%, and 1.3%, respectively, which improves the grey relational grade by 6.8%. The electrical resistance test confirms that the conductivity of the conductive layer obtained using the final optimal process parameters is better than that of the conductive layer obtained using the initial optimal process parameters. Energy spectrum analysis reveals that the conductive layer is composed of C, Cu, Zn, Zr, and O. Analysis of variance shows that the most significant component of the multi-responses is the peak current, with a 51.4% contribution.