MULTI-RESPONSE OPTIMIZATION OF EDD PROCESS OF DIE STEEL FOR IMPROVING PRODUCTION RATE AND HOLE QUALITY

Abstract

Improving the technical outputs of the electrical discharge drilling (EDD) process is an effective solution to decrease manufacturing costs. This paper presented a multi-response optimization to simultaneously improve the material removal rate (MRR) and decrease the dilation of hole (DH).
The processing conditions considered include the pulse on time (TON), the current (AMP), the gap voltage adjustor (GAP), and the pulse off time (TOFF). An EDD drilling machine was adopted in conjunction with the Box-Behnken matrix to conduct experimental trails for machining of SKD61 steel. The highly nonlinear relationships between the process parameters and criteria outputs were developed using the Kriging models. Finally, an archive-based micro-genetic algorithm (AMGA) was used to determine the optimal values of the processing factors. The results showed that DH could be approximately decreased 12.26%, while (MRR) is around improved 32.17%. The
combination of the Kriging model and AMGA could be considered as an intelligent approach for modeling EDD processes and generating reliable optimal results.