Improvement of EDM Performance with Parametric Optimization and Various Supportive Techniques

This paper provides an up to date overview on recent research on performance improvement of Electro discharge machining process. Rough machining gives poor surface finish due to microcracks and pores, also finish machining gives better finish but in that case MRR (Material Removal Rate) or machining speed is very less hence various monitoring and control systems were suggested such as continuous gap monitoring system, servo and pulse adaptive control system, knowledge based control system etc. Moreover it is very difficult to achieve higher cutting speed and better surface finish simultaneously and hence it is considered as multi criteria optimization problem. Classical approach suggested by Fisher and Yates is inefficient as it considers one factor only at a time. Taguchi method also can optimize one factor, either MRR or SR (Surface finish) at a time. Hence it is supplemented with various supportive techniques such as fuzzy logic, grey relational analysis, two-phase parameter design, ANN (Artificial Neural Network) and various combination methods. Thus improvement of EDM performance is achieved not only by various monitoring and control system but also by applying parametric optimization with various supportive techniques so as to give better parametric combination for simultaneous optimization of multiple quality characteristics.