Modeling and Optimization of Medium-Speed WEDM Process Parameters for Machining SKD11

This study analyzed the workpiece surface quality (Ra) and the material removal rate (MRR) on process parameters during machining SKD11 by medium-speed wire electrical discharge machining (MS-WEDM). An experimental plan for composite design (CCD) has been conducted according to methods response surface methodology (RSM) and subsequently to seek the optimal parameters. The experimental data were utilized to model MRR and Ra under optimal parameter condition by a backpropagation neural network combined with genetic algorithm (BPNN-GA) method. Eventually, the comparisons between the results from BPNN-GA and those from the RSM demonstrate that BPNN-GA method is a more effective way for optimizing MS-WEDM process parameters.