Investigation and Optimization of the Effect of Input Parameters on Material Removal Rate, Tool Wear Rate, and Surface Roughness in Electrical Discharge Machining of A356 Nano-Composite Reinforced By Alumina

In this research, the effect of input parameters of Electrical Discharge Machining (EDM) on A356 nano-composite reinforced by 3.5% alumina (Al2O3) was examined and optimized by the Taguchi technique based on the L9 orthogonal array and duplicated levels technique. The input parameters of these experiments consisted of voltage (two-level), current intensity (three-level), pulse on-time (three-level), and pulse off-time (three-level). Moreover, the output parameters were comprised of the material removal rate of the workpiece, the tool wear rate of the machining, and the surface roughness of the workpiece. The analysis of the results and investigation of the signal-to-noise graphs (S/N) and variance analysis (ANOVA) were carried out by using software. Also, with the determination of the loss function of total normalized values of the output parameters based on appropriate weight coefficients, the optimum level of each input parameter was identified. Besides, with performing the variance analysis, the magnitude of contribution percentage of each of the input parameters in the total variance was calculated. Based on the obtained results, it was concluded that the most influential parameter on the material removal rate was the pulse off-time, on tool wear rate was the current intensity, and on the surface roughness was the pulse on-time. Furthermore, the first level of the voltage (80 V), the first level of the current intensity (10 A), the first level of the pulse on-time (35 µs), and the second level of the pulse off-time (70 µs) were determined as the optimum input parameters. The contribution percentage of the input parameters in the total variance for voltage, current intensity, pulse on-time, and pulse off-time was found to be 12.98, 20.96, 5.47, and 60.60, respectively.