In this study, the authors divided the work into two parts. The first part involved the development and validation of a thermal model for Electric Discharge Machining (EDM) using Ansys software. This model took into consideration various factors such as Gaussian heat flux, spark radius, fraction of heat transferred as a equation of pulse on time and pulse current, latent heat in specific heat values and temperature dependent thermal conductivity properties. Three different values of fraction of heat transferred to workpiece (Fc) were used in simulation to determine which one is better at correctly predicting MRR and SR. The second part involved the parametric study of the experimental results using ANOVA, main effect plot and grey relational analysis.
The workpiece in this study was Al-based hybrid composites, which were manufactured using stir casting. Three composite materials, Al-10%SiCmicro-3%SiCnano, Al-10%SiCmicro-4.5%SiCnano, Al-10%SiCmicro-6%SiCnano were considered. The EDM process was accomplished using a L9 orthogonal array, and the performance parameters were measured in terms of MRR, TWR, SR, Dilation in hole diameter, and Hole taper.
The results showed that the Fc value calculated using the Shabdard's function [1] provided the best prediction of MRR and SR, with a MRR ratio range of 1.20-8.00, followed by Fc taken from Dibitonto [2] (MRR ratio range -0.28-12.95) than Fc calculated from Ming et al. [3] (MRR ratio range 0-18.56). The results showed that the dilation in hole diameter and Hole taper increased with an increase in the percentage of SiC nano-particles, while TWR increased with an increase in the pulse current and Hole taper decreased with increase in pulse on time. The best EDM machining results were obtained at 6A pulse current, 20 pulse on time, and 6% SiC nano-particles in the hybrid composite. A validation experiment was also performed, and it was found that the MRR, dilation in hole diameter, and Hole taper improved at 6% SiC nano-particles, 6A pulse current, and 30 pulses on time.