Experimental Investigation, Predictive Modeling, Parametric Optimization and Cost Analysis in Electrical Discharge Machining of Al-SiC Metal Matrix Composite

This experimental investigation deals with electrical discharge machining of Al-SiC metal matrix composite using a brass electrode to analyze the three major technological response characteristics concerning surface roughness, overcut, and material removal rate. Forty-six sets of experimental trials are conducted by considering five cutting parameters (discharge current, gap voltage, pulse-on-time, pulse-off-time and flushing pressure) based on Box-Behnken’s design of experiments (BBDOEs). Additionally, response surface methodology (RSM), analysis of variance (ANOVA), and statistical technique (here, desirability function approach) followed by computational approach (here, genetic algorithm) are employed respectively for experimental investigation, predictive modeling, and multi-response optimization. Thereafter, the effectiveness of proposed two (RSM, GA) multi-objective optimization techniques are evaluated by the confirmation test. Subsequently, the best optimal solution is employed for economic analysis. Additionally, the effects of discharge current on influencing various response features have also been studied. Finally, an approach has been proposed for sustainability assessment, taking into consideration of the environmental impact and the dielectric consumption created by the electrical discharge machining process. The result shows that discharge current has the significant contribution (72.23% for MRR, 40.56% for Ra, 34.01% in case of OC) in improvement of material removal rate, degradation of surface finish as well as the dimensional deviation of hole diameter, especially overcut. The proposed vegetable oil-based dielectric fluid is biodegradable, eco-friendly, and thus leading sustainable manufacturing.