Electrical discharge machining assessment of AA7075/Rice Husk Ash composite using response surface methodology

This study aims to explore electrical discharge machining of green AA7075 composite supplemented with rice husk ash (an agricultural waste) using response surface methodology. Central composite rotatable design for three factors – current, pulse duration and gap voltage – was used for carrying out machining experiments. The effect of these input parameters was evaluated on performance parameters including material removal rate, tool wear rate and surface roughness. Regression models are developed for each response, and model adequacy was checked using the analysis of variance technique. Furthermore, Pareto charts for the standardized effects, normal probability distribution plots, residuals vs fits plots, residual vs order plots, main effect plots and contour plots were also developed for output parameters. Peak current was found to be the major process parameter affecting every response variable. The influence of other linear, squared and interaction effects that are found to be significant for each response are discussed. Multi-response optimization for different process parameters using the composite desirability approach is also highlighted. Confirmatory experiments at optimum process parameters are carried out to analyze variations in predicted values and experimental values. Electrical discharge machined sample was characterized through scanning electron microscopy to study its surface after successive spark discharges.