Optimisation of Performance Parameters of EDM for Heat Treated Al 7050 Alloy using ANN and MORSM

The present study aims to optimize the material removal rate (MRR) and surface roughness (SR) of spark electro-discharge machining (EDM) by considering the concurrent effect of various input parameters. The experiments were carried on heat-treated Al-7050 Alloy.An Artificial Neural Network (ANN) model is used to anticipate the connection between the response parameters such as MRR and SR with process parameters like Peak Current (Ip), Pulse on Time (T-on) and Pulse off Time (T-off). The present ANN model is able to predict the response parameters with high accuracy with experimental outputs, as perceived from overall regression coefficients R. R(2)andmean square errors (MSE) values are in the acceptable threshold.Further, the experimental outputs are optimized using multi-objective response surface method (MORSM). The experimental and optimized outputs at optimized process parameters are compared, the error estimated for MRR and SR are 2.24% and 0.25% respectively. The composite desirability value obtained from, the optimisation is 0.7525. This suggests the modesty of the ANN model and MORSM model of optimization for optimizing the multi-objective optimization problems efficiently.