Investigation on Electrochemical Machining of EN31 Steel for Optimization of MRR and Surface Roughness Using Artificial Bee Colony Algorithm

Abstract

In this paper, artificial bee colony (ABC) algorithm is employed to find out the optimal combinations of process parameters in ECM of EN 31 steel for maximum material removal rate (MRR) and minimum surface roughness (Ra). Experiments are carried out to establish an empirical relationship between process parameters and responses using response surface methodology (RSM). Four process parameters viz. electrolyte concentration, voltage, feed rate and inter-electrode gap are considered in this study. The developed second order response equations from RSM are used as the objective function in ABC algorithm. The optimum combination of process parameters are obtained from the analysis and the corresponding value of maximum MRR and minimum Ra are also obtained separately. Then a multi-objective optimization is implemented to calculate the best solutions formaximum MRR and minimum surface roughness simultaneously using ABC. Confirmation tests are carried out to check the validity of the study. It is seen that the results of confirmation tests show a good agreement with the predicted results. Also, variations of responses with process parameters are studied using 3D surface plots. Finally, the surface morphology is studied with the help of scanning electron microscopy (SEM).