Optimization of multiple-machining criteria in electrochemical machining of aluminum composites using design of experiments

Abstract

Electrochemical Machining (ECM) appears to be a promising non-traditional machining process to produce parts from difficult-to-machine materials with complex profiles. In ECM the machining criteria like metal removal rate (MRR), surface roughness (SR) and radial over cut (ROC) depends on machining parameters such as applied voltage, feed rate, electrolyte concentration, workpiece electrical conductivity etc. In composites, the electrical conductivity depends on the reinforcement content in the matrix. The salient feature of the present work is that the reinforcement content is considered as one of the machining parameter along with voltage, feed rate and electrolyte concentration and varied within the selected range for studying the effect of these parameters on the machining characteristics of electrochemical machining of LM6 Al/B₄C composites. Non-linear regression models have been formulated after conducting the experiments using the concept of central composite design of experiments and the developed models are tested with the help of twenty test cases. The quality of the machined surfaces is studied by using scanning electron microscopic (SEM) images. The responses MRR, SR and ROC are optimized individually and simultaneously based on response surface methodology (RSM). The average absolute percentage error in prediction of all responses for the non-linear model is found to be equal to 9.657. Moreover, the optimal values of MRR, SR and ROC are seen to be equal to 0.778 g/min, 3.923 µm and 0.673 mm respectively.