Multi-Objective Optimization of Process Parameters for Electrochemical Machining of 6061Al/ 10%Wt Al2O3/ 5%Wt SiC Composite using Hybrid Fuzzy-Artificial Bee Colony Algorithm

A new hybrid fuzzy-Artificial Bee Colony algorithm (Fuzzy-ABC) for the optimization of electrochemical machining (ECM) process parameters is presented in this paper. The 6061Al/10%wt Al2O3/5%wt SiC composite is taken as a test specimen and its machining characteristics on ECM process are studied. Maximizing the material removal rate (MRR), minimizing the surface roughness (Ra) and minimizing the over-cut (OC) are the main indicators of quality of an ECM process and thus are considered as objectives. The main process parameters governing the ECM process are current, applied voltage, flow rate, tool feed rate, inter-electrode gap and electrolyte concentration. The central composite design of response surface methodology was employed in order to identify the effective machining parameters on the above objectives. Fuzzy Logic (FL) concepts provide a fairly accurate prediction, when sufficient information is not available. The artificial bee colony (ABC) algorithm is a new evolutionary computational technique provides better results to that of other algorithms. Hence, in this paper, fuzzy logic was integrated with artificial bee colony algorithm, thus making a new hybrid Fuzzy-ABC algorithm. The optimized values for ECM were obtained through the hybrid Fuzzy-ABC algorithm. Confirmatory experiments reveal that the experimental values are fairly close with optimized values.