Multi-Objective Optimization of Electrochemical Cut-off Grinding Process of Ti-6Al-4V using PCA based Grey Relational Analysis

Abstract

Electrochemical cut-off grinding (ECCG) process is one of the advance hybrid machining processes which is widely used to machine electrically conductive but difficult-to-cut materials such as titanium alloys, nickel alloys, tungsten carbide, tool materials, super alloys, MMC, etc. In ECCG process, the material is removed from the workpiece by electrochemical reaction along with mechanical abrasive action. In this paper, the multi-objective optimization of process parameters takes place with an aim to maximize material removal rate and minimize surface roughness during ECCG process of Ti-6Al-4V by using hybrid methodology named as principal component analysis (PCA) based grey relational analysis (GRA). Voltage, tool feed rate, electrolyte concentration, electrolyte flow rate and grinding wheel rotation are taken as process parameters to conduct the experiments on electrochemical cut-off grinding setup. The ECCG process is optimized to get the optimal level of parameters for higher MRR and lower Ra value. The optimized result indicates that the PCA based grey relational analysis approach has acquired the setting of optimal process parameters for the ECCG process as voltage = 11 V, tool feed rate = 0.15 mm/min, electrolyte concentration = 300 g/l, electrolyte flow rate = 4 l/min, and grinding wheel rotation = 1600 rpm. The ANOVA of OQPI model is done in order to check the acceptability of the developed model. The actual and predicted OQPI values are compared and the result shows 7.58% error which is within an acceptable range