Optimization of machining parameters during the ECCDG of inconel 718 using PCA based grey relational analysis

Abstract

Electrochemical cut-off diamond grinding (ECCDG) process is a hybrid machining process in which material is removed from the specimen by both electrochemical reaction and mechanical abrasive action. It is extensively used to machine electrically conductive but hard-to-cut materials such as nickel alloy, titanium alloy, tungsten carbide, metal matrix composites, super alloys etc. Inconel 718, a nickel based super alloy is difficult to machine with traditional methods due to its high strength and poor thermal diffusion. It is most productive material in aerospace industries. This paper concern with the optimization of process parameters during ECCDG process of Inconel 718 intend with to maximize material removal rate and minimize surface roughness. The optimization is done via a method known as principal component analysis (PCA) based grey relational analysis (GRA). A face centered central composite rotatable design of response surface methodology (RSM) has been used to plan the experimental runs on Minitab’17. 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 diamond grinding setup. The ECCDG process is optimized to get the optimal level of parameters for higher MRR and lower surface roughness 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 = 0.18 mm/min, electrolyte concentration = 250 g/l, electrolyte flow rate = 6 l/min, and grinding wheel rotation = 1000 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 0.24% error which is within an acceptable range.