Multiple Optimization of Cutting Parameters on Turning of 9XC Heat Treatment Steel Under MQL Cutting Conditions

This study towards the multi-response optimization of cutting parameters when turning 9XC heat treatment steel using Minimum Quantity Lubrication (MQL). The input parameters used are cutting speed Vc, feed rate Vf and depth of cut ap; and the responses examined are surface roughness and material removal rate (MRR). The objective of this research is to find the best combination of cutting settings to accomplish two targets simultaneously which are minimizing surface roughness and intensifying MRR. To find the ideal point, based on the Box-Behnken experimental matrix, the response surface methodology (RSM) consisting of 15 experiments is used. Experiments were carried out on the xxx lathe to collect data on roughness and MRR. Experimental models Ra and MRR are determined by using ANOVA. In this research, the multi-response optimization problem is solved by applying the desirability function (DF). The outcomes of the experimental study show that the optimized cutting parameters are Vc = 180 m/min; fr = 0.0759829 mm/rev; ap = 0.3 mm corresponding to Ra = 0.306147µm; MRR = 65.7155cm3/min; In addition, the impact of experimental variants on surface roughness in turning 9XC hardened steel using MQL is also analyzed and discussed.