Optimization and Mathematical Modelling of Surface Roughness Criteria and Material Removal Rate when Milling C45 Steel using RSM and Desirability Approach

Abstract

This work consists of studying the workability of C45 steel in face milling by using coated carbides (GC4040). The objective is to investigate the evolution of surface roughness (Ra, Ry, and Rz) and Material Removal Rate (MRR) according to cutting speed, feed rate, and depth of cut. A full-factorial design (43)was adopted in order to analyse the obtained experimental results via bothAnalysis of Variance (ANOVA) and Response Surface Methodology (RSM)design. The levels of cutting speed were as follows: Vc1=57 m/min; Vc2=111m/min; Vc3=222 m/min and Vc4=440 m/min. The ranges of feed rate werefz1=0.024 mm/tooth; fz2=0.048 mm/tooth; fz3=0.096 mm/tooth and fz4=0.192mm/tooth. As for the depth of cut levels, they included ap1=0.2 mm; ap2=0.4mm; ap3=0.6 mm, and ap4=0.8 mm. To determine mathematical models tomake predictions, a statistical analysis of the results by using RSM was appliedto obtain the main effects and interactions plot of the answer. Furthermore, amulti-objective optimization procedure for minimizing Ra and maximizing themetal removed rate using the desirability approach was also implemented.Therefore, the developed models can be effectively used to predict the surfaceroughness criteria and the material removal rate in machining C45 steel. Theresults indicated that feed rate is a significant factor affecting surfaceroughness (Ra: 52.37%, Ry: 80.97%, and Rz: 54.96%), followed by cuttingspeed (Ra: 37.88%, Ry: 12.90%, and Rz: 24.43%). Meanwhile, cutting speedand feed rate are the most significant parameters on the MRR with a contribution of 29.5% followed by the depth of cut with 11.62%.