A Comparison of RSM-DA and PSO-TOPSIS in optimizing the Finishing Turning of 9XC Steel under MQL Conditions

Abstract

This study compares the effectiveness of RSM-DA and PSO-TOPSIS in optimizing the finishing turning of 9XC steel under Minimum Quantity Lubrication. Experiments using the Box-Behnken Design were conducted. Depth of Cut (ap), Feed Per Tooth (fz), and Cutting Speed (Vc) served as the input parameters while the Material Removal Rate (MRR) and Surface Roughness (Ra) as the output responses. Fifteen experiments based on the Box-Behnken orthogonal array design were carried out. The RSM-DA method yielded optimized values of 3.35999 cm3/min for MRR and 0.25367 μm for Ra when Vc, ap, and fz were set at 180 m/min, 0.2999 mm, and 0.06 mm/rev respectively. The Pareto solutions were obtained by PSO and TOPSIS identified the optimum set. The optimized MRR and Ra roughness values were found to be 4.320 cm3/min and 0.474 μm, respectively when Vc = 180 m/min, ap = 0.3 mm, and fz = 0.10 mm/rev. The research results showed the suitability, strengths, and weaknesses of PSO-TOPSIS and RSM-DA for multi-objective optimization of the turning process of 9XC alloy under Minimum Quantity Lubrication conditions.