Optimization of Machining Parameters to Minimize Surface Roughness During End Milling of AISI D2 Tool Steel Using Genetic Algorithm

Abstract

Today’s dies and molds making industries demand for milling of hardened tool steel with less production time and requirement of excellent quality. AISI D2 tool steel has attained high hardness and excellent corrosion resistance at elevated temperature. The experiments were conducted on hardened D2 tool steel using AlCrN coated end mill tool based on response surface methodology (RSM). Central composite design (CCD) method was implemented to design 30 experiments. Analysis of variance (ANOVA) was used to verify adequacy of model. The derived model is utilized to analyze and interaction effect of the input milling parameters with surface roughness. Genetic algorithm was used to optimize of machining parameters to obtain best surface quality on AISI D2 tool steel during milling process. Lowest surface roughness was measured 0.08 after applying genetic algorithm. Optimized value from genetic algorithm was also validated experimentally.