Optimization Of Machining Parameters of CNC Milling Operation for Material Removal Rate and Surface Roughness on En-24 Steel Using Taguchi Method

Abstract

The significance of quality and productivity in the manufacturing industry cannot be overstated, as they directly impact profitability. To remain competitive and keep pace with advancements in technology, manufacturing industries must continuously improve their processes to enhance the quality and productivity of their products. One technology that has contributed to such improvements is CNC milling machines, which have been used in this study. For this study, the high-strength, ductile, and wear-resistant steel alloy EN24 was selected for milling. Taguchi L9 orthogonal array proposal of experiment was used to select cutting parameters, and a total of nine milling operations were conducted. Rate of material removal and surface roughness were calculated for all the nine experiments. Signal-to-noise (S/N) ratios and mean values were used to identify the influencing cutting parameter for material removal rate and surface roughness. ANOVA technique was employed to calculate the optimal cutting parameters for achieving better material removal rate and surface roughness. To analyze the parameters that influence MRR and surface roughness, a comparison was made between the S/N ratios and initial readings using ANOVA technique. Overall, this study demonstrated the importance of selecting appropriate cutting parameters for achieving optimal MRR and surface roughness of CNC milling procedures, which can lead to improvements in quality and productivity in the manufacturing industry.