Optimization of Milling Parameters for 9CrSi Steel under Minimum Quantity Lubrication Using Taguchi and ANOVA Analysis

This study investigates the optimization of milling parameters for 9CrSi steel (50-55HRC) under minimum quantity lubrication (MQL) conditions using the Taguchi method and analysis of variance (ANOVA). Experiments were conducted on a CNC VMC 85S milling machine with a 10mm TiAlN-coated end mill, utilizing canola oil at a flow rate of 120ml/h and 3.5kg/cm² air pressure. The Taguchi L9 orthogonal array was employed to evaluate the effects of cutting speed (80-120m/min), feed rate (0.020-0.030mm/tooth), and depth of cut (0.2-0.6mm) on surface roughness (Ra). Signal-to-noise (S/N) ratios were analyzed to determine optimal parameters, while ANOVA assessed the statistical significance of each factor. Results indicate that feed rate has the most significant impact on Ra (p = 0.043, rank 1), followed by depth of cut (p = 0.050, rank 2), with cutting speed showing minimal influence (p = 0.232). The optimal parameter combination minimizes Ra, enhancing surface quality. These findings provide valuable insights for sustainable machining of high-hardness steels under MQL conditions.