Application of CuO Nanofluid MQL and Taguchi Method for Enhanced Surface Quality in Hard Milling of 9CrSi Steel

This study investigates the optimization of cutting parameters in hard milling of 9CrSi alloy steel using Minimum Quantity Lubrication (MQL) enhanced with CuO nanoparticles to achieve superior surface roughness (Ra). The Taguchi method with an L9 orthogonal array was employed to evaluate the effects of cutting speed (v: 60, 80, 100 m/min), feed rate (f: 0.01, 0.015, 0.02 mm/tooth), and depth of cut (d: 0.2, 0.3, 0.4 mm) on surface roughness. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) revealed that the optimal conditions—cutting speed of 100 m/min, feed rate of 0.01 mm/tooth, and depth of cut of 0.2 mm—yielded the lowest surface roughness (Ra = 0.225). The feed rate was identified as the most influential factor, contributing 82.43% to surface roughness variation. These findings highlight the efficacy of CuO nano-enhanced MQL in improving surface quality and promoting sustainable machining practices for high-hardness alloys like 9CrSi steel.