Zhonghan Cui

This investigation uses polycrystalline cubic boron nitride (PCBN) tools for precision turning of D6AC (45CrNiMoVA) hardened steel, thereby enabling the manufacturing of components that meet the requirements of intelligent manufacturing lines. A Taguchi’s L16 (4³) orthogonal design was employed to systematically investigate the effects of cutting speed, depth of cut, and feed rate on cutting force, cutting temperature, surface roughness, and tool wear. Analysis of variance (ANOVA) was then conducted to quantify the contribution of each cutting parameter, and high-accuracy predictive models (R² > 0.86) were established for the key response variables, namely cutting force components (F_x, F_y, F_z), cutting temperature (T), and flank wear width (VB_max). The results show that excellent surface quality can be achieved within the investigated range, namely at cutting speeds of 100–250 m·min⁻¹, depths of cut of 0.05–0.2 mm, and feed rates of 0.05–0.125 mm·rev⁻¹, with surface roughness (Ra) below 0.8 μm and mostly around 0.4 µm. At a feed rate of 0.05 mm·rev⁻¹, the measured Ra was greater than the theoretical value (Ra*), whereas at a feed rate of 0.075 mm·rev⁻¹, Ra was lower than Ra*, with the difference increasing as feed rate increased. The ANOVA results showed that cutting forces were dominated by depth of cut, cutting temperatures by feed rate, and tool wear by depth of cut. The optimal process strategy was derived as follows: first, prioritize a lower feed rate; second, select an appropriate depth of cut based on tool failure or deformation control objectives; and third, choose a suitable cutting speed according to tool-life requirements or machining efficiency. This study provides process guidance and predictive tools for PCBN finishing of D6AC steel, thus promoting green, precise, and efficient machining of high-strength, high-hardness, and low-thermal-conductivity materials.