This article deals with drilling, the most common and simultaneously most important traditional machining operation, and which is significantly influenced by the properties of the machined material itself. To fully understand this process, both from a theoretical and practical perspective, it is essential to examine the influence of technological and tool-related factors on its various parameters. Based on the evaluation of experimentally obtained data using advanced statistical methods and machine learning decision trees, we present a detailed analysis of the effects of technological factors (f_n, v_c) and tool-related factors (D, ε_r, α₀, ω_r) on variations in torque (M_c) during drilling of two types of engineering steels: carbon steel (C45) and case-hardening steel (16MnCr5). The experimental verification was conducted using CTS20D cemented carbide tools coated with a Triple Cr SHM layer. The analysis revealed a significant influence of the material on torque variation, accounting for a share of 1.430%. The experimental verification confirmed the theoretical assumption that the nominal tool diameter (D) has a key effect (53.552%) on torque variation. The revolution feed (f_n) contributes 36.263%, while the tool’s point angle (ε_r) and helix angle (ω_r) influence torque by 1.189% and 0.310%, respectively. No significant effect of cutting speed (v_c) on torque variation was observed. However, subsequent machine learning analysis revealed the complexity of interdependencies between the input factors and the resulting torque.

This study investigates the influence of tool geometry and cutting parameters on thrust forces and process stability during the drilling of 90MnCrV8, a hard and wear-resistant tool steel. The objective was to identify the dominant and interactive effects of feed per revolution (f_rev), nominal tool diameter (D), cutting speed (v_c), and geometry angles (ε_r, α_o, ω_r) on the thrust force (F_f). Experimental data were evaluated using analysis of variance (ANOVA) to determine statistical significance and effect size (η²), supported by theoretical models by Kienzle, Merchant, Oxley and Zorev to explain observed physical trends. Feed per revolution had the most decisive influence on thrust force (η² = 0.690; p < 0.001), followed by tool diameter (D; η² = 0.188). Geometric parameters showed secondary yet significant effects, mainly on stress distribution and chip evacuation. The interaction between D and f_rev produced a multiplicative force increase, while the combination of f_rev and helix angle (ω_r) reduced friction at higher feeds. Cutting speed had a minor effect (η² = 0.007), suggesting limited thermal softening. The findings confirm that drilling hard steels is primarily governed by the energy of plastic deformation.

The titanium alloy Ti-6Al-4V is widely used in the aerospace, medical, and automotive industries; however, its machining remains challenging due to its low thermal conductivity and high chemical reactivity. This study investigates the influence of the tool clearance angle on tool wear during the turning of Ti-6Al-4V under wet cutting conditions. A Design of Experiments (DoE) approach was employed, varying the clearance angle, cutting speed, and feed rate to determine their effects on tool wear. Tool wear was analysed using 3D topography measurements. Regression analysis was used to evaluate the experimental data with the main objective of quantifying the impact of the individual factors and their interactions, resulting in the development of a predictive statistical model. The model’s accuracy was assessed using the coefficient of determination (R²) and the adjusted coefficient of determination (R²adj). The results demonstrate that the clearance angle has a significant impact on crater wear formation and overall tool life. An optimised moderate clearance angle reduces tool degradation, enhances tool life, and improves the surface integrity of the machined component.