The surface roughness of hole machining greatly influences the mechanical properties of parts, such as early fatigue failure and corrosion resistance. The boring and trepanning association (BTA) deep hole drilling with axial vibration assistance is a compound machining process of the tool cutting and the guide block extrusion. At the same time, the surface of the hole wall is also ironed by the axial large amplitude and low-frequency vibration of the guide block. The surface-forming mechanism is very complicated, making it difficult to obtain an effective theoretical analytical model of the surface roughness of the hole wall through kinematic analysis. In order to achieve accurate prediction of the surface quality of the hole wall, the chip-breaking mechanism and the hole wall formation mode of BTA deep hole vibration drilling were analyzed. The influence of drilling spindle speed, feed, amplitude, and vibration frequency on the surface roughness of the hole wall during BTA deep hole vibration drilling was illustrated by a single-factor experiment. A four-factor and three-level test scheme was designed by using the Box–Behnken design (BBD) experimental design method. A surface roughness prediction model for hole wall machining was established based on the response surface methodology. The accuracy of the prediction model was analyzed through ANOVA, and the complex correlation coefficient of the model was 0.9948, indicating that the prediction model can better reflect the mapping relationship between vibration drilling parameters and surface roughness. After optimization analysis and experimental verification, the obtained vibration drilling parameters can achieve smaller surface roughness. The error between the predicted value of the model and the experimental measurement value is 8.65%. The established prediction model is reliable and can accurately predict the surface roughness of the hole wall of BTA deep hole axial vibration drilling, providing a theoretical basis for the surface quality control of the machining hole wall. It can be applied to process optimization in practical production.

To overcome the issues of excessive cutting force, poor chip segmentation, and premature tool wear during the drilling of Ti-6Al-4V titanium alloy. This study established the cutting edge motion trajectory function and instantaneous dynamic cutting thickness equation for ultrasonic vibration-assisted drilling through kinematic analysis. Based on this, an analytical model of drilling force was formulated, integrating tool geometry, cutting radius scale effects, dynamic chip thickness, and drilling depth. In parallel, a finite element model was constructed to achieve visual simulation analysis of chip deformation and cutting force. Finally, the accuracy of the model was verified through experiments, with a comprehensive analysis performed on how cutting parameters affect thrust force. The findings indicate that the average absolute prediction errors of thrust force and torque between the analytical model and finite element simulations were 7.87% and 6.26%, respectively, confirming the model’s capability to accurately capture instantaneous force and torque variations. Compared to traditional drilling methods, the application of ultrasonic vibration assistance resulted in reductions of 40.8% in thrust force and 41.7% in torque. The drilling force exhibited nonlinear growth as the spindle speed and feed rate were elevated, while it declined with greater vibration frequency and amplitude as drilling depth increased. Furthermore, the combined effect of optimized vibration parameters enhanced chip fragmentation, producing short discontinuous chips and effectively preventing entanglement. Overall, this research provides a theoretical and practical foundation for optimizing ultrasonic vibration-assisted drilling and improving precision hole making in titanium alloys.

Titanium alloy (Ti-6Al-4V) exhibits exceptional comprehensive properties, which have resulted in its widespread adoption across diverse industrial sectors. However, its poor machinability poses a significant bottleneck to achieving high-efficiency and high-precision manufacturing. To address the challenges inherent in conventional milling (CM), axial ultrasonic vibration is introduced at the end of the milling spindle to enhance machining quality. Through kinematic analysis, a model of the tool-tip trajectory and tool-workpiece contact rate is established. By incorporating the vibration displacement vector, an instantaneous cutting thickness equation is derived. Subsequently, by integrating tool geometric parameters, instantaneous cutting thickness (IUCT), contact rate, and vibration impact effects, an analytical prediction model for transient cutting forces in ultrasonic vibration-assisted milling (UVAM) is developed. Concurrently, a finite element (FE) model is constructed to simulate the milling process, enabling numerical analysis of chip morphology, stress–strain fields, and the evolution of cutting forces. Finally, a test platform is established to verify the reliability and predictive accuracy of the proposed model. Comparative analysis reveals the advantages of UVAM over CM and elucidates the roles of UVAM parameters in machining performance. The results indicate that the experimentally measured tri-axial milling forces align well with the analytical model predictions and FE simulation outputs, exhibiting consistent trends. Compared with CM, axial UVAM reduces the tri-axial average cutting forces by 14.73%, 15.47%, and 14.49%, respectively, while simultaneously decreasing the surface roughness Ra by approximately 12.1%, indicating an improvement in surface quality. This research provides a reference for understanding the influence of process parameters and a basis for subsequent multi-parameter coupled optimization in the high-performance machining of difficult-to-machine materials.