Prediction of cutting forces in five-axis micro-ball end milling

Ball end milling;five-axis machining;cutting force modeling;Micro Machining

Xu, Chi ; Kapoor, Shiv G. ; Kapoor ; Shiv G.

关键词: Ball end milling;    five-axis machining;    cutting force modeling;    Micro Machining;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/78324/Chi_Xu1.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Five axis micro-ball end milling has been shown as a viable option for machining complex free form surfaces with high aspect ratios and provide micron-scale tolerances. Unfortunately, due to the high fragility of the cutting tool, premature tool failure has been a major challenge in micro-scale machining. Tool strength of a micro-ball end mill can be easily exceeded by the strain induced by cutting force, thus cutting force is desired to be accurately predicted. Traditionally, researchers have used the mechanistic relationship between experimental force and chipload to develop empirical cutting force models for end mill operation. However, these models suffer the drawbacks including the need for extensive experimental calibration, and the limitation to in-plane tool movements. Therefore a comprehensive cutting force model that is suitable for micro-ball end milling operation is desired.The work in this thesis presents a five-axis ball end milling force model that is specifically tailored to micro-scale machining. A composite cutting force is generated by combining two force contributions from a shearing/ploughing slip-line field model and a quasi-static indentation model. To fully capture the features of micro-scale five-axis machining, a unique chip thickness algorithm based on the velocity kinematics of a ball end mill is proposed. This formulation captures intricate tool trajectories as well as readily allows the integration of runout and elastic recovery effects. A workpiece updating algorithm has also been developed to identify tool-workpiece engagement. As a dual purpose, historical elastic recovery is stored locally on the meshed workpiece surface in vector form so that the directionality of elastic recovery is preserved for future time increments. The model has been calibrated and validated through a comparison with experiment data gain by five axis micro-ball end mill testing. Simulation results show reasonably accurate prediction of end milling cutting forces with minimal experimental data fitting. A potential model application for machining process planning is also presented.