Cutting force prediction in end milling processes: Analytical models and applications

Accurate prediction of cutting forces in milling operations is crucial for optimizing machining performance, ensuring process stability, enhancing surface quality, and extending tool life. This study presents the development and validation of a mechanistic force prediction model tailored for end milling on a 3-axis CNC milling machine (GMS 800). The model incorporates cutter geometry, process parameters, chip thickness variation, and tool engagement to compute instantaneous and average cutting forces in the tangential, radial, and axial directions. Force coefficients were determined experimentally through controlled calibration tests across a range of spindle speeds, feed rates, and milling strategies (up and down milling). The model was validated through comparison with experimental force measurements, showing strong agreement, particularly in the dominant feed (Y) direction. Six different test cases were analyzed to evaluate the model’s accuracy and robustness, with results demonstrating that the predicted forces closely matched the measured data under various conditions. Minor discrepancies observed in the X and Z directions were attributed to unmodeled dynamic effects and tool runout. The model also enabled estimation of cutting torque and power, providing additional insights into machining efficiency. This research contributes a practical and reliable tool for force prediction in CNC milling, which can be used to optimize cutting parameters, minimize tool deflection, and support intelligent process planning. Future work will focus on integrating dynamic effects and real time feedback to enhance adaptability and performance in advanced manufacturing environments.