An optimized milling force prediction method for multi-axis ball-end finish milling

Abstract

By accurately predicting milling force in finish milling, simulation of the milling process can be effectively conducted, followed by the provision of effective recommendations on optimization of machining process parameters. The prediction of ball-end milling force poses a significant challenge due to the influence of the cutter workpiece engagement (CWE) calculation and cutting force coefficient identification. This paper proposes a precise approach for predicting milling force, which involves an improved calculation method of CWE and an optimized identification approach for cutting force coefficients based on a mechanistic model. In the calculation of CWE, an optimization method considering the dynamic change of undeformed slice thickness and CWE boundary calculation is proposed. Furthermore, an improved approach incorporating interference signal removal and multiple nonlinear regression fitting methods is utilized for cutting force coefficient identification. Subsequently, the resulting prediction is validated through comparison with measurements and demonstrates a prediction accuracy exceeding 94%. The conclusion drawn is that the proposed prediction method for multi-axis ball-end finish milling force exhibits high accuracy in its predictions.