Posture optimization for robotic oscillating ball-end milling balancing machining accuracy and tool wear

Traditional robotic milling optimization prioritizes stiffness and machining accuracy and confines robots within limited postures, triggering concentrated cutting loads, non-uniform wear and shortened tool service life. Conventional oscillating ball-end milling homogenizes wear via periodic tool orientation adjustment, yet its direct robotic implementation requires continuous posture tuning that degrades robotic stiffness and machining accuracy. To address such limitations, this work develops a posture optimization method for robotic oscillating ball-end milling to synchronously balance machining accuracy and tool wear uniformity. An analytical cutting force model is derived by embedding coupled geometric constraints of radial depth of cut, axial depth of cut, feed per tooth, and tool inclination into instantaneous undeformed chip thickness (IUCT), which correlates cutting parameters, IUCT and cutting force analytically without explicit cutter-workpiece engagement (CWE) boundary computation. Using the cutting force and robotic stiffness models, the global normal compliance index for robotic deformation sensitivity is defined. Furthermore, a wear non-uniformity index describing the tool wear distribution is defined through the tool wear model. These two indices are combined into a comprehensive index via geometric mean to eliminate empirical weighting and realize consistent evaluation across varied cutting scenarios. The final optimization framework minimizes the proposed index to output optimal posture trajectories balancing accuracy improvement and localized wear inhibition. Comparative robotic milling experiments verify that the presented method achieves preferable trade-off between machining accuracy and tool wear over existing optimization approaches.