Processing accuracy improvement of robotic ball-end milling by simultaneously optimizing tool orientation and robotic redundancy

Robotic ball-end milling presents advantages such as a broad workspace, cost-effectiveness, and integration with vision/force sensing, making it a promising method in machinery manufacturing. However, its low stiffness leads to deformation error that seriously affects part profile accuracy. Reducing the deformation error is an effective method to improve the machining accuracy of robotic milling. However, existing research primarily focuses on translational deformation of the robot end effector calculated using average cutting force, overlooking the effect of changes in cutting force and deformation at the tool tip. To address these limitations, an optimization model is proposed to simultaneously optimize tool orientation and redundant angle to minimize force-induced tool tip deformation errors, accounting for cutting force variations at different tool postures. First, an error index for tool tip deformation is introduced, and it considers the comprehensive deformation of the tool tip point instead of the translational deformation of the robot end-effector to offer a more accurate analysis of the machining error. Second, a rapid calculation method for cutter-workpiece engagement is developed, facilitating efficient calculation of cutting forces and enhancing the accuracy of deformation error calculation under various tool orientations. Finally, employing a particle swarm optimization algorithm with multiple constraints, including robot kinematics and tool interference, both tool orientation and robotic redundant angles are optimized to minimize tool error index at each cutter location. Through a comparison test using a simplified aeroengine casing, the proposed method demonstrates effective enhancement of the accuracy of robot milling processing compared with unoptimized and existing studies.