A prediction model for surface topography in robotic flat-end milling considering tool vibration and redundant angles

Industrial robots provide a flexible and cost-effective solution for machining large workpieces, but their application is often limited by inherent structural properties. Serial articulated robots, in particular, exhibit relatively low, configuration-dependent stiffness, making them susceptible to vibrations during milling that impair the final surface topography. To address this, this paper presents a predictive model for surface topography that integrates the robot’s posture-dependent dynamics with tool vibration. The proposed method begins by establishing an ideal kinematic model of the cutting edge trajectory. Next, the posture-dependent frequency response function is predicted using an inverse distance-weighted algorithm, and the dynamic parameters of the dominant vibration mode are identified. The resulting tool vibration displacements are then calculated by solving the system’s dynamic model and are integrated into the cutting edge’s swept surface. Milling experiments were conducted to validate the model, demonstrating strong agreement between the predicted and measured surface topography.