A multi-modal and configuration-dependent chatter prediction approach for a milling robot

In robotic milling for aerospace large and complex cabin structural components, chatter can significantly impair the surface quality of workpieces, and in severe cases even result in tool damage. To mitigate chatter-related issues, the selection of appropriate process parameters using Stability Lobe Diagrams (SLDs) is a widely employed and effective strategy. Nevertheless, most prior investigations have primarily focused on regenerative chatter in specific robotic configurations, often disregarding the impact of low-frequency chatter originating from the inherent structural modes of the robot and its configuration-dependent dynamics. A novel approach for predicting the multi-modal stability of milling robots across their entire workspace is presented in this study. By integrating multibody dynamics model and regenerative chatter theory, this approach comprehensively accounts for the vibrations of the robotic milling system, which encompasses both the robotic structure and the tool, as well as the influence of multi-order modal variations. Moreover, a new representation method for the stability cloud map is suggested. Utilizing the multibody system transfer matrix method, a dynamics model is formulated to accommodate alterations in configurations. Additionally, a grid-based dynamic parameter identification method is proposed to predict frequency response functions under different robotic configurations. The chatter stability prediction model is integrated with the dynamics model to establish a multi-modal driven SLD. Finally, the correctness of the proposed robotic dynamics model and the effectiveness of the multi-modal SLDs with variable configurations are validated through modal and milling experiments conducted on an industrial robot.