Modelling the dynamics of industrial robots for milling operations

• Published in: Robotics and computer-integrated manufacturing Vol. 61; p. 101852
• Main Authors: Huynh, Hoai Nam, Assadi, Hamed, Rivière-Lorphèvre, Edouard, Verlinden, Olivier, Ahmadi, Keivan
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2020; Elsevier BV
• Subjects: CAD; Chatter; Computer aided design; Damping; Identification; Industrial robots; Machine tools; Milling; Milling (machining); Modal analysis; Parameter identification; Robot; Robot arms; Robots; Stability lobes; Stiffness; Vibration; Identification; Modal analysis; Robot; Milling
• ISSN: 0736-5845; 1879-2537
• DOI: 10.1016/j.rcim.2019.101852

•Straightforward approach to identify the inertial and elastic parameters of an industrial robot for milling operations.•Elastic parameters are identified around the joints of motion and also around axes normal to the axes of motion.•Dynamic parameteres are determined using a combination of rigid body identification method and experimental modal analysis.•Elastic parameters are used to predict the robot dynamic behaviour in other robot postures.•The original research can potentially lead to enhancing productivity of milling operations with robots thanks to the selection of optimum cutting parameters. Using industrial robots as machine tools is targeted by many industries for their lower cost and larger workspace. Nevertheless, performance of industrial robots is limited due to their mechanical structure involving rotational joints with a lower stiffness. As a consequence, vibration instabilities, known as chatter, are more likely to appear in industrial robots than in conventional machine tools. Commonly, chatter is avoided by using stability lobe diagrams to determine the stable combinations of axial depth of cut and spindle speed. Although the computation of stability lobes in conventional machine tools is a well-studied subject, developing them in robotic milling is challenging because of the lack of accurate multi-body dynamics models involving joint compliance able of predicting the posture-dependent dynamics of the robot. In this paper, two multi-body dynamics models of articulated industrial robots suitable for machining applications are presented. The link and rotor inertias along with the joint stiffness and damping parameters of the developed models are identified using a combination of multiple-input multiple-output identification approach, computer-aided design model of the robot, and experimental modal analysis. The performance of the developed models in predicting posture-dependent dynamics of a KUKA KR90 R3100 robotic arm is studied experimentally.