Workpiece position optimisation in robotic multi-axis machining

Abstract

• A new approach to robot static stiffness modelling is presented • Proposed stiffness model considers dependence of the stiffness parameters of each robot joint on its rotation • A static stiffness criterion along the toolpath is designed and used for evaluating suggested machining operation in different tool-axis orientations and positions of the part within the robot workspace • Genetic algorithm is used to search for the optimal tool-axis orientation and positioning of the part for robotic machining • Multi-axis machining test shows improvement in accuracy and surface quality of machined part when the proposed method is applied The use of robots for machining is becoming increasingly common in industrial robotics applications. The advantages include lower acquisition costs compared to CNC machines and a larger working space with respect to the machine footprint. The disadvantages are low static stiffness and the risk that the robot structure will emit low-frequency vibrations during the machining operation. Both of these phenomena negatively affect the accuracy and quality of the machined part. In this paper, a mathematical model of the static stiffness of an industrial robot is developed from experimentally measured data, and further implemented in the off-line preparation of a robot control programme. By determining the directional stiffness during machining operations and calculating an integral stiffness criterion for a given robot configuration and workpiece position in the workspace, a genetic algorithm is used to find the optimal part position and robot end-effectors' redundant angle of rotation. The model’s validity and accuracy are verified by a five-axis machining experiment. The results of measuring the quality of the surfaces machined in the default and optimised workpiece positions clearly show the effectiveness of the proposed method.