Task-dependent workpiece placement optimization for minimizing contour errors induced by the low posture-dependent stiffness of robotic milling

Because of the low cost, large workspace and high flexibility, industrial robots (IRs) are promising and competitive alternatives of multi-axis machine tools for milling operations. However, the deformation induced by the low posture-dependent stiffness of robot significantly deteriorates the contour accuracy of milling. Existing studies mainly focused on minimizing the deformation errors caused by the low stiffness, while the contour errors which directly affect the form accuracy did not attract enough attention. In order to improve the contour accuracy of robotic milling, a machining performance index is proposed to optimize the workpiece placement in this paper. Firstly, deformation errors induced by cutting forces are estimated based on the robot stiffness model. Secondly, contour errors are calculated according to deformation errors, and a contour error based machining performance index (CEMPI) is defined by integrating the statistical properties of contour errors. Finally, the optimal workpiece placement is achieved by minimizing CEMPI with particle swarm optimization (PSO). The effectiveness of the proposed task-dependent workpiece placement optimization method is validated by simulation and experiments, which shows that the contour accuracy can be significantly improved with the proposed strategy when compared with traditional methods.

Automated summary

The success of robotic milling in industrial applications directly impacts contour accuracy. This paper proposes a new machining performance index to optimize workpiece placement and achieves optimal placement through particle swarm optimization algorithm. Results show that this method can significantly improve contour accuracy.