Improving the capability of a redundant robotic cell for cast parts finishing

Abstract

Purpose Precision aluminium moulding makes possible the production of large‐size, complex and high‐technology cast parts. However, industrial requirements linked to economic and safety reasons call into question the manual performance of finishing operations. The purpose of this paper is to enhance industrial robot applications by using vision and redundancy optimization to improve their capability. Design/methodology/approach After having presented the concepts associated with machine and kinematics capability, the paper first describes the finishing constraints related to the process and the study of inaccuracy factors. Adjusting the trajectory by vision minimizes some inaccuracy factors but does not take into account the structure loading. Therefore, the authors present the optimization, kinematics and precision criteria as well as the multi‐objective method developed by integrating the loading aspect. This method has been verified by simulation and the results validated on industrial parts. Findings The paper presents an improvement in machine capacities based on redundancy and an optical 3D measurement system. It develops the strategies, sensors and cell architecture to perform finishing operations. Research limitations/implications The finishing of high‐technology structural cast parts requires the completion of the machining and polishing processes adapted to each part. The choice was made to develop a robotic cell dedicated to integrating specific features, in contrast to machine tools. Practical implications This study was carried out within the framework of the Eureka SANDCAST project in cooperation with the Alcan group, specialized in high‐technology moulded aluminum parts. Originality/value The paper presents an approach to robotic cell capability improvement. The robotic cell is dedicated to finishing operations, by machining and polishing large cast aluminum parts; the objectives are to improve machine capability and kinematics capacity with vision and redundancy management.