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Influence of process parameters and robot postures on surface quality in robotic machining

Peng Xu, Yinghao Gao, Xiling Yao, Ye Han Ng, Kui Liu, Guijun Bi

Year
2022
Citations
4
Access
Open access

Abstract

Abstract The use of industrial robots for machining large parts has attracted more and more attention. Previous studies have shown that ball-end milling is greatly affected by the process parameters. Besides, robotic machining is also affected by various posture-dependent robot performances. However, these two critical aspects are usually treated separately in many works for studying robotic machining. In this paper, a redundant robotic system consisting of a six-axis industrial robot, a two-axis positioner and a linear track was developed for machining. The combined effects of milling process parameters and robot postures on the machining results were experimentally investigated. Grey relational analysis-based multi-objective optimization was conducted for lower cutting force and better surface quality. A group of process parameters and robot posture was obtained as the optimal combination that generally yields the best milling performance. The results allow to preliminarily determine the main factors that affect the quality of robotic machining.

Keywords

MachiningProcess (computing)Quality (philosophy)RobotArtificial intelligenceSurface (topology)Computer scienceComputer visionManufacturing engineeringMechanical engineering

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