Assembly precision distribution for industrial parallel robots based on multi-joint desensitization design

Abstract

This paper presents a multi-joint desensitization design (MDD)-based assembly distribution and precision evolution for industrial parallel robots. The optimization of a 3-UPS/S parallel robot is demonstrated through the optimization of its performance index and precision performance, achieved through the construction of a global error sensitivity. The precision degradation law for independent sources of uncertainty is introduced, and the accelerated degradation after multiple repairs is considered to establish a source-split maintenance yield model to formulate an optimized operation and maintenance strategy. Experiment demonstrates that the MDD method significantly enhances the precision and reliability of the equipment. Compared with that in the pre-optimization stage, the lifetime of the equipment is extended by 38.88%, while the cost remains unchanged. In addition, the effectiveness of MDD in additive manufacturing is demonstrated through an industrial bending pipe case.

Graphical abstract

Keywords

assembly distribution / precision evolution / independent sources of uncertainty / multi-joint desensitization design

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