This paper presents a multi-joint desensitization design(MDD)-based assembly distribution and precision evolution for industrial parallel robots.The optimization of a-UPS/S parallel robot is demonstrated through the o...This paper presents a multi-joint desensitization design(MDD)-based assembly distribution and precision evolution for industrial parallel robots.The optimization of a-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.展开更多
基金funded by the China National Key Research and Development Project(Grant No.2022YFB3303303)Key Project of Zhejiang Provincial Natural Science Foundation(Grant No.Z26E050041)State Key Laboratory of Materials Processing and Die and Mold Technology Key Open Fund,China(Grant No.P2024-001).
文摘This paper presents a multi-joint desensitization design(MDD)-based assembly distribution and precision evolution for industrial parallel robots.The optimization of a-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.
