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A novel geometric error modeling optimization approach based on error sensitivity analysis for multi-axis precise motion system

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Abstract

In this paper, a novel error modeling approach for multi-DOF precise motion platform (MPMP) based on the error sensitivity analysis (ESA) is introduced. Sensitivity analysis (SA) is widely adopted for finding the essential parameters in system in mathematical way. This paper leads an error sensitivity analysis based on Monte Carlo thought into geometric error model. Through comparing the variance between the set of evaluated error and corresponding orientation deviations, a sensitive order with several sensitive levels can be developed. Conventional error modeling method only concentrates the systematic accuracy, while calculation efficiency is also important. Thus, this error modeling optimization approach based on sensitivity analysis is beneficial for the high-accuracy and high-quantity manufacture environments, which is more precise and effective. It also can save the computational volume for the calculation in error model. A case study of the new error modeling optimization procedure for six-axis stage in the alignment in optoelectronic packaging system (OPS) is carried out. The time-consumed results indicate that the optimized error model can not only keep high-accuracy requirement, but also improve the computational efficiency, which is informative and effective for MPMP motion control. For large number working situation, the optimized error model is available as well.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (Grant No. 51705149) and the Natural Science Foundation of Hunan province (Grant No. 2018JJ3168).

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Authors and Affiliations

  1. School of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China

    Hao Tang, Changping Li, Zilin Zhang & Tae Jo Ko

  2. School of Mechanical Engineering, Yeungnam University, Gyeongsan, 712-749, Korea

    Tae Jo Ko

Authors
  1. Hao Tang
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  2. Changping Li
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  3. Zilin Zhang
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  4. Tae Jo Ko
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Corresponding authors

Correspondence to Changping Li or Tae Jo Ko.

Additional information

Recommended by Associate Editor Yongho Jeon

Hao Tang was born in Changsha, Hunan, China, in 1988. He graduated from Dong Hua University, Shanghai, China, and started the M.S. degree in mechanical engineering in Central South University, Changsha, China, in 2009, and transferred into Ph.D. student in 2011. His research interests include error analysis, error modeling and precision transferring in complicated multi-axis motion system, and applications of optoelectronic packaging system and laser welding system. He, as a visiting student, went to University of Michigan, Ann Arbor, US, from Sept. 2013 to Mar. 2015, and worked in S.M. Wu manufacture center.

Chang Ping Li is an Assistant Professor of Mechanical Engineering at Hunan University of Science & Technology, China. He received his bachelor’s from Kumoh National Institute of technology, South Korea. He received master’s degrees and Ph.D. in mechanical engineering from Yeungnam University, South Korea. His research interests include the development of machine tools; hybrid machining; nontraditional machining; the deburring process of CFRP composites.

Zi Lin Zhang is an undergraduate student of Mechanical Engineering at Hunan University of Science & Technology, China. His research interests include error analysis, error modeling and precision transferring in complicated multi-axis motion system, and applications of optoelectronic packaging system and laser welding system.

Tae Jo Ko is a Professor of Mechanical Engineering at Yeungnam University, South Korea. He received his bachelor’s and master’s degrees from Pusan National University, South Korea. He received a Ph.D. in mechanical engineering from POSTECH, South Korea. His research interests include the development of machine tools; micro-cutting processes; nontraditional machining; surface texturing using piezoelectric actuators; surface texturing using grinding, bio-machining, and textured surfaces on cutting tools; and the deburring process of CFRP composites.

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Tang, H., Li, C., Zhang, Z. et al. A novel geometric error modeling optimization approach based on error sensitivity analysis for multi-axis precise motion system. J Mech Sci Technol 33, 3435–3444 (2019). https://doi.org/10.1007/s12206-019-0638-x

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  • DOI: https://doi.org/10.1007/s12206-019-0638-x

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