Design of Grinder Fixture Based on Non-Parametric Regression Response Surface

Taking the mold polishing machine as the research object, in order to improve the dynamic characteristics of the polishing machine, the vibration characteristics are determined through modal and harmonic response analysis. Through topology optimization methods, structural enhancements were made to the fixed seat, improving its contour shape. A multi-objective optimization model was established, sensitivity analysis was performed, and the final optimization design variables were determined. Through automatic space filling sampling complete the experiment points. Non-Parametric Regression model was employed for design optimization, through multi-objective genetic algorithm obtain pareto results. Consequently, the first natural frequency of the fixed seat increased by 12.16%, the maximum deformation decreased by 30.58%, and the mass was reduced by 23.58%, significantly extending its service life. Meanwhile, The amplitude of mold polishing in all directions has also been reduced, resulting in improved dynamic performance of the entire machine.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1109/icceic64099.2024.10775442
Primary Topic
Manufacturing Process and Optimization
Type
article
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article

Design of Grinder Fixture Based on Non-Parametric Regression Response Surface

Zhengcai Wang, Junfeng Yang, Gaofeng Xu, Li Bao
Manufacturing Process and Optimization
article

Design of Grinder Fixture Based on Non-Parametric Regression Response Surface

Zhengcai Wang, Junfeng Yang, Gaofeng Xu, Li Bao
article en

Abstract

Taking the mold polishing machine as the research object, in order to improve the dynamic characteristics of the polishing machine, the vibration characteristics are determined through modal and harmonic response analysis. Through topology optimization methods, structural enhancements were made to the fixed seat, improving its contour shape. A multi-objective optimization model was established, sensitivity analysis was performed, and the final optimization design variables were determined. Through automatic space filling sampling complete the experiment points. Non-Parametric Regression model was employed for design optimization, through multi-objective genetic algorithm obtain pareto results. Consequently, the first natural frequency of the fixed seat increased by 12.16%, the maximum deformation decreased by 30.58%, and the mass was reduced by 23.58%, significantly extending its service life. Meanwhile, The amplitude of mold polishing in all directions has also been reduced, resulting in improved dynamic performance of the entire machine.

Ningbo Polytechnic (CN)
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Manufacturing Process and Optimization
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