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FEA-based prediction of machined surface errors for dynamic fixture-workpiece system during milling process

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Abstract

In precision manufacturing industry, requirements for surface quality are very high. It is important to accurately predict the machined surface errors to reduce manufacturing costs and lead times as well as develop fixturing scheme to optimize machining quality. This paper presents a contribution for predicting the machined surface errors where fixture-workpiece system dynamic effects during milling process are considered. The combined effect of clam** and milling on machined surface errors prediction is taken into account, and finite element analysis is developed to analyze the workpiece deformation. In finite element analysis environment, the static analysis and explicit dynamic analysis are used to calculate the static deformation due to clam** force and the dynamic deformation due to milling force. Milling forces are applied to the manufacturing points step by step. The chip removal effect is taken into account based on element death technique, and every fixture locator is modeled as a virtual spring-damper system to emulate the fixture-workpiece contact points. The developed methodology has been verified by a set of end milling experiments for ten fixture layouts. The measured and predicted results are in good agreement, and the results also illustrate that the closer the triangle formed by the three locators in the primary datum is to an equilateral triangle, the smaller machined surface errors will be.

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Authors and Affiliations

  1. Key laboratory of Fundamental Science for Advanced Machining, Bei**g Institute of Technology, Bei**g, 100081, China

    Zhaohui Dong, Li Jiao, **bin Wang, Zhiqiang Liang, Zhibing Liu & Jie Yi

Authors
  1. Zhaohui Dong
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  2. Li Jiao
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  3. **bin Wang
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  4. Zhiqiang Liang
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  5. Zhibing Liu
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  6. Jie Yi
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Correspondence to Li Jiao.

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Dong, Z., Jiao, L., Wang, X. et al. FEA-based prediction of machined surface errors for dynamic fixture-workpiece system during milling process. Int J Adv Manuf Technol 85, 299–315 (2016). https://doi.org/10.1007/s00170-015-7854-z

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  • DOI: https://doi.org/10.1007/s00170-015-7854-z

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