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Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO

Received: 30 August 2022     Accepted: 15 September 2022     Published: 21 September 2022
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Abstract

Taking the amount of warpage deformation of automotive brake Plug-in as the research object, UG NX10.0 software was used to design the product model and Moldflow software was used for predictive analysis of the product model. The preliminary optimized parameters were obtained by using the response surface method - central composite experiment design (CCD) and combined with injection molding CAE technology. The mold temperature was 70°C, the melt temperature was 250°C, the holding pressure was 95 MPa, and the holding time was 10s. The warpage was 1.18 mm. Through the analysis of variance, the influence of four injection process parameters on product warpage was obtained, namely, holding pressure>holding time>melt temperature>mold temperature. Based on the fitted response surface algorithm model, the process parameters were optimized using particle swarm optimization (PSO) with the minimum warpage as the constraint condition, and the optimal combination of the optimized process parameters was obtained, that was, the mold temperature was 60°C, the melt temperature was 280°C, the holding pressure was 95 MPa and the holding time was 8.296 s. The minimum warpage was 1.057 mm. The optimization results showed that the minimum warpage was reduced by 10.85% compared with the initially optimized parameters, and the effectiveness of the proposed method was verified by using this parameter combination for actual injection production.

Published in International Journal of Materials Science and Applications (Volume 11, Issue 4)
DOI 10.11648/j.ijmsa.20221104.11
Page(s) 84-94
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Automotive Brake Plug-in, Response Surface, Injection Molding Process Parameters, Warpage, Particle Swarm Optimization

References
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Cite This Article
  • APA Style

    Huan-Lao Liu, Zi-Lin Zhang, Pei-Ming Peng, Can Liu. (2022). Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO. International Journal of Materials Science and Applications, 11(4), 84-94. https://doi.org/10.11648/j.ijmsa.20221104.11

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    ACS Style

    Huan-Lao Liu; Zi-Lin Zhang; Pei-Ming Peng; Can Liu. Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO. Int. J. Mater. Sci. Appl. 2022, 11(4), 84-94. doi: 10.11648/j.ijmsa.20221104.11

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    AMA Style

    Huan-Lao Liu, Zi-Lin Zhang, Pei-Ming Peng, Can Liu. Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO. Int J Mater Sci Appl. 2022;11(4):84-94. doi: 10.11648/j.ijmsa.20221104.11

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  • @article{10.11648/j.ijmsa.20221104.11,
      author = {Huan-Lao Liu and Zi-Lin Zhang and Pei-Ming Peng and Can Liu},
      title = {Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO},
      journal = {International Journal of Materials Science and Applications},
      volume = {11},
      number = {4},
      pages = {84-94},
      doi = {10.11648/j.ijmsa.20221104.11},
      url = {https://doi.org/10.11648/j.ijmsa.20221104.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmsa.20221104.11},
      abstract = {Taking the amount of warpage deformation of automotive brake Plug-in as the research object, UG NX10.0 software was used to design the product model and Moldflow software was used for predictive analysis of the product model. The preliminary optimized parameters were obtained by using the response surface method - central composite experiment design (CCD) and combined with injection molding CAE technology. The mold temperature was 70°C, the melt temperature was 250°C, the holding pressure was 95 MPa, and the holding time was 10s. The warpage was 1.18 mm. Through the analysis of variance, the influence of four injection process parameters on product warpage was obtained, namely, holding pressure>holding time>melt temperature>mold temperature. Based on the fitted response surface algorithm model, the process parameters were optimized using particle swarm optimization (PSO) with the minimum warpage as the constraint condition, and the optimal combination of the optimized process parameters was obtained, that was, the mold temperature was 60°C, the melt temperature was 280°C, the holding pressure was 95 MPa and the holding time was 8.296 s. The minimum warpage was 1.057 mm. The optimization results showed that the minimum warpage was reduced by 10.85% compared with the initially optimized parameters, and the effectiveness of the proposed method was verified by using this parameter combination for actual injection production.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Optimization of Injection Molding Process Parameters for Automotive Brake Plug-in Based on CCD and PSO
    AU  - Huan-Lao Liu
    AU  - Zi-Lin Zhang
    AU  - Pei-Ming Peng
    AU  - Can Liu
    Y1  - 2022/09/21
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ijmsa.20221104.11
    DO  - 10.11648/j.ijmsa.20221104.11
    T2  - International Journal of Materials Science and Applications
    JF  - International Journal of Materials Science and Applications
    JO  - International Journal of Materials Science and Applications
    SP  - 84
    EP  - 94
    PB  - Science Publishing Group
    SN  - 2327-2643
    UR  - https://doi.org/10.11648/j.ijmsa.20221104.11
    AB  - Taking the amount of warpage deformation of automotive brake Plug-in as the research object, UG NX10.0 software was used to design the product model and Moldflow software was used for predictive analysis of the product model. The preliminary optimized parameters were obtained by using the response surface method - central composite experiment design (CCD) and combined with injection molding CAE technology. The mold temperature was 70°C, the melt temperature was 250°C, the holding pressure was 95 MPa, and the holding time was 10s. The warpage was 1.18 mm. Through the analysis of variance, the influence of four injection process parameters on product warpage was obtained, namely, holding pressure>holding time>melt temperature>mold temperature. Based on the fitted response surface algorithm model, the process parameters were optimized using particle swarm optimization (PSO) with the minimum warpage as the constraint condition, and the optimal combination of the optimized process parameters was obtained, that was, the mold temperature was 60°C, the melt temperature was 280°C, the holding pressure was 95 MPa and the holding time was 8.296 s. The minimum warpage was 1.057 mm. The optimization results showed that the minimum warpage was reduced by 10.85% compared with the initially optimized parameters, and the effectiveness of the proposed method was verified by using this parameter combination for actual injection production.
    VL  - 11
    IS  - 4
    ER  - 

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Author Information
  • School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, PR China

  • School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, PR China

  • School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, PR China

  • School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, PR China

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