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. 2024 Aug 8;17(16):3949.
doi: 10.3390/ma17163949.

Multi-Objective Optimization of Injection Molding Parameters for Manufacturing Thin-Walled Composite Connector Terminals

Mingbo Tan  1 , Size Peng  1   2 , Yingfei Huo  3 , Maojun Li  1
Affiliations

Multi-Objective Optimization of Injection Molding Parameters for Manufacturing Thin-Walled Composite Connector Terminals

Mingbo Tan et al. Materials (Basel). .

Abstract

The rapid development of new energy vehicles demands significant improvements in connector structures and performance standards. Wire harness connectors, crucial for linking various electrical components, face challenges due to their small size and thin-walled structure, which can lead to dimensional shrinkage and warping during injection molding. To address these issues, this study optimizes the injection molding process by fine-tuning parameters such as melt temperature, mold temperature, injection time, holding pressure/time, and cooling time. By integrating the Taguchi method with grey relational analysis, the study enhances the molding process for thin-walled composite connectors. This combined approach provides a comprehensive framework for optimizing multiple quality objectives and improving the overall performance of injection-molded composite components.

Keywords: composites; flow characteristics; injection molding; multi-objective optimization.

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Conflict of interest statement

Author Size Peng was employed by the company Hunan Xingtu Aerospace and Spacecraft Manufacturing Co., Ltd. Author Yingfei Huo was employed by the company Yangzhou Pinghang Aerodynamics Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 2
Figure 2
Flowchart of the proposed method.
Figure 1
Figure 1
Schematic showing the injection molding process.
Figure 3
Figure 3
3D structure model and mesh model diagrams.
Figure 4
Figure 4
Distribution map of warping deformation.
Figure 5
Figure 5
Distribution of contribution for various process parameters.
Figure 6
Figure 6
The main effect diagram of S/N for volume shrinkage.
Figure 7
Figure 7
Shrink in the (a) optimum and (b) worst case.
Figure 8
Figure 8
The main effect diagram of S/N for warping deformation.
Figure 9
Figure 9
Warping in the (a) optimum and (b) worst case.
Figure 10
Figure 10
Main effects plot for GRG means.
See this image and copyright information in PMC

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