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优化玻璃纤维复合材料注塑成型中熔接线的拉伸强度

Optimizing the Tensile Strength of Weld Lines in Glass Fiber Composite Injection Molding.

作者信息

Uyen Tran Minh The, Nguyen Hong Trong, Nguyen Van-Thuc, Minh Pham Son, Do Thanh Trung, Nguyen Van Thanh Tien

机构信息

Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City 71307, Vietnam.

Faculty of Mechanical Engineering, Industrial University of Ho Chi Minh City, Nguyen Van Bao Street, Ward 4, Go Vap District, Ho Chi Minh City 70000, Vietnam.

出版信息

Materials (Basel). 2024 Jul 11;17(14):3428. doi: 10.3390/ma17143428.

Abstract

Weld line defects, commonly occurring during the plastic product manufacturing process, are caused by the merging of two opposing streams of molten plastic. The presence of weld lines harms the product's aesthetic appeal and durability. This study uses artificial neural networks to forecast the ultimate tensile strength of a PA6 composite incorporating 30% glass fibers (GFs). Data were collected from tensile strength tests and the technical parameters of injection molding. The packing pressure factor is the one that significantly affects the tensile strength value. The melt temperature has a significant impact on the product's strength as well. In contrast, the filling time factor has less impact than other factors. According to the scanning electron microscope result, the smooth fracture surface indicates the weld line area's high brittleness. Fiber bridging across the weld line area is evident in numerous fractured GF pieces on the fracture surface, which enhances this area. Tensile strength values vary based on the injection parameters, from 65.51 MPa to 73.19 MPa. In addition, the experimental data comprise the outcomes of the artificial neural networks (ANNs), with the maximum relative variation being only 4.63%. The results could improve the PA6 reinforced with 30% GF injection molding procedure with weld lines. In further research, mold temperature improvement should be considered an exemplary method for enhancing the weld line strength.

摘要

熔接线缺陷通常出现在塑料制品制造过程中,是由两股相对的熔融塑料流合并造成的。熔接线的存在损害了产品的美观性和耐用性。本研究使用人工神经网络来预测含30%玻璃纤维(GF)的PA6复合材料的极限拉伸强度。数据从拉伸强度测试和注塑成型的技术参数中收集。保压压力因素对拉伸强度值有显著影响。熔体温度对产品强度也有显著影响。相比之下,填充时间因素的影响比其他因素小。根据扫描电子显微镜结果,光滑的断裂表面表明熔接线区域脆性高。在断口表面众多断裂的GF碎片中,纤维跨过熔接线区域的桥接现象明显,这增强了该区域。拉伸强度值因注塑参数而异,范围为65.51MPa至73.19MPa。此外,实验数据包含人工神经网络(ANN)的结果,最大相对变化仅为4.63%。这些结果可以改进含30%GF且有熔接线的PA6注塑成型工艺。在进一步的研究中,提高模具温度应被视为增强熔接线强度的一种示例性方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c019/11277594/04abaf2b6eda/materials-17-03428-g001.jpg

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