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外部气体辅助模具温度控制和优化成型参数,以提高聚酰胺塑料的焊接线强度。

External gas-assisted mold temperature control and optimization molding parameters for improving weld line strength in polyamide plastics.

机构信息

Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam.

Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam.

出版信息

PLoS One. 2024 Aug 22;19(8):e0307485. doi: 10.1371/journal.pone.0307485. eCollection 2024.

DOI:10.1371/journal.pone.0307485
PMID:39172972
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11340943/
Abstract

In this study, we present a novel approach to injection molding, focusing on the strength of weld lines in polyamide 6 (PA6) composite samples. By implementing a mold temperature significantly higher than the typical molding practice, which rarely exceeds 100°C, we assess the effects of advanced mold temperature management. The research introduces a newly engineered mold structure specifically designed for localized mold heating, distinguishing it as the 'novel cavity.' This innovative design is compared against traditional molding methods to highlight the improvements in weld line strength at elevated mold temperatures. To optimize the molding parameters, we apply an Artificial Neural Network (ANN) in conjunction with a Genetic Algorithm (GA). Our findings reveal that the optimal ultimate tensile strength (UTS) and elongation values are achieved with a filling time of 3.4 seconds, packing time of 0.8 seconds, melt temperature of 246°C, and a novel high mold temperature of 173°C. A specific sample demonstrated the best molding parameters at a filling time of 3.4 seconds, packing time of 0.4 seconds, melt temperature of 244°C, and mold temperature of 173°C, resulting in an elongation value of 582.6% and a UTS of 62.3 MPa. The most influential factor on the PA6 sample's UTS and elongation at the weld line was found to be the melt temperature, while the filling time had the least impact. SEM analysis of the fracture surfaces revealed ductile fractures with rough surfaces and grooves, indicative of the weld line areas' bonding quality. These insights pave the way for significant improvements in injection molding conditions, potentially revolutionizing the manufacturing process by enhancing the structural integrity of the weld lines in molded PA6 samples.

摘要

在本研究中,我们提出了一种新颖的注塑方法,重点研究了聚酰胺 6(PA6)复合材料样品中焊接线的强度。通过采用远高于典型注塑工艺(通常不超过 100°C)的模具温度,我们评估了先进模具温度管理的效果。本研究引入了一种新设计的模具结构,专门用于局部模具加热,将其称为“新型型腔”。该创新设计与传统成型方法进行了比较,突出了在提高模具温度下焊接线强度的改进。为了优化成型参数,我们应用人工神经网络(ANN)结合遗传算法(GA)。我们的研究结果表明,在填充时间为 3.4 秒、保压时间为 0.8 秒、熔体温度为 246°C 和新型高模具温度为 173°C 的情况下,可以获得最佳的极限拉伸强度(UTS)和伸长率值。一个特定的样品在填充时间为 3.4 秒、保压时间为 0.4 秒、熔体温度为 244°C 和模具温度为 173°C 的情况下展示了最佳的成型参数,其伸长率值为 582.6%,UTS 值为 62.3 MPa。对 PA6 样品焊接线的 UTS 和伸长率影响最大的因素是熔体温度,而填充时间的影响最小。对断裂表面的 SEM 分析显示出韧性断裂,具有粗糙表面和凹槽,表明焊接线区域的结合质量。这些见解为注塑条件的重大改进铺平了道路,通过增强注塑成型 PA6 样品中焊接线的结构完整性,有可能彻底改变制造过程。

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