修剪
材料科学
模具
造型(装饰)
注塑机
复合材料
机械工程
结构工程
工程类
作者
Chengmao Huang,Wenxuan Zhang,Yu Zhang,Jianguo Wen,Yifeng Ma,Shande Li
摘要
ABSTRACT Reaction injection molding is particularly well‐suited for the fabrication of large, intricate components exhibiting variable wall thicknesses. It is the primary manufacturing process utilized for polydicyclopentadiene products. The polymerization reaction of dicyclopentadiene occurs during the reaction injection molding, releasing high exothermic energy, which can lead to uneven cooling that can readily result in warpage deformation. Therefore, the polydicyclopentadiene reaction injection molding mold must be equipped with an efficient cooling system to guarantee the quality of plastic parts produced and ensure optimal production efficiency. This paper took the cooling system of the polydicyclopentadiene reaction injection molding mold of the lower door trim as the research object. An agent model for the prediction of cooling effect based on the GA‐BP neural network was established, and the spatial arrangement parameter combinations of cooling channels were optimized using the GA‐BP‐SAPSO algorithm. Following optimization, the warpage deformation and the average volume shrinkage were reduced by 21.5% and7.5%, respectively, and the temperature difference between the inlet and outlet of cooling channels was reduced to 2.26°C. The optimization results align with the design specifications for polydicyclopentadiene reaction injection molding of the lower door trim.
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