摘要
针对汽车进气格栅产品结构复杂、注塑质量难以保证的问题,采用CAE仿真分析技术对其浇注系统设计进行了改进,改进后的浇注系统采用热流道嘴多点浇注系统,各热流道嘴采用针阀进行时序控制。通过运用神经网络寻优最佳注塑工艺参数、热流道嘴时序开启时间参数,获得了较好的工艺参考参数,解决了产品熔接线和翘曲变形的质量问题,缩短了产品成型周期。实践表明,采用CAE和神经网络分析优化后的产品注塑质量合格,满足了塑料制品成型的高效、精益化生产的需求。
Aiming at the problem that the structure of automobile inlet grille was complex and the injection quality was difficult to guarantee, the design of gating system was improved by CAE simulation analysis technology. The improved gating system adopted a multi-point gating system with hot runner nozzle, and each hot runner adopted a needle valve for timing control. By using neural network to optimize the optimum injection process parameters and to open time parameters with the time sequence of the hot runner, a good process reference parameter was obtained, which solved the quality problems of the product fuse wiring and warping deformation and shortened the product forming cycle. The practice showed that the injection quality of the optimized product was qualified by CAE and neural network, meeting the requirements of high efficiency and lean production.
出处
《塑料工业》
CSCD
北大核心
2017年第9期72-77,81,共7页
China Plastics Industry
基金
广西教育厅科研课题(KY2015YB479)
关键词
CAE分析
神经网络
注塑成型优化
热流道
针阀
时序控制
CAE Analysis
Neural Network
Injection Molding Optimization
Hot Runner
Needle Valve
Timing Control
