摘要
以翘曲变形和收缩为质量指标,采用正交试验法、神经网络模型和遗传算法,优化了模具温度、熔体温度、注塑压力、注塑时间、保压压力、保压时间和冷却时间,获得了工艺参数的最优配置组合,提高了制品质量。利用最优配置组合的工艺参数进行了注塑成型试验,并通过测量验证了CAE模拟的正确性。
Warpage and shrinkage were taken as the quality index, mold temperature,melt temperature,injection pressure, injection time, packing pressure,packing time and cooling time were optimized by using the taguchi,neural network model and genetic algorithm. Optimal combination of process parameters were obtained and products quality was improved. The injection molding experiment was conducted by using optimal combination of process parameters and the validity of the CAE simulation was verified via measuring.
出处
《塑料》
CAS
CSCD
北大核心
2013年第5期106-109,共4页
Plastics
关键词
工艺参数
神经网络
遗传算法
优化
CAE
process parameters
neural network
genetic algorithm
optimization
CAE
