摘要
针对注塑工艺多目标优化问题,以塑件的翘曲变形量、顶出时体积收缩率和缩痕深度作为优化目标,选取熔体温度、模具温度、注射时间、保压压力、保压时间等工艺参数为试验因素,采用中心复合试验设计结合模流分析建立试验样本,利用Vague集方法计算各优化目标相似度,通过指标相关性的指标权重确定(CRITIC)法确定各优化目标影响权重,得到综合相似度;建立综合相似度与各工艺参数之间的响应面模型,运用灰狼算法进行工艺参数寻优,得到最优工艺参数组合。结果表明,将Vague集和响应面模型相结合的优化结果显著,为实际生产过程提供了有益参考。
For the multi-objective optimization problem of injection molding,the warpage deformation,volumetric shrinkage rate and shrinkage depth of the plastic parts were taken as the optimization objectives,and the process parameters,such as,melt temperature,mold temperature,injection time,holding pressure and holding time were selected as experimental factors.The central composite experimental design was combined with the moldflow analysis to establish experimental samples,and the similarity of each optimization objective was calculated using the Vague set method,then the influence weight of each optimization objective was calculated by criteria importance through intercriteria correlation(CRITIC)method.A response surface model between the comprehensive similarity and various process parameters was established,and grey wolf algorithm was applied to obtain the optimal combination of process parameters.The results show that the combination of Vague sets and response surface model provide significant optimization results and provide useful reference for practical production processes.
作者
张庆
何也能
ZHANG Qing;HE Yeneng(Zhejiang Industry Polytechnic College,Shaoxing 312000,China)
出处
《塑料工业》
CAS
CSCD
北大核心
2024年第1期93-100,共8页
China Plastics Industry
基金
浙江省教育厅一般科研项目(Y202043858)。
关键词
VAGUE集
响应面模型
灰狼算法
注塑成型
多目标优化
Vague Set
Response Surface Model
Grey Wolf Algorithm
Injection Molding
Multi-objective Optimization
