基于粒子群算法的注塑产品厚度与成型工艺参数的多目标集成优化  

Integrated Multiobjective Optimization of Part Thickness and Injection Molding Process Parameters Based on PSO

作　　者：路小江[1] 邓益民[1] 

机构地区：[1]浙江省宁波大学工学院,浙江宁波315211

出　　处：《塑料》2008年第1期92-96,81,共6页Plastics

基　　金：浙江省自然科学基金(R104247);浙江省教育厅科研项目(2005163)

摘　　要：提出了一种基于粒子群算法的多目标优化方法,实现对注塑产品厚度与成型工艺参数的多目标集成优化。在应用粒子群算法中,利用改进后的在线归档策略指导粒群体的进化,有效的提高了算法的优良性和收敛性。编写程序自动调用CAD软件和注塑成型软件Moldflow,经过设定相关的工艺参数,调用Moldflow软件进行模拟分析,提取分析结果,计算目标函数等多个步骤后,再按照所提出的优化算法改变优化变量的数值,经过多代分析,最终获得最佳制品厚度以及最佳注射时间、熔料温度、模具温度、浇口位置等工艺参数,实现了翘曲变形、熔接痕、气穴等多个质量指标相对最优。APSO based multi-objective optimization method to obtain the optimal part thickness and its corresponding injection molding process parameters was presented. In applying the PSO algorithm,the improve online documentation stratgy was used to guidance the evolution of particle groups, so the efficiency of the algorithm and the speed in its convergence could be improved markedly. A computer program was developed that automated the steps such as calling the CAD software, setting the injection molding process parameters, calling the software Moldflow to simulate the injection molding process,retrieving the simulation results,and evaluating the objective function. The whole procedure iterated a number of generations by following search process of the proposed optimization algorithm. The optimal part thickness and the optimal molding process parameters were obtained eventually that could produce the part at the relatively optimal qualities in terms of warpage, weld lines, air traps etc.

关 键 词：多目标优化 粒子群算法 在线归档策略 MOLDFLOW 

分 类 号：TP391.72[自动化与计算机技术—计算机应用技术]