注塑成型工艺多目标稳健设计及优化算法  

Multi-objective Robust Design and Optimum Algorithm in Injection Molding Processing

作　　者：黄风立[1,2] 林建平[1] 钟美鹏[2] 许锦泓[2] 

机构地区：[1]同济大学机械工程学院,上海201804 [2]嘉兴学院机电工程学院,浙江嘉兴314001

出　　处：《同济大学学报（自然科学版）》2011年第2期287-291,298,共6页Journal of Tongji University:Natural Science

基　　金：浙江省教育科研计划(Y200805365;Y200909445);嘉兴市科技计划(2009AY2004)

摘　　要：在注塑成型过程单目标稳健设计的基础上,提出了成型质量特性均值及标准差的双目标稳健设计模型以及成型多质量特性的多目标稳健设计模型,提出了基于Pareto最优的混合交叉变异的多目标蚁群算法.在结合实例的研究中,针对某遥控器上下盖的注塑成型工艺参数设置分别建立了翘曲量均值及标准差的双目标稳健设计模型和最大翘曲量及最大体积收缩率的多目标稳健设计模型,再利用混合交叉变异的多目标蚁群算法进行求解,求解结果与non-dominated sorting genetic algorithmsⅡ(NSGAⅡ)算法比较,得出部分算法性能指标优于NSGAⅡ算法.利用多目标稳健优化得到的工艺参数进行实际注塑成型,得到的塑件制品成型质量好并且波动较小.Based on the single objective robust design of injection molding process,the paper presents the bi-objective robust design model based on the mean and standard deviation of the molding quality,the multi-objective robust design model with the multi quality features and the multi-objective ant colonies algorithm with crossover and mutation based on Pareto optimization.Aimed at the craft parameters of plastic injection for the top and down shell of remote controller,both the model of bi-objective robust design based on the mean and standard deviation of warpage quantity,and the model of multi-objective robust design based on the maximum warpage quantity and the maximum volume shrinkage are established with an example.With the multi-objective ant colonies algorithm of crossover and mutation,the models are solved.The result shows that the partial performance of algorithm is superior to that of non-dominated sorting genetic algorithms Ⅱ（NSGAⅡ）.The actual plastic injection was done by means of the parameters obtained by multi objections robust optimization.The quality of plastic parts was high,and the fluctuation was small.

关 键 词：注塑成型 多目标稳健设计 蚁群算法 PARETO最优 

分 类 号：TQ320.66[化学工程—合成树脂塑料工业]