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基于统计提升准则的注塑工艺参数优化
引用本文:谭帅,彭俊,李闯.基于统计提升准则的注塑工艺参数优化[J].材料科学与工艺,2014,22(2):68-74.
作者姓名:谭帅  彭俊  李闯
作者单位:东北大学 信息科学与工程学院,沈阳 110004;东北大学 信息科学与工程学院,沈阳 110004;中能电力科技开发有限公司,北京 100034
基金项目:中央高校基本科研专项资金资助项目(N120304004);中国博士后科学基金资助项目(2013M530937).
摘    要:为了同时改善生产平板型注塑制品时的总体收缩度和收缩均匀度,提出基于统计提升准则的注塑成型工艺参数的多目标优化方法,寻找平衡两个质量指标的优化设计.首先利用小规模的实验设计方法获得建模数据集,针对应用中存在的建模数据奇异点问题提出一种数据预处理方法,并依此分别建立两个指标的初始替代模型,用于代替优化过程中代价高昂的计算分析;随后依据Pareto统计提升准则寻找新的采样点加入建模数据集来重新建模,使寻优结果不断趋近真实的Pareto前沿.仿真结果表明,较常规的建模优化方法,本文提出的方法能使用较少的采样数据,显著地改善平板制品的收缩质量.对于HDPE材质的矩形制品,保压曲线先恒定后线性递减可以获得好的收缩均匀度,使用压力上限值恒定保压可以获得好的平均收缩度.

关 键 词:注塑成型  收缩  多目标优化  统计提升准则  Kriging模型
收稿时间:2013/10/2 0:00:00

Multi-objective optimization of injection molding process parameters based on statistical improvement criterion
TAN Shuai,PENG Jun and LI Chuang.Multi-objective optimization of injection molding process parameters based on statistical improvement criterion[J].Materials Science and Technology,2014,22(2):68-74.
Authors:TAN Shuai  PENG Jun and LI Chuang
Affiliation:School of Information Science & Engineering, Northeastern University, Shenyang 110004, China;School of Information Science & Engineering, Northeastern University, Shenyang 110004, China;ZhongNeng Power Technology Development Co.Ltd., Beijing 100034, China
Abstract:To improve the shrinkage and evenness of the production of injection molded slab, this article introduces an iterative multi objective optimization method based on Kriging surrogate model to find the Pareto set of the optimization problem. The idea of the iterative optimization method is first to establish two approximation function relationships between those index and process parameters by a small size of design of experiment (DOE) with surrogate model to alleviate the expensive computational expense in the optimization iterations. And then statistical improvement criterion of Pareto front is used to provide direction in which additional training samples could be added to better the surrogate model. This process will loop and bring the optimization result close to the ideal Pareto front. Simulation results show that a much better shrinkage quality of molded part can be achieved with the proposed method with smaller amount of samples compared with traditional modeling and optimization method. For rectangular HDPE products, good evenness can be gotten using linear decreasing pressure curve after a period of constant value, and good shrinkage can be gotten using holding pressure with upper limits.
Keywords:injection molding  shrinkage  multi-objective optimization  statistical improvement criterion  kriging model
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