针对注塑成型制品翘曲问题的数值模拟及参数优化方法研究

发布时间：2018-11-14 20:12

【摘要】：针对注塑制品的翘曲变形问题,借助有限元分析软件MoldFlow对注塑成型过程进行数值模拟分析。在此基础上,分别利用正交矩阵法、响应面法及遗传算法对注塑工艺参数进行多目标优化,从而降低制品的翘曲变形量。以下为本文的研究内容及结论:(1)利用正交矩阵方法,对一电器塑料外壳注塑成型过程进行多目标优化,计算出各工艺因素影响度值,并根据影响度值判定该注塑过程主要影响因素,从而获取最优的工艺参数组合,实现对制品翘曲变形及体积收缩率进行优化。(2)利用响应面法研究了一静态支架注塑成型过程中模具温度、熔体温度、注射时间、保压时间及冷却时间五个注塑工艺参数对制品翘曲变形的影响,并分析了它们之间的交互影响作用,最终通过对响应面模型的寻优,得到该注塑成型过程最佳工艺参数组合。(3)利用正交试验方法,借助MoldFlow软件对车灯副反射器进行翘曲变形分析。借助BP神经网络建立注塑工艺参数(熔体温度、模具温度、注射时间、保压时间、冷却时间)与产品翘曲变形之间的关系。利用遗传算法对BP神经网络进行全局寻优,得到产品的最小翘曲变形,以此实现对注塑成型工艺参数的优化,进而减小产品翘曲变形,提高产品质量。
[Abstract]:Aiming at the warpage deformation of injection molding products, the numerical simulation of injection molding process is carried out by means of finite element analysis software MoldFlow. On this basis, the orthogonal matrix method, response surface method and genetic algorithm are used to optimize the injection molding process parameters respectively, so as to reduce the warpage of the products. The following are the contents and conclusions of this paper: (1) by using the orthogonal matrix method, the multi-objective optimization of the injection molding process of an electrical plastic shell is carried out, and the influence degree of each process factor is calculated. According to the value of influence degree, the main influencing factors of the injection molding process are determined, and the optimal combination of process parameters is obtained. The warping deformation and volume shrinkage of the products are optimized. (2) the mold temperature, melt temperature and injection time of a static support during injection molding are studied by response surface method. The influence of five injection molding process parameters on the warpage deformation of the product is analyzed, and the interaction between them is analyzed. Finally, the response surface model is optimized. The optimal process parameters of the injection molding process are obtained. (3) the warpage deformation analysis of the lamp secondary reflector is carried out by using the orthogonal test method and the MoldFlow software. The relationship between injection molding process parameters (melt temperature, mold temperature, injection time, pressure holding time, cooling time) and warping deformation of the product was established by means of BP neural network. The global optimization of BP neural network is carried out by genetic algorithm, and the minimum warpage deformation of the product is obtained, so as to optimize the process parameters of injection molding, and then reduce the warping deformation of the product and improve the quality of the product.
【学位授予单位】：山东科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP18;TQ320.662

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