Shrinkage analysis of molded parts using neural network

被引：16

作者：

Lee, SC

Youn, JR

机构：

[1] Mokpo Natl Univ, Dept Mech Engn, Chungkyemyon 534729, Chonnam, South Korea

[2] Seoul Natl Univ, Dept Fiber & Polymer Sci, Seoul, South Korea

来源：

JOURNAL OF REINFORCED PLASTICS AND COMPOSITES | 1999年 / 18卷 / 02期

关键词：

injection molding; semiconductor; shrinkage; neural network;

D O I：

10.1177/073168449901800205

中图分类号：

TB33 [复合材料];

学科分类号：

摘要：

To predict the shrinkage of molded parts using numerical simulations, the mathematical model should be simplified to overcome the difficulties of formulation due to non-linearity of problems. It is hard to predict the shrinkage exactly because of the simplification. In the present work, the neural network is used to predict the shrinkage which can implement nonlinear models very well. Comparison between the results of neural network and that of the commercial analysis software, ABAQUS, shows that the result of the neural network is in better agreement with that of the experiments.

引用

页码：186 / 195

页数：10