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Evaluation of effect of plastic injection molding process parameters on shrinkage based on neural network simulation

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成果类型:
期刊论文
作者:
Wang, Rongji*;Zeng, Junliang;Feng, Xiaoxin;Xia, Yuejun
通讯作者:
Wang, Rongji
作者机构:
[Feng, Xiaoxin; Wang, Rongji; Zeng, Junliang; Xia, Yuejun] Cent S Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha 410004, Hunan, Peoples R China.
通讯机构:
[Wang, Rongji] C
Cent S Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
Cooling time;Crystallinities;Fill pressure;Melt temperature;Mold temperatures;Moldflow;Neural network simulations;Packing pressure;Plastic injection molding;Process parameters;Reasonable accuracy;C (programming language);Molds;Neural networks;Polypropylenes;Research laboratories;Shrinkage
期刊:
JOURNAL OF MACROMOLECULAR SCIENCE PART B-PHYSICS
ISSN:
0022-2348
年:
2013
卷:
52
期:
1
页码:
206-221
机构署名:
本校为第一且通讯机构
院系归属:
机电工程学院
摘要:
The effects of process parameters, mold temperature (T mo), melt temperature (T me), cooling time (t c), fill pressure (P f), packing pressure (P p), and packing time (t p) on the shrinkage of injection molded polypropylene were investigated by utilizing a combination of the Artificial Neural Network (ANN) method and Moldflow software. An ANN model is developed to understand the relationship between plastic injection molding process parameters and shrinkage. The test results on the performance of the ANN model show that it can predict the shrin...

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