Intelligent Injection Molding on Sensing, Optimization, and Control

被引:68
作者
Zhao, Peng [1 ,2 ]
Zhang, Jianfeng [1 ,2 ]
Dong, Zhengyang [1 ,2 ]
Huang, Junye [1 ,2 ]
Zhou, Hongwei [3 ]
Fu, Jianzhong [1 ,2 ]
Turng, Lih-Sheng [4 ,5 ]
机构
[1] Zhejiang Univ, Coll Mech Engn, State Key Lab Fluid Power & Mech Syst, Hangzhou 310027, Peoples R China
[2] Zhejiang Univ, Coll Mech Engn, Key Lab 3D Printing Proc & Equipment Zhejiang Pro, Hangzhou 310027, Peoples R China
[3] Teder Machinery Co Ltd, Hangzhou 311224, Peoples R China
[4] Univ Wisconsin, Dept Mech Engn, Madison, WI 53706 USA
[5] Univ Wisconsin, Wisconsin Inst Discovery, Madison, WI 53715 USA
关键词
PREDICTIVE FUNCTIONAL CONTROL; PROCESS PARAMETERS OPTIMIZATION; ITERATIVE LEARNING CONTROL; FAULT-TOLERANT CONTROL; MULTIPLE QUALITY CHARACTERISTICS; GUARANTEED COST CONTROL; TAGUCHI METHOD; MAGNETIC-LEVITATION; CAVITY PRESSURE; BATCH PROCESSES;
D O I
10.1155/2020/7023616
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Injection molding is one of the most significant material processing methods for mass production of plastic products. It is widely used in various industry sectors, and its products are ubiquitous in our daily life. The settings and optimization of the injection molding process dictate the geometric precision and mechanical properties of the final products. Therefore, sensing, optimization, and control of the injection molding process have a crucial influence on product quality and have become an active research field with abundant literature. This paper defines the concept of intelligent injection molding as the integral application of these three procedures-sensing, optimization, and control. This paper reviews recent studies on methods for the detection of relevant physical variables, optimization of process parameters, and control strategies of machine variables in the molding process. Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.
引用
收藏
页数:22
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