Emerging approaches to process control in injection molding: a comprehensive review

Injection molding process control, a vital technology in modern manufacturing, has seen substantial advancements in recent years through the integration of Computer-Aided Engineering (CAE) technology and intelligent optimization algorithms. CAE technology plays a crucial role in optimizing process p...

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Veröffentlicht in:International journal of advanced manufacturing technology Jg. 140; H. 9-10; S. 4483 - 4502
Hauptverfasser: Cao, Peng, Xie, Jinzhao, Ma, Yitao, Zhao, Bing, Yang, Weimin, Xie, Pengcheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Springer London 01.10.2025
Springer Nature B.V
Schlagworte:
Adaptive control
Artificial intelligence
CAE
CAE) and Design
Computer aided engineering
Computer-Aided Engineering (CAD
Critical Review
Engineering
Genetic algorithms
Industrial and Production Engineering
Injection molding
Machine learning
Manufacturing
Mechanical Engineering
Media Management
Medical equipment
Neural networks
Optimization
Prediction models
Predictive control
Process controls
Process parameters
Real time
Warpage
Injection molding
Computer-aided engineering
Process optimization
Artificial intelligence
Process control
ISSN:0268-3768, 1433-3015
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Zusammenfassung:Injection molding process control, a vital technology in modern manufacturing, has seen substantial advancements in recent years through the integration of Computer-Aided Engineering (CAE) technology and intelligent optimization algorithms. CAE technology plays a crucial role in optimizing process parameters and mold design by simulating key behaviors in the injection molding process, including flow, cooling, shrinkage, and warpage. However, complex process conditions and nonlinear material behaviors pose limitations on the control precision and real-time performance of traditional CAE methods. To address these challenges, intelligent optimization algorithms—such as machine learning, Genetic Algorithms (GAs), and neural networks—have been introduced into the field of injection molding process control, enhancing the accuracy and efficiency of parameter prediction, defect detection, and adaptive control. This paper reviews recent advancements in the application of CAE technology within injection molding, alongside developments in intelligent algorithms for process optimization, parameter control, and predictive model construction. We further discuss the impact and future trends of combining CAE technology and intelligent algorithms on injection molding process control.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-025-16577-6