Intelligent Injection Molding on Sensing, Optimization, and Control

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Advances in polymer technology Ročník 2020; číslo 2020; s. 1 - 22
Hlavní autoři: Turng, Lih-sheng, Zhou, Hongwei, Huang, Junye, Dong, Zhengyang, Zhang, Jianfeng, Zhao, Peng, Fu, Jianzhong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cairo, Egypt Hindawi Publishing Corporation 01.01.2020
Hindawi
John Wiley & Sons, Inc
Wiley
Témata:
Advanced manufacturing technologies
Algorithms
Artificial intelligence
Detection
Injection molding
Manufacturing
Mass production
Mechanical properties
Methods
Optimization
Plastics industry
Polymer melts
Pressure distribution
Process controls
Process parameters
Product quality
Production methods
Quality control
Researchers
Sensors
Thermocouples
Variables
United States > US
ISSN:0730-6679, 1098-2329
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0730-6679
1098-2329
DOI:10.1155/2020/7023616