DocumentCode
1951103
Title
Machine learning algorithms for quality control in plastic molding industry
Author
Tellaeche, Alberto ; Arana, Ramon
Author_Institution
Tekniker-IK4, Eibar, Spain
fYear
2013
fDate
10-13 Sept. 2013
Firstpage
1
Lastpage
4
Abstract
Injection molding is a very complicated process to monitor and control. With its high complexity and many process parameters, the optimization of these systems is a very challenging problem. To meet the requirements and costs demanded by the market, there has been an intense development and research with the aim to maintain the process under control. This paper outlines the latest advances in algorithms for plastic injection process and monitoring, and presents a real case of application that verifies their performance.
Keywords
injection moulding; learning (artificial intelligence); plastics industry; process monitoring; production engineering computing; quality control; machine learning algorithms; plastic injection monitoring; plastic injection process; plastic molding industry; quality control; Injection molding; Machine learning algorithms; Monitoring; Optimization; Plastics; Process control;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies & Factory Automation (ETFA), 2013 IEEE 18th Conference on
Conference_Location
Cagliari
ISSN
1946-0740
Print_ISBN
978-1-4799-0862-2
Type
conf
DOI
10.1109/ETFA.2013.6648103
Filename
6648103
Link To Document