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 :
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