On the application of artificial intelligence techniques to the quality improvement of industrial processes

Georgilakis, P; Hatziargyriou, N

dc.contributor.author	Georgilakis, P	en
dc.contributor.author	Hatziargyriou, N	en
dc.date.accessioned	2014-03-01T01:18:09Z
dc.date.available	2014-03-01T01:18:09Z
dc.date.issued	2002	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14823
dc.subject	Artificial Intelligent	en
dc.subject	Artificial Neural Network	en
dc.subject	Difference Set	en
dc.subject	Iron	en
dc.subject	Manufacturing Industry	en
dc.subject	Process Parameters	en
dc.subject	Product Quality	en
dc.subject	Quality Improvement	en
dc.subject	Success Rate	en
dc.subject	Decision Tree	en
dc.subject	Neural Network	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	DECISION TREES	en
dc.title	On the application of artificial intelligence techniques to the quality improvement of industrial processes	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/3-540-46014-4_42	en
heal.identifier.secondary	http://dx.doi.org/10.1007/3-540-46014-4_42	en
heal.language	English	en
heal.publicationDate	2002	en
heal.abstract	In this paper, the combined use of decision trees and artificial neural networks is examined in the area of quality improvement of industrial processes. The main goal is to achieve a better understanding of different settings of process parameters and to be able to predict more accurately the effect of different parameters on the final product quality. This paper also presents results from the application of the combined decision tree - neural network method to the transformer manufacturing industry. In the environment considered, quality improvement is achieved by increasing the classification success rate of transformer iron losses. The results from the application of the proposed method on a transformer industry demonstrate the feasibility and practicality of this approach for the quality improvement of industrial processes.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	METHODS AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE	en
heal.bookName	LECTURE NOTES IN ARTIFICIAL INTELLIGENCE	en
dc.identifier.doi	10.1007/3-540-46014-4_42	en
dc.identifier.isi	ISI:000181051700042	en
dc.identifier.volume	2308	en
dc.identifier.spage	473	en
dc.identifier.epage	484	en