DocumentCode :
2144681
Title :
Neural networks and search for minimum defectiveness in molding operation in ceramic industry
Author :
Kumru, M.
Author_Institution :
Dept. of Ind. Eng., Dogus. Univ., İstanbul, Turkey
fYear :
2011
fDate :
15-18 June 2011
Firstpage :
335
Lastpage :
339
Abstract :
This study is to be conducted in a ceramics production plant where the highest product defectiveness occurs in the molding shop of the plant. There are a number of factors that affect the amount of product defectiveness. The purpose is to search for a set of factor treatment conditions which provide the minimum defectiveness performance in the shop. Artificial Neural Network (ANN) method was used to realize the purpose. Based on the statistical analysis, the ANN approach is found to be reliable in predicting the amount of defectiveness that depends on various factors.
Keywords :
ceramic industry; moulding; neural nets; production engineering computing; statistical analysis; artificial neural network method; ceramic industry; ceramics production plant; minimum defectiveness performance; molding operation; molding shop; product defectiveness; statistical analysis; Artificial neural networks; Biological neural networks; Ceramics; Forecasting; Predictive models; Production; Training; artificial neural networks; ceramic molding process; experiment design; metaheuristics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-61284-919-5
Type :
conf
DOI :
10.1109/INISTA.2011.5946140
Filename :
5946140
Link To Document :
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