Defect Prediction in Hot Strip Rolling Using ANN and SVM

Authors:
Manu Hietaniemi;Ulla Elsilä;Perttu Laurinen;Juha Röning
Affiliations:
manu@ee.oulu.fi;University of Oulu, Department of Electrical Engineering, Computer Engineering Laboratory, Intelligent Systems Group, PO BOX 4500, FIN-90401 Oulu, Finland;University of Oulu, Department of Electrical Engineering, Computer Engineering Laboratory, Intelligent Systems Group, PO BOX 4500, FIN-90401 Oulu, Finland;University of Oulu, Department of Electrical Engineering, Computer Engineering Laboratory, Intelligent Systems Group, PO BOX 4500, FIN-90401 Oulu, Finland
Venue:
Proceedings of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008
Year:
2008

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Abstract

One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very important. In this study we used classifiers --feedforward neural networks and a support vector machine --to solve this problem. We also used different kinds of feature selection methods such as a preprocessing step for the classifiers. As a result, these two classifiers confirmed the same grade of classification error in this study.