Statistical Control of Defects in a Continuously Cast Billet Based on Machine Learning and Data Analysis Methods

 
PIIS000523100001250-9-1
DOI10.31857/S000523100001250-9
Publication type Article
Status Published
Authors
Affiliation: Cherepovets State University
Address: Russian Federation, Cherepovets
Affiliation: Cherepovets State University
Address: Russian Federation, Cherepovets
Affiliation: Cherepovets State University
Address: Russian Federation, Cherepovets
Journal nameAvtomatika i Telemekhanika
EditionIssue 8
Pages101-110
Abstract

We consider the problems of defects arising in the production of continuously cast billets at continuous casting plants. We propose a model for predicting slab cracks based on the random forest machine learning algorithm. We determine the main technological parameters that influence the appearance of cracks and present the results of the model.

 
KeywordsStatistical control, continuous casting defect, continuous steel casting, cracks on the slab, hot charging, random forests, influencing parameters
Received30.09.2018
Publication date30.09.2018
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