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Materials 2015, 8(6), 3562-3583; doi:10.3390/ma8063562

A New Predictive Model of Centerline Segregation in Continuous Cast Steel Slabs by Using Multivariate Adaptive Regression Splines Approach

1
Department of Mathematics, University of Oviedo, Oviedo 33007, Spain
2
Department of Electrical Engineering, University of Oviedo, Gijón 33204, Spain
3
Finishing Department, ArcelorMittal España, Avilés 33400, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Luciano Feo
Received: 25 May 2015 / Revised: 4 June 2015 / Accepted: 8 June 2015 / Published: 17 June 2015
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Abstract

The aim of this study was to obtain a predictive model able to perform an early detection of central segregation severity in continuous cast steel slabs. Segregation in steel cast products is an internal defect that can be very harmful when slabs are rolled in heavy plate mills. In this research work, the central segregation was studied with success using the data mining methodology based on multivariate adaptive regression splines (MARS) technique. For this purpose, the most important physical-chemical parameters are considered. The results of the present study are two-fold. In the first place, the significance of each physical-chemical variable on the segregation is presented through the model. Second, a model for forecasting segregation is obtained. Regression with optimal hyperparameters was performed and coefficients of determination equal to 0.93 for continuity factor estimation and 0.95 for average width were obtained when the MARS technique was applied to the experimental dataset, respectively. The agreement between experimental data and the model confirmed the good performance of the latter. View Full-Text
Keywords: statistical learning techniques; continuous cast steel labs; centerline segregation; multivariate adaptive regression splines (MARS); regression analysis statistical learning techniques; continuous cast steel labs; centerline segregation; multivariate adaptive regression splines (MARS); regression analysis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Nieto, P.J.G.; Suárez, V.M.G.; Antón, J.C.Á.; Bayón, R.M.; Blanco, J.Á.S.; Fernández, A.M.D. A New Predictive Model of Centerline Segregation in Continuous Cast Steel Slabs by Using Multivariate Adaptive Regression Splines Approach. Materials 2015, 8, 3562-3583.

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