University of Oulu

Siirtola, P., Tamminen, S., Ferreira, E., Tiensuu, H., Prokkola, E., & Röning, J. (2018, December 19). Recognizing Steel Plate Side Edge Shape automatically using Classi?cation and Regression Models. Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016. Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016. https://doi.org/10.3384/ecp17142503

Recognizing steel plate side edge shape automatically using classification and regression models

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Author: Siirtola, Pekka1; Tamminen, Satu1; Ferreira, Eija1;
Organizations: 1Biomimetics and Intelligent Systems Group, P.O. BOX 4500, FI-90014, University of Oulu, Oulu, Finland
2SSAB Europe, Raahe plate mill, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202003107725
Language: English
Published: Linköping University Electronic Press, 2018
Publish Date: 2020-03-10
Description:

Abstract

In the steel plate production process it is important to minimize the wastage piece produced when cutting a mother steel plate to the size ordered by a customer. In this study, we build classi?cation and regression models to recognize the steel plate side edge shape, if it is curved or not and the amount of curvature. This is done based on time series data collected at the manufacturing line. In addition, this information needs to be presented in a way that enables fast analysis and long-term statistical monitoring. It can then be used to tune the parameters of the manufacturing process so that optimal curvature can be found and the size of the wastage piece can be reduced. The results show that using the classi?cation and linear regression methods, the side edge shape can be recognized reliably and the amount of curvature can be estimated with high accuracy as well.

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Series: Linköping electronic conference proceedings
ISSN: 1650-3686
ISSN-E: 1650-3740
ISSN-L: 1650-3686
ISBN Print: 978-91-7685-399-3
Pages: 503 - 510
DOI: 10.3384/ecp17142503
OADOI: https://oadoi.org/10.3384/ecp17142503
Host publication: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Conference: EUROSIM
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © The Authors 2018.