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Metallurgist

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13-08-2024

Improving the galvanized roll stock production technology by using machine learning methods: a case study of the novolipetsk steel (NLMK) continuous hot-dip galvanizing unit (CHGU-1)

Authors: Yu. S. Toroptseva, A. V. Kuznetsov, A. L. Kotikov

Published in: Metallurgist | Issue 4/2024

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Abstract

The paper describes the existing technologies and challenges associated with galvanized metal production at the Novolipetsk Steel (NLMK) plant. Possible ways to improve the process using machine-learning tools are proposed.

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Wang Y, Chen C, Wang J (2014) Temperature prediction in hot dip galvanizing using neural network models. J Mater Process Techn 214(10):2071–2079

Shen Y, Chen L, Yang Y, Li X (2019) A machine learning model for predicting the quality of hot-dip galvanized coating. J Mater Eng Perform: 2184–2191

Colla V et al (2020) A modular machine-learning-based approach to improve tensile properties uniformity along hot dip galvanized steel strips for automotive applications. Metals 10(7):923. https://doi.org/10.3390/met10070923CrossRef

Proskurkin YV, Popovich VA, Moroz AT (1988) Galvanization: handbook. Metallurgiya, Moscow

Nucor corporation. https://nucor.com/. Accessed 1 Oct 2023

https://newsroom.posco.com/en/poscos-smart-factory-introduces-artificial-intelligence/. Accessed 10 Oct 2023

Smith J (2022) Digital transformation in steel manufacturing: a case study of tata steel. Intern J Ind Eng: 78–92

Muntin AV, Zhikharev PY, Zinyagin AG, Braiko DA (2023) Artificial intelligence and machine learning in metallurgy. Part 1. Methods and algorithms. Metallurg 6:124–130CrossRef

Zhikharev PY, Muntin AV, Braiko DA, Kryuchkova MO (2023) Artificial intelligence and machine learning in metallurgy. Part 2. Application examples. Metallurg 10:99–111

Title: Improving the galvanized roll stock production technology by using machine learning methods: a case study of the novolipetsk steel (NLMK) continuous hot-dip galvanizing unit (CHGU-1)
Authors: Yu. S. Toroptseva
A. V. Kuznetsov
A. L. Kotikov
Publication date: 13-08-2024
Publisher: Springer US
Published in: Metallurgist / Issue 4/2024
Print ISSN: 0026-0894
Electronic ISSN: 1573-8892
DOI: https://doi.org/10.1007/s11015-024-01761-y

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