利用机器学习方法改进镀锌轧辊生产技术：新利佩茨克钢铁公司（NLMK）连续热浸镀锌装置（CHGU-1）案例研究

IF 0.8 4区材料科学 Q4 METALLURGY & METALLURGICAL ENGINEERING

Metallurgist Pub Date : 2024-08-13 DOI:10.1007/s11015-024-01761-y

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

引用次数: 0

摘要

本文介绍了新利佩茨克钢铁公司（NLMK）镀锌金属生产的现有技术和相关挑战。并提出了利用机器学习工具改进工艺的可行方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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)

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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)

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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来源期刊

Metallurgist 工程技术-冶金工程

CiteScore

1.50

自引率

44.40%

发文量

151

审稿时长

4-8 weeks

期刊介绍： Metallurgist is the leading Russian journal in metallurgy. Publication started in 1956. Basic topics covered include: State of the art and development of enterprises in ferrous and nonferrous metallurgy and mining; Metallurgy of ferrous, nonferrous, rare, and precious metals; Metallurgical equipment; Automation and control; Protection of labor; Protection of the environment; Resources and energy saving; Quality and certification; History of metallurgy; Inventions (patents).