{"title":"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","authors":"Yu. S. Toroptseva, A. V. Kuznetsov, A. L. Kotikov","doi":"10.1007/s11015-024-01761-y","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":702,"journal":{"name":"Metallurgist","volume":"68 4","pages":"582 - 587"},"PeriodicalIF":0.8000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\",\"doi\":\"10.1007/s11015-024-01761-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":702,\"journal\":{\"name\":\"Metallurgist\",\"volume\":\"68 4\",\"pages\":\"582 - 587\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metallurgist\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11015-024-01761-y\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"METALLURGY & METALLURGICAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metallurgist","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s11015-024-01761-y","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METALLURGY & METALLURGICAL ENGINEERING","Score":null,"Total":0}
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.
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).
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