Analysis of the Steelmaking Process via Data Mining and Pearson Correlation

Author:

Carrasco-López Susana1,Herrera-Trejo Martín1,Castro-Román Manuel1ORCID,Castro-Uresti Fabián2,Castro-Cedeño Edgar Iván1ORCID

Affiliation:

1. Centro de Investigación y de Estudios Avanzados, CINVESTAV Saltillo, Av. Industria Metalúrgica No. 1062, Parque Industrial Saltillo-Ramos Arizpe, Ramos Arizpe 25900, Coahuila, Mexico

2. Ternium México, San Nicolás de los Garza 66450, Nuevo León, Mexico

Abstract

The continuous improvement of the steelmaking process is a critical issue for steelmakers. In the production of Ca-treated Al-killed steel, the Ca and S contents are controlled for successful inclusion modification treatment. In this study, a machine learning technique was used to build a decision tree classifier and thus identify the process variables that most influence the desired Ca and S contents at the end of ladle furnace refining. The attribute of the root node of the decision tree was correlated with process variables via the Pearson formalism. Thus, the attribute of the root node corresponded to the sulfur distribution coefficient at the end of the refining process, and its value allowed for the discrimination of satisfactory heats from unsatisfactory heats. The variables with higher correlation with the sulfur distribution coefficient were the content of sulfur in both steel and slag at the end of the refining process, as well as the Si content at that stage of the process. As secondary variables, the Si content and the basicity of the slag at the end of the refining process were correlated with the S content in the steel and slag, respectively, at that stage. The analysis showed that the conditions of steel and slag at the beginning of the refining process and the efficient S removal during the refining process are crucial for reaching desired Ca and S contents.

Publisher

MDPI AG

Reference17 articles.

1. Modification of non-metallic inclusions in steel by calcium treatment: A Review;Ren;ISIJ Int.,2023

2. Gatellier, C., Gaye, H., and Nadif, M. (1988). International Calcium Treatment Symposium, University of Strathclyde.

3. Optimization of ladle slag composition by application of sulphide capacity model;Andersson;Ironmak. Steelmak.,2000

4. Evaluation of calcium treatment on oxide and sulfide inclusions through modification indexes;Miao;Metall. Mater. Trans. B,2022

5. Analysis of predictors for modification of alumina inclusions in medium carbon steel;Junca;J. Mater. Res. Technol.,2021

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3