铸造技术2025，Vol.46Issue(10)：931-940,10.DOI:10.16410/j.issn1000-8365.2025.5077
机器学习在炼钢工业的深度应用:机遇与挑战
Deep Applications of Machine Learning in the Steelmaking Industry:Opportunities and Challenges
摘要
Abstract
With the rapid development of artificial intelligence,the application of machine learning algorithms in the steelmaking industry has become a research hotspot.This paper systematically explores the challenges and opportunities of intelligent models in complex industrial scenarios of short-process steelmaking,with a focus on analysing their current applications in key stages such as electric arc furnaces,refining,and continuous casting.An examination of typical scenarios in the steelmaking process elaborates on the role of machine learning in process optimization,anomaly detection,and autonomous decision-making.In response to the real-time and reliability demands of the steelmaking environment,this study proposes research directions for machine learning within intelligent manufacturing systems,including cutting-edge technologies such as multimodal sensing,causal reasoning,and digital twins.Finally,this study explores the challenges,potential solutions,and future application prospects of machine learning in deep integration with the short-process steelmaking industry.关键词
机器学习/短流程炼钢/质量预测/自主决策/基础模型Key words
machine learning/short-process steelmaking/quality prediction/autonomous decision/foundation models分类
机械工程引用本文复制引用
宗男夫,韩永德,杨军,王子铮,荆涛,Jean-Christophe GEBELIN..机器学习在炼钢工业的深度应用:机遇与挑战[J].铸造技术,2025,46(10):931-940,10.基金项目
国家重点研发计划重点专项(2017YFB1103700) （2017YFB1103700）
国家自然科学基金面上项目(52074162) （52074162）
