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<p>Under the background of global green manufacturing and industrial intelligent digitization, the iron and steel industry is standing at the key node of transformation and upgrading. In particular, the iron and steel industry is a process industry, and the blast furnace operation is a “black-box” process. The End-to-End (E2E) paradigm is used to realize the design paradigm of machine learning (ML) and deep learning (DL) that combines Operation Technology (OT) with Information Technology (IT) and uses IT to assist OT optimization, to realize the intelligent development of the blast furnace. This paper summarizes the research progress of ML and DL in the optimization of collaborative mechanism of blast furnace intelligent control technology. In addition, this paper also discusses the potential future development in this field, aiming at improving the efficiency of steel production and provide solutions for intelligent blast furnace research.</p>

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Research Progress of Machine Learning and Deep Learning Applications in the Context of Blast Furnace Intelligence

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • Ping-guo Jiang,
  • Meng-ting Tu,
  • Le-yu Liu,
  • Yi-bo Jiang,
  • Xiong-gang Lu

摘要

Under the background of global green manufacturing and industrial intelligent digitization, the iron and steel industry is standing at the key node of transformation and upgrading. In particular, the iron and steel industry is a process industry, and the blast furnace operation is a “black-box” process. The End-to-End (E2E) paradigm is used to realize the design paradigm of machine learning (ML) and deep learning (DL) that combines Operation Technology (OT) with Information Technology (IT) and uses IT to assist OT optimization, to realize the intelligent development of the blast furnace. This paper summarizes the research progress of ML and DL in the optimization of collaborative mechanism of blast furnace intelligent control technology. In addition, this paper also discusses the potential future development in this field, aiming at improving the efficiency of steel production and provide solutions for intelligent blast furnace research.