Prediction Model of Converter Oxygen Consumption Based on Recursive Classification and Feature Selection

Liu, Zhang; Zheng, Zedong; Kaitian, Zhang; Xinyue, Shen; Wang, Yongzhou

doi:10.1007/978-3-030-65257-9_10

The Minerals, Metals &Amp; Materials Series

2021

DOI: 10.1007/978-3-030-65257-9_10

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Prediction Model of Converter Oxygen Consumption Based on Recursive Classification and Feature Selection

Zhang Liu

Zedong Zheng

Zhang Kaitian

et al.

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Toward learning steelmaking—A review on machine learning for basic oxygen furnace process

Ghalati,

Zhang,

El‐Fallah

et al. 2023

Materials Genome Engineering Advances

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Basic oxygen furnace (BOF) steelmaking is the most widely used process in global steel production today, accounting for around 70% of the industry's output. Due to the physical, mechanical, and chemical complexities involved in the process, conventional monitoring and control methods are often pushed to their limits. The increasing global competition has created a demand for new methods to monitor and control the BOF steelmaking process. Over the past decade, Machine Learning (ML) techniques have garnered substantial attention, offering a promising pathway to enhance efficiency and suitability of steel production. This paper presents the first comprehensive review of ML applications in the BOF steelmaking process. We provide an introduction to both fields: an overview of the BOF steelmaking process and ML. We analyze the existing work on ML applications in BOF steelmaking and synthesize common concepts into categories, supporting the identification of common use cases and approaches. This analysis concludes with the elaboration of challenges, potential solutions, and a future outlook for further research directions.

show abstract

Toward learning steelmaking—A review on machine learning for basic oxygen furnace process

Ghalati,

Zhang,

El‐Fallah

et al. 2023

Materials Genome Engineering Advances

View full text Add to dashboard Cite

show abstract

ASU model with multiple adjustment types for oxygen scheduling concerning pipe pressure safety in steel enterprises

et al. 2023

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Prediction Model of Converter Oxygen Consumption Based on Recursive Classification and Feature Selection

Cited by 2 publications

References 8 publications

Toward learning steelmaking—A review on machine learning for basic oxygen furnace process

Toward learning steelmaking—A review on machine learning for basic oxygen furnace process

ASU model with multiple adjustment types for oxygen scheduling concerning pipe pressure safety in steel enterprises

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