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Consideration of green intelligent steel processes and narrow window stability control technology on steel quality

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Abstract

In order to promote the intelligent transformation and upgrading of the steel industry, intelligent technology features based on the current situation and challenges of the steel industry are discussed in this paper. Based on both domestic and global research, functional analysis, reasonable positioning, and process optimization of each aspect of steel making are expounded. The current state of molten steel quality and implementation under narrow window control is analyzed. A method for maintaining stability in the narrow window control technology of steel quality is proposed, controlled by factors including composition, temperature, time, cleanliness, and consumption (raw material). Important guidance is provided for the future development of a green and intelligent steel manufacturing process.

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References

  1. R.Y. Yin, A discussion on “smart” steel plant—View from physical system side, Iron Steel, 52(2017), No. 6, p. 1.

    Google Scholar 

  2. J. Zhou, Intelligent manufacturing-main direction of “Made in China 2025”, Chin. Mech. Eng., 26(2015), No. 17, p. 2273.

    Google Scholar 

  3. R.Y. Yin, “Flow”, flow network and dissipative structure—Understanding of the physical system of manufacturing process of process manufacturing type, Sci. Sin. Technol., 48(2018), No. 2, p. 136.

    Article  Google Scholar 

  4. Y.G. Sun, Development road map of digital. network and intelligent manufacturing technology of iron and steel industry, China Steel Focus, 2015, No. 9, p. 4.

  5. Q.S. Yuan, R.Y. Yin, X.H. Cao, and, P.C. Liu, Strategic research on the goals characteristics and paths of intelligentization of process manufacturing industry for 2035, Strategic Study CAE, 22(2020), No. 3, p. 148.

    Google Scholar 

  6. R.Y. Yin, Process engineering and manufacturing process, Iron Steel, 49(2014), No. 7, p. 15.

    Article  Google Scholar 

  7. C.C. Qi, Big data management in the mining industry, Int. J. Miner. Metall. Mater., 27(2020), No. 2, p. 131.

    Article  Google Scholar 

  8. Y.G. Sun, H.Y. Xu, Y.J. Zeng, and W.B. Li, Energy flow information model based dynamic multi-type energy scheduling in steel works, [in] Baosteel BAC, Shanghai, 2013, p. 266.

  9. R. Zhu, X.T. Wu, G.S. Wei, and B.H. Tian, Development of green and intelligent technologies in electric arc furnace steelmaking process, Iron Steel, 54(2019), No. 8, p. 9.

    Google Scholar 

  10. J.H. Liu and H. Dong, Thoughts on continuous optimization of special steel production process, Chin. Metall., 28(2018), No. 9, p. 1.

    Google Scholar 

  11. L.B. Yang, J.Q. Zeng, Y. Deng, X.W. Xu, and L.P. Wu, Highly efficiency and long-life combined blowing technology of big converter, Iron Steel, 55(2020), No. 4, p. 45.

    Google Scholar 

  12. R.Y. Yin, Integrated Technology of the platform for clean steel production-an important direction of the technology progress in steelmaking, Iron Steel, 44(2009), No. 7, p. 1.

    Google Scholar 

  13. R.Y. Yin, Integration technology of high efficiency and low cost clean steel “prodoction platform” and its dynamic operation, Iron Steel, 47(2012), No. 1, p. 1.

    Google Scholar 

  14. X.L. Pan, Z. Li, Y.H. Wang, and H.Z. Liang, Advanced technology of clean steel production at home and abroad, Steelmaking, 23(2007), No. 1, p. 59.

    CAS  Google Scholar 

  15. X.C. Li, C.T. Shi, and F. Zhao, Industry 4.0 meets with China iron and steel industry, Iron Steel, 50(2015), No. 11, p. 1.

    Google Scholar 

  16. C.H. Guo, Iron and steel industry and industry 4.0, Metall. Ind. Autom., 39(2015), No. 4, p. 7.

    Google Scholar 

  17. W.Z. Liu, Thinking on the intelligent manufacturing of steel industry in China, Metall. Ind. Autom., 42(2018), No. 4, p. 1.

    Google Scholar 

  18. W.Z. Liu, Current situation and thinking of intelligent manufacturing in China’s iron and steel industry, Chin. Metall., 30(2020), No. 6, p. 1.

    Google Scholar 

  19. Y. Yu, Information architecture design of hesteel tangsteel industry for intelligent manufacturing, Iron Steel, 52(2017), No. 1, p. 1.

    CAS  Google Scholar 

  20. H.F. Hu, Development and outlook of intelligent manufacturing technology in steel industry, Baosteel Meishan, 2014, No. 6, p. 1.

  21. K. Ohara, M. Tsugeno, Y. Sakiyama, K. Kitaqoh, J. Yanaqimoto, and H. Imanari, Process optimization for the manufacturing of sheets with estimated balance between product quality and energy consumption, CIRP Ann.-Manuf. Technol., 63(2014), No. 1, p. 257.

    Article  Google Scholar 

  22. E. Toshihiko, Optimizing steelmaking system for quality steel mass production for sustainable future of steel industry, Steel Res. Int., 85(2014), No. 8, p. 1274.

    Article  CAS  Google Scholar 

  23. H.N. Zhang and S.Q. LI, Consideration about intelligent manufacturing of HBIS Shijiazhuang Iron and Steel Co., Chin. Metall., 26(2016), No. 6, p. 1.

    Google Scholar 

  24. R.Y. Yin, Metallurgical Process Engineering, 2nd ed., Metallurgical Industry Press, Beijing, 2009.

    Google Scholar 

  25. R.Y. Yin, Theory and Method of Metallurgical Process Integration, Metallurgical Industry Press, Beijing, 2013.

    Google Scholar 

  26. R.Y. Yin, Theory and Methods of Metallurgical Process Integration, Metallurgical Industry Press, Beijing, 2016.

    Google Scholar 

  27. R.Y. Yin, Comment on behavior of energy flow and construction of energy flow network for steel manufacturing process, Iron Steel, 45(2010), No. 4, p. 1.

    Google Scholar 

  28. S. Kawasaki, H. Hirahashi, M. Aoki, K. Hajika, and Y. Hunaoka, Improvement of the refining process around combined blowing converter in kobe works, Tetsu-to-Hagané, 76(1990), No. 11, p. 1900.

    Article  CAS  Google Scholar 

  29. O. Yamase, M. Ikeda, J. Fukumi, C. Taki, K. Yamada, and K. Iwasaki, Industrialization of a new steelmaking process utilizing hot metal pretreatment and smelting reduction, Tetsu-to-Hagané, 74(1988), No. 2, p. 270.

    Article  CAS  Google Scholar 

  30. E. Toshihiko, Steelmaking technology for the last 100 years: toward highly efficient mass production systems for high quality steels, ISIJ Int., 55(2015), No. 1, p. 36.

    Article  CAS  Google Scholar 

  31. J.H. Liu, H. Cui, and Y.P. Bao, Key technologies for high grade pipeline refining, J. Univ. Sci. Technol. Beijing, 31(2009), No. S1, p. 1.

    Google Scholar 

  32. Y. Fan, S.L. Li, X.C. Miao, G. Wang, and X.G. Ai, Application status and prospect of narrow window control and big data in direct rolling, Chin. Metall., 28(2018), No. 9, p. 8.

    Google Scholar 

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Acknowledgements

This work was financially supported by the National Key R&D Program of China (No. 2017YFB0304000), and the National Natural Science Foundation of China (Nos. 52074093, 51874102, 51704080, and 51674092).

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Correspondence to Lu Lin.

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Lin, L., Zeng, Jq. Consideration of green intelligent steel processes and narrow window stability control technology on steel quality. Int J Miner Metall Mater 28, 1264–1273 (2021). https://doi.org/10.1007/s12613-020-2246-2

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  • DOI: https://doi.org/10.1007/s12613-020-2246-2

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