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Proceedings of the 5th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2014) pp 215–218Cite as

Application on Determination of Key Factors of Hot Metal Silicon Content Based on Multivariate Statistics

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Abstract

This paper use multivariate statistics to analyze and research the influencing factors of the hot metal silicon content, and apply principal component analysis to determine the key factors. According to blast furnace refining mechanism and production practice, determine 16 relevant operating parameters of hot metal silicon content, set up matrix and model, get the contribution rate of each variable to the principal, find out six key factors and use T2 statistics monitor hot metal silicon content changes in the actual production situation.

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Acknowledgments

The authors gratefully acknowledge the financial support of the national natural science foundation, China (No.70932004) and the sixth innovation practice program of Shanghai (IAP6022).

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China

    Wen-wen Liu, Rui Miao, Bing-yu Tang & Qiang Zhang

  2. Shanxi Taigang Stainless Steel CO., LTD, 2Jiancaoping Street, Taiyuan, 030003, China

    Wen-wen Liu

Authors
  1. Wen-wen Liu
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  2. Rui Miao
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  3. Bing-yu Tang
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  4. Qiang Zhang
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Corresponding author

Correspondence to Wen-wen Liu .

Editor information

Editors and Affiliations

  1. Tianjin, China

    Ershi Qi

  2. Xi'an Jiaotong University, China, Xi'an, China

    Qin Su

  3. Industrial Engineering Institution of CM, Tianjin, China

    Jiang Shen

  4. Xi'an Jiaotong University, China, Xi'an, China

    Feng Wu

  5. Tianjin University, China, Tianjin, China

    Runliang Dou

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Liu, Ww., Miao, R., Tang, By., Zhang, Q. (2015). Application on Determination of Key Factors of Hot Metal Silicon Content Based on Multivariate Statistics. In: Qi, E., Su, Q., Shen, J., Wu, F., Dou, R. (eds) Proceedings of the 5th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2014). Proceedings of the International Asia Conference on Industrial Engineering and Management Innovation, vol 1. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-100-0_40

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