Optimal batching plan of deoxidation alloying based on principal component analysis and linear programming

Zinan Zhao (Telephone of North China University of Technology: 18001435933)
Shijie Li (Telephone of North China University of Technology: 18001435933)
Shuaikang Li (Telephone of North China University of Technology: 18001435933)

Abstract


As the market competition of steel mills is severe, deoxidization alloying is an important link in the metallurgical process. To solve this problem, principal component regression analysis is adopted to reduce the dimension of influencing factors, and a reasonable and reliable prediction model of element yield is established. Based on the constraint conditions such as target cost function constraint, yield constraint and non-negative constraint, linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements. The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills, which is of positive significance for improving the market competitiveness of steel mills, reducing waste discharge and protecting the environment.


Keywords


deoxidization alloying; principal component regression analysis; linear programming; optimization of dosing scheme

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References


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DOI: https://doi.org/10.30564/jmer.v3i2.1903

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