Abstract
ABSTRACTTo reduce the content of MgO in the slag, which helps in lowering production costs, the chemical components of a SiO2–CaO–MgO–Al2O3–TiO2 blast furnace (BF) slag system with high Al2O3 content were optimised using the multi-objective particle swarm optimisation (MOPSO) algorithm. First, models for predicting the metallurgical properties of BF slag were established and verified, based on mixture experimental designs and the ion and molecule coexistence theory. Second, the problem was solved by MOPSO using the MATLAB software package. Optimisation results show that the appropriate content of MgO in the slag should be 4–7%, and the MgO/Al2O3 ratio should be 0.2–0.6. Finally, optimised solutions were used in the 3200 m3 BF of a steel company in China. MgO in the slag was reduced to less than 5%, the MgO/Al2O3 ratio was controlled at 0.3–0.4, and the fuel ratio remained at 515 kg t−1.
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