Optimisation of the MgO/Al 2 O 3 ratio of high-alumina BF slag based on MOPSO algorithm

Abstract

To 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.