Sheng-li Wu, Dauter Oliveira, Yu-ming Dai, and Jian Xu, Ore-blending optimization model for sintering process based on characteristics of iron ores, Int. J. Miner. Metall. Mater., 19(2012), No. 3, pp. 217-224. https://doi.org/10.1007/s12613-012-0541-2
Cite this article as:
Sheng-li Wu, Dauter Oliveira, Yu-ming Dai, and Jian Xu, Ore-blending optimization model for sintering process based on characteristics of iron ores, Int. J. Miner. Metall. Mater., 19(2012), No. 3, pp. 217-224. https://doi.org/10.1007/s12613-012-0541-2
Sheng-li Wu, Dauter Oliveira, Yu-ming Dai, and Jian Xu, Ore-blending optimization model for sintering process based on characteristics of iron ores, Int. J. Miner. Metall. Mater., 19(2012), No. 3, pp. 217-224. https://doi.org/10.1007/s12613-012-0541-2
Citation:
Sheng-li Wu, Dauter Oliveira, Yu-ming Dai, and Jian Xu, Ore-blending optimization model for sintering process based on characteristics of iron ores, Int. J. Miner. Metall. Mater., 19(2012), No. 3, pp. 217-224. https://doi.org/10.1007/s12613-012-0541-2
An ore-blending optimization model for the sintering process is an intelligent system that includes iron ore characteristics, expert knowledge and material balance. In the present work, 14 indices are proposed to represent chemical composition, granulating properties and high temperature properties of iron ores. After the relationships between iron ore characteristics and sintering performance are established, the "two-step" method and the simplex method are introduced to build the model by distinguishing the calculation of optimized blending proportion of iron ores from that of other sintering materials in order to improve calculation efficiency. The ore-blending optimization model, programmed by Access and Visual Basic, is applied to practical production in steel mills and the results prove that the present model can take advantage of the available iron ore resource with stable sinter yield and quality performance but at a lower cost.
An ore-blending optimization model for the sintering process is an intelligent system that includes iron ore characteristics, expert knowledge and material balance. In the present work, 14 indices are proposed to represent chemical composition, granulating properties and high temperature properties of iron ores. After the relationships between iron ore characteristics and sintering performance are established, the "two-step" method and the simplex method are introduced to build the model by distinguishing the calculation of optimized blending proportion of iron ores from that of other sintering materials in order to improve calculation efficiency. The ore-blending optimization model, programmed by Access and Visual Basic, is applied to practical production in steel mills and the results prove that the present model can take advantage of the available iron ore resource with stable sinter yield and quality performance but at a lower cost.