Abstract
In order to maximise the reduction of pig iron cost in an ironmaking process, and at the same time ensure the output and quality of the pig iron, a design and optimisation system for the charging ingredients and structure in an ironmaking system was established using metallurgical theory. The system includes six modules, namely, sinter metallurgical performance testing and analysis, sintering burdening design, sinter component and property prediction, blast furnace burdening design, blast furnace batching calculation and ironmaking system burden optimisation. Based on actual production, testing and material balance theory, the system integrated these modules on VB and MATLAB using a series of intelligent algorithms, such as the BP neural network, multiple objective linear programming, genetic algorithms and so on. As a result, the optimum burden composition and structure of the sinter and blast furnace that satisfied all the constraint conditions could be obtained. Standing as a pinnacle of the global ironmaking production, the system can design and optimise not only the sintering burden, but also the blast furnace burden. Compared with the traditional production testing and hand calculation in the ironmaking system, the project can greatly reduce the production risk and greatly increase the calculation accuracy. Industrial application shows that the system is especially beneficial to reduce the ironmaking cost and at the same time ensure the output and quality.
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