Abstract
In this paper, an optimisation system for charging composition and structure in the sintering process was established in order to reduce the sinter cost in the ironmaking process. The system comprised four modules: sinter metallurgical performance testing and analysis, sintering burdening design and optimisation, sintering matching calculation, and sinter component and property prediction. The data for the first module came from actual production values of a steelworks and from testing in the laboratory. Based on material balance theory, the second module used a linear programming method to optimise sinter cost, quality and quantity. The third module was built to predict the sintering production data. The fourth module can be used to predict some composition and properties of the sinter based on a Back-Propagation neural network. The system integrated all of these modules using Visual Basic and MATLAB. As the result, the optimum charging composition and structure of sinter which satisfies all constraint conditions can be obtained. Compared with traditional production testing and hand calculation in the sintering process the system can reduce the sinter cost and greatly decrease the production risk. Industrial application proves that the system is very useful and efficient in reducing sinter cost while ensuring output quantity and quality.
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