MODEL FOR OPTIMAL CONTROL OF CHARGE LOADING PARAMETERS OF METAL-REDUCING PLANTS

Abstract

Purpose. The study’s main objective is to consider two main factors simultaneously when optimizing the blast furnace loading process. The first is to maximize the potential use of gases in the blast furnace’s “dry zone”, which increases the efficiency of the ore recovery process. The second is to increase the melting productivity by optimizing the temperature regimes and uniform distribution of the charge over the furnace space, which ensures the stability of the furnace. Achieving a balance between these factors is critical to improving the overall efficiency of blast furnace production. Methodology. The study used regression analysis to investigate the quantitative dependencies between the utilization degree of reducing gases and the efficiency of blast furnace melting. Evaluation of the results allowed us to create a predictive model to determine the main characteristics of the process. Findings. The research results allowed us to create a predictive model to determine the main characteristics of the process. The analysis was carried out based on experimental data obtained from industrial blast furnaces, considering different modes of loading and distribution of raw materials. Originality. The developed model is a new approach to optimizing control influences on blast furnace loading, considering the dynamic change in ore load. This allows including current changes in technological parameters and promptly adjust the smelting process. This approach improves the process’s technical and economic performance and effectively predicts further development. Practical value. The proposed methodology for controlling the loading process provides more accurate control over reducing gases use and the effectiveness of their impact on the ore. That leads to a decrease in fuel losses, a reduction in the environmental burden, and an increase in the overall productivity of the blast furnace by optimizing gas-dynamic processes.