Artificial Neural Network Predictive System for Oxygen Steelmaking Converter

Abstract

The main objective of the paper is the presentation of the static control model of steelmaking converter process based on the artificial neural network approach. The results of classical mass and energy balance as well as regression models are also presented. The developed artificial neural network predicts the temperature of the liquid metal and the volume of necessary oxygen blow. The ANN was trained and tested with the real industrial data measured in one of the Polish steel plants. The comparison of the ANN results with the classical calculations is presented.