A slag prediction model in an electric arc furnace process for special steel production

In the steel industry, there are some parameters that difficult to measure online due technical difficulties. these scenarios, soft-sensors, which tools aim forecasting of certain variables, play an indispensable role for quality control. this investigation, different soft sensors developed address problem predicting slag quantity and composition in electric arc furnace process. The results provide evidence models perform better simulated data than real data. They also reveal higher accuracy measured slag.