AISTech 2022

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Energy Savings and Quality Reliability by Superheat Control Prediction to the Continuous Casting Through Machine Learning (Room 315)

The electric arc furnace and the ladle furnace in the steel industry have high energy consumption due to melting the scrap and processing it to make steel. Nevertheless, the temperature decreases due to several transfers and time elapsed between the processes. Consequently, it is necessary to superheat the steel to guarantee an adequate temperature at the end of the process. For these reasons, a machine learning model was developed to estimate the superheat necessary to the molten steel at the continuous casting. This artificial intelligence model has several benefits such as energy consumption saving, refractory performance and steel quality improvement.