This paper presents the deployment and benefits of a comprehensive closed-loop process optimization system at Marcegaglia Sheffield, UK, covering Scrap Yard, Electric Arc Furnace (EAF), Argon Oxygen Decarburization (AOD), and Ladle Furnace (LF) operations.
The paper focusses on Scrap Yard and EAF as key stages, and discusses how advanced sensor systems in combination with closed loop control...
Reliable real-time knowledge of bath oxygen and carbon is a long-standing challenge in DRI-based Electric Arc Furnace (EAF) operation, directly impacting energy efficiency, decarburization control, and endpoint stability. This paper presents a novel hybrid physics-guided machine learning framework for continuous bath oxygen and carbon prediction, explicitly coupling metallurgical first...
EAF operations face critical variability challenges in scrap mix composition and quality that directly impact slag basicity control and alloy chemistry prediction. Traditional multivariate statistical approaches rely on reactive empirical adjustments where conventional analytical tools reach computational limits for real-time process optimization.
This study presents operational validation of...