Saving Energy by the Application of Artificial Intelligence to the Hot Metal Ladle Logistics

One of the biggest challenges of the steel industry is maintaining the correct temperature of the hot metal. The scheduling of hot metal ladles plays a vital role in minimizing heat losses and maximizing scrap utilization in the converter. This study presents an AI-based approach to support decision-making of hot metal ladles, considering key input parameters such as the ladles' thermal state and location, the refractories' thickness, and crane availability. Integrating sophisticated AI algorithms in such a decision support system ensures the evaluation of energy favorable scenarios, thereby minimizing hot metal temperature losses and maximizing scrap utilization and ladle availability.

Maria Gabriela Garcia Campos | Tata Steel Nederland
 

Bruno Luchini | Tata Steel Netherlands
 

Paul van der Beurden | Tata Steel Netherlands
 

Sido Sinnema | Tata Steel Netherlands