Xiangtan Iron and Steel Group

Temperature prediction in laminar cooling has significant value in the steelmaking process. Accurate temperature prediction helps optimize the phase transition process, thereby improving the hardness, toughness, and strength of the steel to meet different application requirements. Reasonable temperature prediction can improve energy efficiency, reduce unnecessary energy consumption, and lower production costs. Finally, by reducing temperature fluctuations during the cooling process, product defects and stress concentrations can be minimized, enhancing the reliability and qualification rate of the finished products.

The Pangu prediction model improves the hit rate of temperature predictions by more than 15% compared to the customer’s own model, replacing manual predictions and automatically selecting corresponding cooling parameters in conjunction with the optimized model.