Smart system for calculating feedstock in electric steelmaking
Metallics Optimizer uses artificial intelligence techniques to forecast the amount of undesired tramp elements in the scrap before it is melted. The Metallics Optimizer uses this forecast to calculate the lowest-cost composition for the melt's feedstock utilizing optimization algorithms.
Customer challenges addressed
- Lack of knowledge of the chemical composition of the scrap means a large amount of expensive raw materials is used.
- Low-cost scrap with unwanted tramp elements puts product quality at risk.
- The costs of producing the melt are not transparent.