Initial Results on Hyperspectral Characterization of Steel Scrap

The main focus of this project is to address the challenge of identifying impurities and foreign substances in recycled steel scrap. To tackle this issue, a combination of hyperspectral analysis and artificial intelligence is employed, specifically using imaging in the short-wavelength (SWIR) infrared range. By accurately determining the composition of the scrap, this approach enables more precise utilization of additives and optimization of the production process in terms of energy consumption.