Browsing by Keyword "Secondary metallurgy process optimization"
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Item Ladle furnace slag characterization through hyperspectral reflectance regression model for secondary metallurgy process optimization(2017-11-13) Picon, Artzai; Vicente Rojo, Asier; Rodriguez-Vaamonde, Sergio; Armentia, Jorge; Arteche, Jose Antonio; Macaya, Inaki; Vicente, Asier; Tecnalia Research & Innovation; COMPUTER_VISION; INDUSTRY_THINGSIn steelmaking process, close control of slag evolution is as important as control of steel composition. However, there are no industrially consolidated techniques that allow in-situ analysis of the slag chemical composition, as in the case of steel with OES-spectrometers. In this work, a method to analyze spectral reflectance of ladle furnace slag samples to estimate their composition is proposed. This method does not require sample preprocessing and is based on a regression algorithm that mathematically maps the spectral reflectance of the slag with its actual composition with errors lower than 10%. Specifically designed normalization and calibration steps have been proposed to allow a global model training with data from different locations. This allows real-time monitoring of the thermodynamical state of the steel process by feeding a thermodynamic equilibrium optimization model. The system has been validated on several ArcelorMittal locations achieving process savings of 0.71 Euro per liquid steel tons.