Optimal regulation algorithms and complex numerical simulations are utilized in contemporary production processes. High quality of products, minimum of scrap, and reduction of carbon footprint are current trends in industry processes including the continuous casting process of steel. The paper shows a utilization of the 3D transient solidification model and an original fuzzy regulator for the improvement of the surface slab quality in the continuous casting of a high-strength low-carbon steel. An optimal casting scenario was proposed based on the real casting measurement and statistical evaluation. The relationship between the temperature history of the slab surface and the number of surface defects was statistically evaluated. Based on statistical data, the fuzzy regulator and the solidification model were used to find an optimal cooling strategy as a function of the casting speed and of the casting temperature. Though results are demonstrated for a specific slab caster and for a specific grade of steel, the presented concept is general from its nature and it can be used for any caster or any grade of steel.Keywords: Continuous casting, fuzzy optimization, secondary cooling, steel quality
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