Metallurgical companies are actively investing in AI-based solutions. Forecasts for metal product demand and ferroalloys costs make it possible to create a purchasing campaign; an operational planning system - to construct a production schedule, optimize intra-workshop logistics, and adjust shift tasks; and models for optimal purging and metal release temperatures in an EAF (Electric arc furnace) or a BOF (Basic oxygen furnace) provide energy savings and improve finished product quality. Implementing these solutions - as part of the situational-analytical center - results in improved product quality while reducing costs.

Our solutions

Purge process optimization

The lag or absence of measuring devices leads to purging being performed with a margin. The steel bath’s peroxidation increases metal waste, excessive deoxidizer consumption, and ferroalloy losses. When smelting high-carbon steel grades, craftsmen often prefer to blow the steel bath off 'to zero'. This leads to significant overspending in ferroalloys at the ladle furnace stage. The SBDA solution monitors the state of the steel bath (weight, chemical composition, metal and slag temperatures, and waste gases) in the steelmaking unit (EAF, BOF converter) during smelting. A system based on artificial intelligence and a rigorous thermodynamic model guides the steelmaker with prompts to reduce the oxygen-lancing time, metal waste, steel bath over-oxidation, and overspending ferroalloys.

Reduced consumption
of oxygen, deoxidizers, and ferroalloys
$3 M
in savings per year
with 1 million tons production
Reduced metal waste
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Ferroalloy calculator

Ferroalloys consumption rates approved by the Technical Directorate are not usually tied to market price. The steelmaker does not calculate the cost of materials for alloy additions. Optimal combination calculations and ferroalloy amounts reduce costs and ensure the target chemical composition. SBDA ferroalloy calculator solves the combinatorial problem by selecting the optimal charge from a cost price point of view to accurately calculate the mass of each element, taking equipment characteristics into account. The system allows you to “expand” boundaries of operational responsibility area “Purchaser” – “Technologist” – “Master steelmaker” and to respond to changes in market conditions during the production process.

ferroalloys costs
consumption in malleable discharge compared to technological standards
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Improving the quality of finished products: predicting mechanical properties

Accurately following a processing technique suitable for average chemistry values ​​does not guarantee falling within the target mechanical property parameters. The volume of non-conforming products in rolled metal is between 0.15% and 2%. “Dips” in mechanical properties are avoided by the AI-based SBDA system. The system predicts mechanical properties based on actual chemical composition and given process parameters. If the forecast of mechanical properties deviates from the target corridors, the system recommends changes in the rolling/heat treatment machinery operating modes

average absolute error reduction
in mechanical properties prediction compared to linear models
$1.5 M
combined savings per year
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