{"id":2903,"date":"2026-06-23T10:51:06","date_gmt":"2026-06-23T10:51:06","guid":{"rendered":"https:\/\/artelnics.com\/case_studies\/celsa-rolling-furnace-digital-twin\/"},"modified":"2026-08-21T20:20:22","modified_gmt":"2026-08-21T20:20:22","slug":"celsa-rolling-furnace-digital-twin","status":"publish","type":"case_studies","link":"https:\/\/artelnics.com\/case_studies\/celsa-rolling-furnace-digital-twin\/","title":{"rendered":"Building a digital twin of a rolling furnace"},"content":{"rendered":"
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A digital twin models furnace behavior to understand billet temperature, gas consumption and process optimization opportunities.<\/p>\n

\n Steel manufacturing<\/span>
\n Digital twin<\/span>
\n Process optimization<\/span>\n <\/div>\n

Challenge<\/h2>\n

Continuous rolling furnaces involve high temperatures, several zones and moving billets. Operators need to understand how process settings affect billet temperature and energy consumption.<\/p>\n

Data<\/h2>\n

The model used furnace-zone temperatures, gas-flow information, billet properties, speed and process geometry, combining physical knowledge with measured plant data.<\/p>\n

Solution<\/h2>\n

Artelnics developed a digital twin based on differential-equation models and data validation, comparing modeling approaches and relating furnace settings to process behavior.<\/p>\n

\n
Core model<\/strong><\/p>\n

Temperature evolution of billets across furnace zones.<\/p>\n<\/div>\n

Optimization lever<\/strong><\/p>\n

Gas flow, zone temperature and speed settings.<\/p>\n<\/div>\n<\/div>\n

Results<\/h2>\n

The digital twin gives engineers a practical tool to study furnace operation, evaluate scenarios and identify opportunities to reduce energy use while preserving product quality.<\/p>\n

Illustrations<\/h2>\n
\"Temperature
Furnace temperature comparison<\/figcaption><\/figure>\n
\"Gas
Gas flow and temperature<\/figcaption><\/figure>\n<\/article>\n