CELSA to try out machine learning software for enhancing steel production processes
Fero Labs is going to employ its so-called white-box machine learning algorithms at CELSA Nordic’s steel plant in Mo i Rana, Norway
CELSA Nordic, a leading producer of reinforcing steel and wire rod in Europe, has entered into an agreement with Fero Labs, developers and providers of factory optimization software, to evaluate the program’s performance in enhancing steel production processes and optimizing material use.
New technological options
After an initial application phase, Fero Labs is going to employ its so-called white-box machine learning algorithms at CELSA Nordic’s steel plant in Mo i Rana, Norway, on a broader base. Against the backdrop of rising raw material and alloy costs, increasing supply chain difficulties around the globe and the urge to make steelmaking processes more sustainable, producers are increasingly looking for new technological options.
Optimized costs and use of resources through process optimization
CELSA Ameringsstal AS, operator of the steelmaking and rolling facilities in Mo i Rana, is the leading producer of reinforcing steel – straight rebar, bar in coils (BIC) and wire rod – in the Nordics. The Fero Labs software will be used to analyze each batch of steel being processed in the meltshop and make recommendations as to the optimum quantities of alloying agents to be added to achieve the specified steel grade. The steelmaker expects improvements in yield, optimized energy consumption and minimized occurrence of defects from the deployment of the software program. “This implementation will significantly enhance our operations, and if it delivers on expectations, we can implement it in our sister mills across Europe,” says Utku Öner, CEO of CELSA Nordic.