We're excited to announce our partnership with CELSA Nordic, part of Celsa Group, a leading European manufacturer of circular and low-emission steel. In a pilot program with the group's Norway plant, Fero's white-box machine learning algorithms demonstrated the ability to reduce emissions and costs by making production more efficient.
From the press release:
For steel and iron, which comprise 95% of metal tonnage produced annually around the world, raw material and alloy costs are a constant challenge. As prices continue to surge due to the global supply chain crisis, steelmakers are turning to technology for answers.
"We are always looking at how to improve our production processes to be more sustainable, to lower costs, and to be more competitive in an international market," said Utku Öner, CEO of CELSA Nordic. "Fero helps us tackle these goals at the same time. This implementation will significantly enhance our operations, and if it delivers on expectations, we can implement it in our sister mills across Europe."
CELSA Nordic adds alloys to their steel to make sure their rebar products meet the quality standards in the Nordic market. Fero Labs' software analyzes each batch while it's still in the melt shop and recommends the optimal amount of alloys to add, reducing waste and costs. Other use cases intended to be explored during deployment include improving yield, optimizing energy consumption, and minimizing defects.
"The steel industry is continuing to grow immensely and we're happy to help manufacturers such as CELSA Nordic take on challenges that come with producing steel," said Berk Birand, co-founder and CEO of Fero Labs. "With rising raw material costs, lower demand, and the need to downsize workforces to maintain profitability, it is imperative that plant operators are equipped to quickly identify solutions for production issues while operating at peak performance at all times."