Fero Labs and Gerdau have been honored with the coveted best innovation award for a machine-learning technical paper at the AISTech Expo in Ohio.
The award-winning technical paper, titled "Adopting Machine Learning Based Workflows for Reducing Production Risk and Cost," demonstrates how Gerdau achieved significant operational efficiencies and cost savings with an average saving of $3 per ton on alloy costs, by implementing Fero Labs’ cutting-edge machine learning software.
"The significance of this technical paper is that it showcases not just a ‘moment in time’ pilot", said co-author Pamir Ozbay (Fero Labs), "but a successful, multi-year deployment of an AI solution in industrial steel production, setting a benchmark in an industry still exploring pilot implementations."
The paper outlines that the success of the Fero Labs/Gerdau partnership goes beyond mere application of technology; it involves substantial change management to integrate AI into everyday workflows effectively.
The paper outlines the necessity of involving operations teams from the start, simplifying user interfaces for ease of use, and providing clear insights into the model's reliability through confidence bands and explainability. This approach ensures that teams are not just receiving blind predictions and recommendations, but also understanding the accuracy of these insights, fostering trust and adoption of the technology.
Readers of the paper will understand how strategic AI implementation and comprehensive change management led to significant financial gains, potentially saving millions in operational costs.
The Digitalization Applications Best Paper Award was presented today at the Digitalization Applications Technology Committee meeting held during AISTech in Ohio, the largest Iron and Steel Expo in North America. The award was presented to its authors, Pamir Ozbay of Fero Labs and Carter Almquist of Gerdau.
Download the technical paper, or speak with an industrial AI expert at Fero Labs.
