Fero Labs
Why Process Expertise Doesn’t Scale —And What Actually Changes That
Discover why process expertise doesn’t scale in steel plants and how explainable decision support changes that. This article explores the limitations of traditional analytics and in-house models, the importance of capturing engineering reasoning, and how consistent, explainable process decision frameworks help teams respond faster and make better choices as conditions change.
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Use case
How One Global Steel Producer Proved AI Value Quickly — Without Overcomplicating the Pilot
This article describes how a global steel producer evaluated Fero Labs’ explainable AI through a focused proof-of-concept pilot rather than a broad digital transformation. The pilot targeted a common steel mill challenge: manual machine learning model retraining that consumes hundreds of engineering hours each year. By validating model accuracy, enabling real-time retraining, and removing ongoing maintenance, Fero Labs helped the producer demonstrate clear ROI before expanding into additional use cases such as alloy optimization, defect diagnostics, mechanical property prediction, and process optimization. The post outlines a practical, repeatable approach for steel producers, manufacturers, and consultants seeking to deploy industrial AI, scale engineering expertise, improve efficiency, protect product quality, and support more sustainable steel production—without disrupting existing workflows.
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Steel
After a Disappointing Digital Rollout: Four Things Steel Mills Do Differently Next Time
Proven digital transformation in steelmaking isn’t about hype — it’s about how you deploy. In this article, we analyze why around 70% of digital projects underperform and detail how mills that rebound do so by redefining their approach: precise problem definition, minimal scope, workflow-aligned integration, and rigorous tech evaluation. If a past deployment failed at your mill, learn the practical criteria and steps other operations used to turn the next one into a success.
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Fero Labs
Carnegie Mellon University’s CISR Partners with Fero Labs to Shape the Next Generation of AI-Driven Steel Innovators
Carnegie Mellon University’s CISR and Fero Labs announce a partnership bringing explainable AI, real industrial datasets, and mill-ready decision tools into CMU’s steelmaking research curriculum — preparing metallurgists and process engineers to drive efficiency, sustainability, and the future of steel production.
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