Steel

After a Disappointing Digital Rollout: Four Things Steel Mills Do Differently Next Time

Name: CamelCase Collective
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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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Digitalization

Why Some Digital Projects Fail to Deliver - and How to Ensure Yours Succeed

Steel and chemical operations are proving that AI and digital transformation can work. See how explainable machine learning and focused deployment help rebuild trust and deliver real results in production.

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Digitalization

The Key Question for AI Vendors: “Will This Work with the Data I Already Have?”

Discover the critical question AI vendors must answer to ensure successful integration: "Will this work with the data I already have?" Fero Labs answers this question as it relates to their AI software for manufacturing excellence. Learn how to assess data compatibility and readiness for AI implementation, ensuring seamless integration with your existing data infrastructure.

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Digitalization

The Enduring Relevance of ‘GIGO’ in the Age of AI

For process engineers and data scientists: Poor data quality can derail industrial AI. Discover why "Garbage In, Garbage Out" (GIGO) remains critical in industrial process workflows using AI. Learn how poor data quality impacts process optimization and predictive models, and explore actionable strategies to ensure reliable insights for manufacturing success. Explore how Fero Labs tackles GIGO with advanced tools to clean, curate, and optimize manufacturing data for actionable results.