Before we deployed the Asset Health AI application, unplanned mill downtime was a costly issue for our customer, a multi-billion-dollar global steel producer.
More than ten leading software vendors, including large enterprise software providers, specialty software shops and consulting firms competed for the best results.
Even while it's visualizing high-frequency multivariate signals across complex and varying asset hierarchies, the application makes challenging data easy to access and use.
The Asset Health AI implementation extends across the majority of this customer's manufacturing processes, addressing 140 unique failure-modes. From continuous casting, to hot rolling, to cold rolling, to the galvanizing lines, data pipelines fuel two important AI inference engines.
The goal was simple, the outcomes clear: