Metals and Mining Case Study
Industry: Steel Manufacturing
Location: South America
Machine Type(s): Continuous Steel Casters
Components: Bending Roll, Breakout, Pinch Roll
A major South American steel manufacturer was underperforming its revenue targets because of unscheduled plant downtime. SKF Enlight AI’s AI-driven Industrial Analytics solution triggered alerts up to 8 days before failure occurrence. The failure prediction rate of 93% has helped the manufacturer improve yield rates and reduce maintenance and overhead costs.
Lost production / revenue due to unscheduled downtime High O&M costs from overtime labor expenditures
Prediction Rate: 93% Time to Failure: 8 days
Business Impact / ROI
30% reduction in unplanned downtime
15% reduction in operating costs
Data generated by over 400 sensors was streamed to SKF Enlight AI’s cloud. Enlight AI applies advanced Machine Learning algorithms (AutoML) to the data. Based on detection of anomalous behavioral patterns, the solution provided predictions of evolving failure and indications of failure root cause.
What is Automated Machine Learning?
Within the Machine Learning discipline, there are multiple manual processes that are dependent on data scientists. AutoML applies advanced algorithms which automate manual Machine Learning processes, thereby reducing the need for human labor.
With AutoML industrial plants can scale Predictive Maintenance solutions across multiple plants within a few days.