Case Study: Alcoa achieves reduced unplanned downtime with Senseye Predictive Maintenance

Alcoa - Customer Case Study

Alcoa, a global leader in bauxite, alumina, and aluminum products, wanted to move from planned maintenance to predictive maintenance across its global operations to improve efficiency, reduce costs, and address tight market margins. The company needed a robust solution that could use existing machine and maintenance data without requiring thousands of new sensors or extensive training, and partnered with Senseye for its Predictive Maintenance product, Senseye PdM.

Senseye connected Senseye PdM to Alcoa’s existing OSIsoft PI and Oracle EAM systems at an aluminum smelter in East Iceland, enabling predictive monitoring of critical assets without installing new sensors. The solution delivered alerts and diagnostics before failures, reduced unplanned downtime by 20%, improved operating efficiency and maintenance costs, and achieved ROI in 4 to 6 months, leading to further rollout across additional Alcoa sites.

Alcoa

Bruno Longchamps

Global Aluminum Manufacturing Intelligence Manager