Alcoa
Alcoa optimizes its predictive maintenance with AVEVA PI System
Alcoa, a historic leader in the aluminum industry for more than 130 years, wanted to take a new step by practicing predictive maintenance on the machines in its smelters rather than suffering failures. The challenge was to integrate historical data from AVEVA PI System with maintenance information managed in Oracle eAM, in order to cross-reference the two sources and extract reliable predictions. The platform deployed now makes it possible to predict a machine's remaining useful life by matching real-time operational data with maintenance history. Alcoa thus identifies not only the nature and source of an anomaly, but also how much time is available before intervention is needed. The results validate the approach: unplanned downtime is down 20%, maintenance costs are decreasing and maintenance labor hours have fallen by 10%, durably transforming the operational efficiency of the smelters.
FAQ
How does AVEVA PI System predict a machine's remaining useful life?
At Alcoa, AVEVA PI System cross-references real-time operational data from the aluminum smelter with maintenance history from Oracle eAM. This correlation makes it possible to identify early failure signatures and calculate the remaining useful life of critical equipment. Teams schedule interventions at the right time, neither too early (waste) nor too late (failure). This is the founding principle of modern industrial predictive maintenance.
Why integrate AVEVA PI System with a CMMS such as Oracle eAM?
Integrating PI System with Oracle eAM is essential because these two worlds were historically siloed: maintenance managed its schedule, and operations managed their data. By cross-referencing both sources, Alcoa identifies the nature and origin of an anomaly, and how much time is available before intervention is needed. This IT/OT convergence turns reactive maintenance into a structured predictive strategy aligned with the assets' actual industrial performance.
What ROI does AVEVA predictive maintenance deliver for an aluminum smelter?
Alcoa reduced its unplanned shutdowns by 20%, lowered its maintenance costs and cut the labor hours spent on maintenance by 10%. In an industry as capital-intensive as aluminum, where every pot shutdown is costly, these gains add up quickly. Beyond the figures, predictable interventions improve overall planning and asset availability, two critical KPIs for the competitiveness of a global producer.
How does Alcoa leverage 130 years of aluminum industry history with AVEVA?
Alcoa is capitalizing on more than a century of operational experience by turning its know-how into predictive models powered by AVEVA PI System. Failure modes historically known to experts become automated rules applied in real time across all machines. This digitization of experience is crucial as the workforce turns over: tacit knowledge becomes a lasting digital asset, accessible to new generations of operators.
Why is predictive maintenance strategic in the mining and metals industry?
Mines and aluminum smelters run continuously with heavy equipment whose shutdown affects the entire production chain. AVEVA PI System makes it possible to anticipate failures and schedule interventions during optimal windows, rather than suffering breakdowns. For Alcoa, this strategy reduces lost production, optimizes maintenance resources and improves team safety. It is a pillar of digital transformation in heavy industry.