United StatesManufacturing2019 – ongoingAlcoa
Predictive maintenance for aluminum-smelter equipment
Alcoa's smelter maintenance project reduced unplanned downtime by 20%, according to AVEVA
Problem
Alcoa stored machine sensor readings and maintenance records in separate systems. It lacked a useful way to combine them to predict failures.
Approach
Alcoa tested Senseye at its Fjardaal smelter in Iceland. AVEVA PI System's asset framework connected operating data with Oracle eAM maintenance records. Maintenance crews investigated detected faults before equipment failed.
Results
Takeaway
Crews checked an apparently functioning saw motor during a scheduled shutdown and found a loose belt guard. The repair avoided an unscheduled stop, according to AVEVA.
Categories
- Size
- Large enterprise
- Industry
- Manufacturing
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
AVEVA described Alcoa's maintenance deployment with Senseye. It reported 20% less unplanned downtime and 10% fewer maintenance person-hours.
Full details are in the original sources.