AWS Predictive Maintenance in Manufacturing Use Case
Use case typePredictive maintenanceUpdated Jun 13, 2026
Commonwealth Bank of Australia faces challenges with equipment failure and degradation causing unplanned downtime and high maintenance costs in manufacturing operations. They implemented a predictive maintenance solution using AWS technologies to optimize equipment performance and extend asset lifespan by predicting failures before they occur.
- Organization
- Commonwealth Bank of Australia
- Industry
- Manufacturing
- Location
- United States
- Published
- April 2026
Reported outcomes
Strategic outcomes
Scale & capacityIncreased asset uptime and availabilityCost efficiencyReduced maintenance expensesBetter decisions & insightImproved equipment health understandingNew product / capabilityImplemented predictive maintenance capability
Primary read
Use case focus
Showing 2 of 2
- 1Predictive Maintenance
- 2IoT Monitoring
Equipment failure leads to costly unplanned downtime and reduced operational efficiency in manufacturing.
- Deployment of machine learning-based predictive maintenance system using Amazon Monitron, Amazon Rekognition for anomaly detection in images/videos, and Amazon SageMaker for custom ML models.
- Integration of IoT sensors via AWS IoT Core, Device Management, and IoT Events to monitor equipment conditions like temperature, vibration, and humidity in real-time.
- Alerts and maintenance scheduling are optimized based on analyzed sensor data to prevent failures and reduce costs.
- Increased asset uptime and availability in manufacturing operations.
- Reduced maintenance expenses through condition-based servicing rather than scheduled maintenance.
- Improved understanding of equipment health and operational performance through advanced AI and IoT integration.
Sources & evidence1
Groundedness: 4/5
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