Industries
IoT & Predictive Maintenance
Equipment data can support maintenance decisions when it is reliable and connected to asset history.
IoT & Predictive Maintenance
Follow the record to the next decision
We discuss sensor inputs, review rules and the action taken when a signal changes. A model or threshold needs evaluation in the actual operating environment.
Workflows to examine
- Real-time sensor data collection
- Predictive failure alerts
- Maintenance scheduling automation
- Equipment health dashboards
- Historical failure analysis
In practice
IoT & Predictive Maintenance: a practical example
A sensor starts reporting an unusual pattern on a machine. Compare the reading with operating conditions and a known maintenance event. Agree who investigates the alert and how their findings return to the record before using the signal to change the maintenance schedule.
An illustrative scenario to discuss when planning your project.