What is Predictive Maintenance?
Predictive maintenance is a maintenance strategy that uses Real-time data and analytical models to predict when a machine component will need servicing. As a result, maintenance is only carried out when it is actually needed, leading to lower costs and less unplanned downtime.
Predictive maintenance uses Sensors, historical data and often Machine Learning to predict future failures in good time.
🧠 How does predictive maintenance work?
- Data collection
- Real-time data from Sensors: vibration, temperature, pressure, acoustics
- Historical data from SCADA, MES, CMMS or a Historian
- Analysis and models
- Thresholds, trends, anomalies
- Advanced algorithms or AI models for pattern recognition
- Prediction
- When will a failure occur?
- Which component is critical?
- How much time is left before action is needed?
- Action and planning
- Automatic creation of a task in the CMMS
- A warning on the HMI or in SCADA
- Ordering parts before failure
🏭 Use in OT networks
- Monitoring of motors, pumps, fans, bearings and drives
- Process industry: preventing failures of valves, compressors and sensors
- Power plants, chemicals, pharmaceuticals: where maximum availability is required
- Integrated into Edge Computing or the cloud for analysis and visualisation
- Part of Smart Industry and Industry 4.0 strategies
Predictive maintenance increases OEE (Overall Equipment Effectiveness) and extends asset life.
🔍 Predictive vs. preventive vs. condition monitoring
| Maintenance type | Trigger | Benefit |
|---|---|---|
| Preventive maintenance | Time or usage interval | Easy to plan |
| Condition Monitoring | Current condition (measurements) | Real-time insight |
| Predictive maintenance | Predictions from trend analysis | Maximum efficiency, minimal downtime |
🔐 Security considerations
- Sensor and system data can be sensitive
- Make sure you have:
- Separate networks or VLANs
- Access Control and encryption
- SIEM monitoring and log capture
- Authentication for cloud and edge platforms
- Pay attention to integration with IT systems through OT convergence
Security is essential when predictive maintenance is connected to external platforms or analytics services.
📌 In summary
Predictive maintenance enables organisations to plan maintenance intelligently, based on data and predictions, reducing costs and increasing reliability. It is an indispensable element of modern, data-driven OT strategies.