Predictive Maintenance & Anomaly Detection
Lifecycle stages:
MLOps journey description: This journey involves monitoring systems for early signs of failure, using AI to detect anomalies and predict maintenance needs before issues occur.
Use case examples: Anticipating equipment failure and detecting deviations from normal operations.
- Predicting pump failures using time-series sensor data
- Early detection of corrosion or fouling in pipelines
- Vibration anomaly detection in rotating equipment (e.g., turbines)
- Temperature and pressure spike detection for compressors
- Fault detection in SCADA systems