Upstream Operator Cuts Unplanned Downtime 55% with Predictive Maintenance
Deploying an IoT and AI platform on Azure that monitors critical rotating equipment in real time, predicting failures days before they happen.
Project Overview
The Challenge
Unplanned downtime on critical compressors and pumps was costing millions per incident, while preventive maintenance schedules were largely calendar-based.
- 1Multi-million-dollar production losses from unplanned equipment failures
- 2Calendar-based maintenance over-servicing healthy assets and missing degrading ones
- 3Limited remote monitoring capability for offshore and remote sites
Our Solution
CloudGate built a predictive maintenance platform ingesting sensor data from compressors, pumps, and turbines, applying ML models to detect early signs of failure.
- Real-time sensor ingestion via Azure IoT Hub across 200+ critical assets
- Custom anomaly detection and remaining useful life models on Azure ML
- Maintenance command center in Power BI with auto-generated work orders
The Results
- Predicted and prevented a major compressor failure 11 days before occurrence
Technologies Used
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