Case studies Energy & manufacturing
Predictive maintenance for a global energy company
A major energy conglomerate
70%improvement in machine reliability
2×
Lower maintenance costs
100s
Of sensors monitored
The challenge
Unplanned downtime was a major drain. Hundreds of sensors produced a constant stream of data, but engineers had no way to spot early signs of fatigue or prioritise maintenance by actual machine health.
What we built
- A predictive maintenance framework turns high-frequency sensor data into early warnings.
- Real-time monitoring produces a health score for every asset.
- Reliability reports help engineers prioritise work by risk.
- Maintenance shifted from reactive and scheduled to predictive.
The results
- Machine reliability improved 70%.
- Maintenance costs were cut in half.
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