Predictive Maintenance Solutions
By detecting anomalies and trends early, we help reduce unplanned downtime, extend asset life, and lower maintenance costs.
See it before it breaks
Unexpected equipment failure is costly and dangerous. Dreig’s predictive maintenance solutions use machine learning algorithms to detect subtle patterns in sensor data—helping you predict breakdowns before they happen and schedule interventions only when truly needed.
What We Do
- Design and deploy condition monitoring frameworks
- Apply supervised and unsupervised ML models to time-series data
- Integrate predictive triggers into CMMS, SCADA, or MES
- Create dashboards for OEE, MTBF, RUL, and trend deviations
Applications
- Vibration and thermal analysis of pumps, motors, and gearboxes
- Predictive analytics for HVAC, chillers, and compressors
- Transformer and switchgear health modelling
- Real-time insights for conveyors, fans, turbines, and more
Business Benefits
- 30–60% reduction in unplanned downtime
- 20–40% increase in asset lifespan
- 10–15% savings in MRO parts and labor
- Safer working environments with lower incident rates
Move from calendar-based to condition-based maintenance—driven by data, not guesswork.
Let’s Make Compliance and Excellence Simple.
From ISO certification to technical testing and strategic consulting, our experts are ready to guide you every step of the way.
