CLIFFGATECLIFFGATE · Industrial AI
Industrial AI: Real-time equipment monitoring
SCADA/DCS integration, ML prediction, and actionable alerts
Problème métier
Plants often have sensors, SCADA screens, and historian data, but this information is not converted into predictive action. Operators receive alarms when something is already wrong, while management receives downtime reports after losses have occurred.
Approche technique
- —Connect to existing SCADA/DCS tags and historian databases without replacing plant control systems.
- —Normalize streams from pumps, compressors, heat exchangers, pipelines, boilers, centrifuges, reactors, conveyors, and utilities.
- —Train models on vibration, temperature, pressure, flow, acoustic signals, current consumption, and operating regimes.
- —Generate failure probability and remaining-useful-life indicators for 48–72 hour maintenance windows.
- —Route alerts into dashboards, CMMS work orders, escalation workflows, and management reports.
Résultat métier
- —Move from reactive repair to preventive maintenance.
- —Reduce unplanned downtime during peak production seasons.
- —Prioritize maintenance based on risk and production impact.
- —Lower emergency spare-part and contractor costs.
- —Create a structured reliability dataset for continuous improvement.