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Intelligent Boiler Sootblower Optimization AI
2025•✅ Completed
Photo Documentation Under Review
Project Overview
Monitored heat transfer efficiency across boiler sections using historical telemetry from the PI Server. Used gradient boosting regression to predict optimal times to clean tubes, balancing cleaning costs with thermal gain.
Key Results & Impact
- ✓35% reduction in steam consumption for sootblowing (Company OKR 2025).
- ✓Prevented slagging accumulation, protecting boiler heating surfaces.
- ✓Deployed as an automated scheduler in plant IT network.
Technologies Used
PythonXGBoostPI SystemSQLScikit-Learn
Additional Information
CategoryApplied ML & AI
Year2025
StatusCompleted