AI Boiler Tube Failure Prediction
The Problem
“Predict boiler tube failures before forced outages”
Organizations face these key challenges:
1
Forced outages and rapid derates from unexpected tube leaks, causing high replacement power costs and reliability penalties
2
Limited visibility into early-stage degradation due to sparse inspections, incomplete root-cause linkage, and noisy DCS signals
3
Inefficient maintenance planning: over-replacing healthy tubes while missing high-risk circuits, increasing outage duration and cost
Impact When Solved
20–40% reduction in boiler tube leak forced outages through early warning and risk-based maintenance$1M–$5M annual value per large unit from avoided downtime, reduced repair spend, and fewer start/stop cycles10–25% reduction in inspection and tube replacement scope with higher precision targeting of at-risk locations
The Shift
Real-World Use Cases
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