Predictive maintenance for heat exchangers
Predictive maintenance for heat exchangers uses process-data analytics — tracking approach temperature, pressure drop and heat-transfer effectiveness — to detect fouling and scaling before it forces an unplanned clean or starves the process of heat.
Why monitor heat exchangers
Heat exchangers foul gradually, quietly cutting heat-transfer effectiveness and raising energy use long before they cause a problem. Because the degradation is in process data rather than vibration, analytics that model expected performance are the right tool — flagging when cleaning will actually pay back, rather than cleaning on a fixed, often wasteful, schedule.
Common failure modes
- Fouling and scaling on heat-transfer surfaces
- Tube blockage and flow maldistribution
- Corrosion and tube leaks
- Gasket failure
Which monitoring techniques fit
- Process-data analytics (approach temperature, effectiveness, pressure drop)
- Performance trending against a clean baseline
- Periodic inspection and leak testing
- Thermography on accessible units
What the data shows
A widening approach temperature and rising pressure drop at constant flow are the classic fouling signature; a sudden change can indicate a tube leak or blockage. Trending effectiveness shows the optimal, cost-justified time to clean.
Related guides
Heat exchanger fouling: causes and prevention
Why exchangers foul, what it costs in energy and throughput, and how to predict and manage cleaning instead of reacting to it.
Waste heat recovery in industry
Where industrial waste heat hides, the technologies that capture it, and how to judge whether recovery pays at your site.
Predictive maintenance: a practical guide
What predictive maintenance is, how it differs from preventive maintenance, which techniques fit which assets, and how to start without boiling the ocean.
Software that helps
AVEVA Predictive Analytics
Early-warning analytics for critical process and power assets.
Seeq
Advanced analytics for time-series process data.
AspenTech (aspenONE)
Process modelling and optimization for heavy process industry.