TARGETED OUTCOME
9+ months Early warning window before failure Predictive Maintenance · OIL & GAS
Predict heat exchanger fouling months before it costs you a batch.
Heat exchanger fouling in polyethylene and similar process manufacturing extends batch cycles, raises energy use and forces unplanned maintenance — and weekly U-coefficient checks rarely catch it early enough. The XMPro AO Platform turns real-time exchanger telemetry into predictive insight that names the failure window months ahead.
What's getting in the way today.
Fouling progresses quietly across the heat exchanger. Four pressures compound:
ISSUE 01 OPEN
Extended batch cycles
Fouling slowly lengthens batch cycles, eroding plant yield without a single dramatic event to react to.
ISSUE 02 OPEN
Intermittent monitoring
Weekly U-coefficient calculations miss the leading edge of fouling — by the time the metric drops, the cleaning window is already overdue.
ISSUE 03 OPEN
Unplanned interventions
Without predictive insight, fouling is discovered during disruption rather than during planned maintenance windows.
ISSUE 04 OPEN
Efficiency loss
Progressive fouling drops heat transfer efficiency, lifting energy consumption and shortening exchanger lifespan.
Heat Exchanger Fouling Prediction — how it works.
Continuous telemetry from temperature, pressure and flow sensors, modelled against the exchanger’s design U-coefficient, with predictive analytics flagging fouling progression long before efficiency collapses.
Real-time data integration Predictive analytics Anomaly detection Automated recommendations Operational dashboards Digital twin simulation
The platform integrates shell- and tube-side temperature, pressure and flow data continuously across every heat exchanger, calculating the U-coefficient at far higher frequency than weekly manual checks. Predictive models trained on historical fouling signatures forecast when performance will fall below required standards, surfacing the failure window with confidence scoring. Anomaly detection flags wear and fouling patterns; threshold breaches generate ranked maintenance recommendations with cleaning urgency, parts and crew assignment attached. Operators see live U-coefficient trends, exchanger duty, safety intelligence and ranked actions on a single dashboard, with work-request creation one click away.
*Illustrative dashboards from the platform. Layout, signals and decision points are scoped per site.
Scope this for your operation.
Tell us about your fleet, your control maturity and the lever that matters most. We’ll map this use case to your starting point.
*Indicative ranges from industry research and customer engagements · actuals vary by site, control maturity and starting baseline.
What this looks like in operation.
Cleaning aligned to planned outages
A multi-month warning window lets fouling-driven maintenance slide into planned shutdowns instead of triggering them.
Yield protected
Batch cycles stay efficient because fouling is acted on before heat-transfer loss compounds.
Lower energy and unplanned-cost exposure
Real-time visibility into exchanger efficiency turns slow fouling into a planned cost rather than an unplanned crisis.
Built for these industries.
Other solutions you might explore.
Not a concept. In production.
XMPro is deployed at Tier 1 global operators across asset-intensive and mission-critical industries — delivering measurable results across predictive maintenance, process optimisation and operational intelligence.
Now pushing the frontier.
MAGS agents are achieving what no other industrial platform has demonstrated — sustained autonomous operations at enterprise scale.
0+
Days Autonomous
Safety-critical petrochemical operations
3-0+
Agents Per Team
Specialized agents coordinating per use case
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Teams Deployable
Scale across sites and business units
0%
Governed
Every agent, every decision, every action — auditable
