Vanderlande

Logistics · Netherlands / UK

25% less unplanned downtime

Vanderlande deploys predictive maintenance on Heathrow Terminal 3 baggage systems using AWS Monitron

Predictive maintenance on one of the world's busiest airports, deployed by the Dutch OEM on its own installed infrastructure, creating a replicable service proposition across 600+ airports in the Vanderlande network.

Friction

Unplanned failures in baggage handling systems cause flight delays, reputational damage, and high emergency repair costs. Reactive maintenance in a 24/7 airport operation is structurally unmanageable. There is no convenient time for a breakdown.

Breakthrough

Sensors on critical assets stream vibration and temperature data to AWS Monitron. ML models detect anomalies and predict failures before they occur. Maintenance teams receive early warnings integrated into Vanderlande's own service planning system, enabling planned interventions to replace emergency ones.

Impact

25% reduction in unplanned downtime on monitored assets. Substantial savings on spare parts and maintenance labour. Shift from reactive to proactive maintenance: planned interventions replace emergency callouts. Framework replicable across Vanderlande's 600+ airport customers worldwide.

Unlock the full analysis with breakthrough, impact, what made it smart and its technical approach below!

Name

Organisation name

Problem

Heathrow Terminal 3 processes thousands of bags per hour. A baggage system failure at peak time can delay dozens of flights and generate headlines. The cost of a single significant unplanned outage in recovery time, staff hours, delay compensation, and reputational damage can exceed the cost of an entire year's predictive maintenance programme.

What made it smart

Vanderlande deploying predictive maintenance on its own installed infrastructure means the OEM's knowledge of the system's design, failure modes, and wear patterns is built into the AI model. This is qualitatively different from a third-party retrofit. The system is calibrated to the specific mechanics of Vanderlande's own equipment.

Technical approach

Vibration and temperature sensors on critical baggage handling components stream data to AWS Monitron. ML models identify anomaly patterns that precede failures, generating alerts when maintenance should be scheduled. Alerts are integrated into Vanderlande's existing service management and planning workflows, enabling maintenance scheduling before failure occurs.

Strategic lesson

For OEMs and infrastructure providers, predictive maintenance is not just an efficiency tool. It is a service model transformation. The company that monitors and predicts becomes a partner, not just a supplier.

Reflection question

Does your organisation own or maintain physical assets that could be monitored continuously, and have you considered what a predictive maintenance service would mean for your customer relationships and revenue model?