Building More Reliable Baggage Operations at Scale - Manchester Airport Group Selects MSAI

MultiSensor AI is excited to announce the planned deployment of its reliability monitoring solutions with Manchester Airport Group (MAG), one of the UK’s leading airport operators. The deployment reflects a growing focus across airports on improving asset reliability and reducing unplanned disruption across critical baggage handling and inspection systems. Read the press release here.

As a pioneer in condition-based monitoring, early threat detection, and predictive maintenance, MultiSensor AI supports environments where systems run continuously and downtime is not an option. The collaboration with MAG highlights how airports are using continuous monitoring to gain earlier visibility into asset condition and strengthen day-to-day operational resilience.

For asset-intensive environments like airports, reliability depends on catching issues early - without adding more manual inspections or operational complexity.

The MultiSensor AI solution and software platform is designed for these conditions, combining continuous multi-sensor monitoring with reliability engineering expertise to help teams detect degradation earlier, prioritize the right work, and maintain uptime across critical systems.

Reliability Challenges Inside Modern Airport Operations

Airport baggage handling systems operate under sustained load, tight timing, and constant pressure to perform.  Conveyors, motors, bearings, and electrical components are tightly linked, so small issues can quickly ripple across an entire terminal.

Traditional inspection schedules can miss early signs of trouble. Issues like overheating, friction buildup, or electrical degradation often develop gradually between inspections, pushing teams into reactive maintenance once performance is already impacted. During peak travel periods, the cost of these disruptions exceeds maintenance budgets.

Seeing Problems Earlier, Without More Manual Work

Continuous condition monitoring fills these visibility gaps by showing how assets behave during live operations - not just during inspections. Maintenance teams can spot trends, detect early warning signs, and act before minor issues escalate.

At Manchester Airport Group, the deployment combines fixed monitoring with handheld thermal inspections. This approach provides continuous oversight of high-impact areas, such as baggage handling systems, while still supporting targeted inspections when deeper analysis is needed.

Starting with critical assets allows teams to build confidence in alerts, understand real operating behavior, and fold insights into existing maintenance workflows.

MultiSensor AI excels in environments where equipment runs continuously and failures are costly. The MSAI Connect platform provides consistent visibility into asset condition during live operations - helping maintenance teams shift from reactive responses to condition-based decisions.

Moving Toward Condition-Based Decisions

With continuous insight, maintenance decisions can shift from fixed schedules to actual asset condition. In practice, this helps teams:

• Catch early signs of overheating or mechanical stress
• Identify issues between inspection intervals
• Prioritize work based on risk and impact
• Reduce the likelihood of unplanned downtime

For airports, earlier intervention supports smoother operations and more predictable performance.

Supporting, Not Replacing, Maintenance Teams

Continuous monitoring works because it complements existing maintenance programs. Data from fixed sensors and handheld inspections can be reviewed alongside current systems, adding clarity without adding complexity.

Platforms like MSAI Connect bring sensor data into a single view of asset health, while the MSAI Hub supports reliable data collection in live environments - making it easier to scale monitoring across sites.

A Model That’s Spreading Beyond Airports

Manchester Airport Group’s deployment reflects a wider trend across UK and European infrastructure. Airports, logistics operators, data centers, and other asset-intensive environments are adopting continuous monitoring to meet rising expectations for uptime and reliability.

As more operators move beyond periodic inspections toward continuous visibility, condition monitoring is becoming a practical, proven part of modern reliability programs - especially where operations can’t afford surprises. 

Proven across large, complex operations in Europe and North America, MultiSensor AI helps organizations scale reliability monitoring without disrupting existing maintenance workflows. To learn how MultiSensor AI supports reliability programs in airports and other asset-intensive environments, book a meeting with our team or request a demo to see how continuous condition monitoring works in practice.