Predictive aircraft maintenance needs to look beyond isolated sensor readings and make greater use of operational flight data if the industry is to unlock its full potential, Shawn Lee, head of customer success management Asia at Skywise told delegates at this week's PAM APAC conference in Singapore.
Presenting the Skywise approach to predictive maintenance, Lee argued that component-level sensor data provides only part of the picture when engineers are "trying to understand degradation".
"While sensors can identify how a component is performing, Lee said operational context - including throttle profiles, pilot inputs and environmental conditions - can provide greater insight into why deterioration is occurring".
Bringing the two together could enable maintenance teams to reduce false positives, identify less obvious or ‘invisible’ degradation and better predict cumulative fatigue rather than simply reacting when individual parameters approach physical limits.
Lee drew a comparison with Formula 1, where teams combine vehicle telemetry with wider information about how and where a car is being operated rather than analysing individual sensor readings in isolation.
Lee said the same principle "could help aviation move further from reactive maintenance towards more effective predictive and preventive strategies", ultimately increasing aircraft availability by reducing operational interruptions.
Collaboration was another major theme of the presentation, with Lee arguing that sharing expertise and data can "accelerate the development of predictive maintenance capabilities".
Its Digital Alliance brings together Airbus, Delta TechOps, GE Aerospace, Liebherr and Collins Aerospace, combining aircraft OEM, airline MRO, systems and component expertise.
Skywise acts as integrator, with the alliance targeting nose-to-tail predictive maintenance coverage and capabilities extending beyond Airbus aircraft.
"The initiative now covers more than 20 ATA chapters across Airbus families," Lee explained, "with established coverage on the A320 and A330 and further development focused on the A220 and A350".
Lee also highlighted plans to make it easier for airlines to incorporate their own engineering knowledge and analytics into the wider ecosystem.
The myAnalytics framework is intended to allow operators to build their own intelligence on top of the platform, including analytics developed from their own field experience. The capability can be used with or without coding skills and is not restricted to Airbus aircraft.
The approach reflects a broader message from the session: that the next stage of predictive maintenance may depend not simply on collecting more aircraft data, but on "connecting operational context, engineering expertise and intelligence from across the industry".
