Imagine a plane with a 'digital skin' that feels stress and heat just like human skin. This skin sends data to a virtual copy of the aircraft that predicts when a part will break before it actually happens. It is like having a crystal ball for aircraft health, ensuring the vehicle is safe to fly without needing to take it apart for inspection every time.
Urban air vehicles face high maintenance costs and safety risks due to unpredictable structural wear. Current maintenance is often reactive or based on generic schedules rather than actual vehicle usage.
A digital twin platform integrated with a self-powered IoT sensing skin and a cloud-based analytics system for fault detection.
If you are an air taxi operator dealing with high maintenance downtime — this project developed a digital twin and IoT sensing skin that enables predictive maintenance. This reduces operational costs and improves the safety of urban skies.
If you are a vehicle manufacturer dealing with unknown structural stress in new designs — this project developed a system to record the actual load spectrum of every flight. This provides real load data to optimize the design of future vehicle generations.
If you are a fleet manager dealing with unpredictable component failures — this project developed AI-driven remaining useful life estimation. This allows you to schedule repairs based on actual wear rather than fixed calendars.
Based on available project data, costs are reduced through the implementation of predictive maintenance, which uses AI to estimate the remaining useful life of components.
The project is targeting TRL5 for the IoT sensing skin and data acquisition units, meaning it is moving toward validation in a relevant environment but is not yet at full industrial scale.
Based on available project data, specific licensing terms are not provided, but the project involves a consortium of 7 partners including 3 industry players.
The system uses a cloud platform for real-time processing and storage, ensuring secure data transmission from the vehicle to the cloud.
The project period runs from 2023-02-01 to 2026-01-31, indicating the development phase concludes in early 2026.
The consortium is well-balanced for technology transfer, consisting of 7 partners across 4 countries. With an industry ratio of 43% (3 industrial partners and 1 SME), there is a strong commercial pull to complement the 3 universities and 1 research organization, ensuring the digital twin and sensing skin are developed with market needs in mind.
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