NDTonAIR · Project

Smarter Aircraft Inspection Tools That Catch Hidden Defects Before They Become Dangerous

manufacturingTestedTRL 5

Imagine you own a car and the mechanic could check every bolt and weld without ever opening the hood — just by shining a laser or placing a sensor on the surface. That's basically what NDTonAIR did for airplanes. They built inspection tools that use lasers, ultrasound, heat cameras, and machine learning to find cracks, weak spots, and bonding failures in aircraft parts — especially the newer composite materials that are lighter but harder to inspect. They also trained a new generation of engineers who know how to use these tools in real factories.

By the numbers

Working demonstrator systems built

Consortium partners across Europe

Countries represented in the consortium

Total project deliverables produced

SMEs involved in development

38%

Industry participation ratio in consortium

The business problem

What needed solving

Aircraft manufacturers and maintenance providers face a growing challenge: modern planes use more composite materials that are lighter and stronger, but hidden defects like delamination, weak bonding, or micro-cracks are extremely difficult to find with traditional inspection methods. Missing a defect can mean catastrophic failure; over-inspecting means grounded planes and lost revenue. The industry needs faster, more reliable, and more automated inspection tools.

The solution

What was built

The project built 6 demonstrator systems: a laser-based ultrasound field measurement system, an automatic defect detection and classification tool for eddy current testing, an embedded fiber-optic sensor system (FPSH transducers) for continuous structural monitoring, a multi-technique bonding quality tester, a combined optical and thermography inspection tool, and a piezoelectric SHM device validated under fatigue conditions on benchmark samples.

Audience

Who needs this

Aircraft MRO providers (Lufthansa Technik, SR Technics, AFI KLM E&M)Composite parts manufacturers for aerospace and automotiveNDT equipment companies looking to add AI-based defect classificationAirlines with in-house structural inspection teamsWind turbine blade manufacturers needing composite inspection

Business applications

Who can put this to work

Aerospace MRO (Maintenance, Repair, Overhaul)

enterprise

Target: Aircraft maintenance companies and airlines with in-house inspection

If you are an MRO provider dealing with costly manual inspections that miss hidden defects in composite aircraft parts — this project developed 6 demonstrator systems including laser-based ultrasound, automated defect detection algorithms, and full-field thermography tools that can spot problems faster and more reliably than traditional methods. The automatic classification software reduces human error in defect assessment.

Composite Materials Manufacturing

mid-size

Target: Companies producing carbon fiber or composite parts for aerospace, automotive, or wind energy

If you are a composite parts manufacturer struggling with quality assurance on bonded structures — this project developed a demonstrator system specifically for testing bonding quality using multiple NDT techniques. The embedded sensor approach (FPSH transducers) allows continuous monitoring during production, catching defects before parts leave your factory.

Sensor and Inspection Equipment

SME

Target: Companies developing or selling NDT equipment and inspection services

If you are an inspection equipment maker looking to add machine learning capabilities to your product line — this project produced automatic detection and classification algorithms trained on real defects, plus a piezoelectric SHM device tested under fatigue conditions. With 6 industry partners already involved in development, the technology has been validated in realistic settings.

Frequently asked

Quick answers

What would it cost to license or adopt these inspection technologies?

The project was a training network (MSCA-ITN-ETN) with 16 partners across 7 countries. Licensing terms would depend on the specific demonstrator and the partner institution that developed it. Contact the coordinator at Universita degli Studi di Perugia or the relevant industry partner to discuss terms.

Can these tools work at industrial scale in a real maintenance hangar?

The project produced 6 working demonstrators, including a full-field optical and thermography inspection tool and an SHM device tested under fatigue conditions. These are functional prototypes validated in lab and near-production settings. Scaling to full hangar operations would require further engineering and certification.

Who owns the intellectual property from these demonstrators?

IP is distributed among the 16 consortium partners, which include 6 industry partners and 4 SMEs. Each demonstrator was developed by specific partner combinations. IP rights follow the Horizon 2020 grant agreement rules — the partner who generated the result typically owns it.

Do these inspection methods meet aviation regulatory requirements?

The project specifically worked on quantifying NDT techniques through their probability of detecting reference defects, which is a key regulatory requirement. However, full EASA or FAA certification would require additional validation steps beyond what a research project typically delivers.

How quickly could we integrate these tools into existing inspection workflows?

The automatic defect detection and classification software could potentially be integrated into existing eddy current or ultrasound inspection setups. The embedded sensor technology (FPSH transducers) would require hardware modifications to structures. Based on available project data, integration timelines would vary by demonstrator.

Is the machine learning defect detection ready for production use?

The project delivered optimized automatic detection and classification algorithms tested on real defects for eddy current inspection. This is a working demonstrator, not a certified production system. The algorithms would need validation on your specific part geometries and defect types before deployment.

What kind of ongoing support or collaboration is available?

The consortium includes 7 universities and 3 research organizations with deep expertise in NDT. The project trained a generation of researchers who are now active in industry and academia across 7 countries. Continued collaboration or contract research is possible through the coordinator or individual partners.

Consortium

Who built it

NDTonAIR assembled a strong, well-balanced consortium of 16 partners from 7 countries (AT, BE, DE, FR, IT, LT, UK), with 38% industry participation — above average for a training network. The mix of 7 universities, 3 research organizations, and 6 industry partners (including 4 SMEs) means the technology was developed with direct industry input, not in an ivory tower. The geographic spread across major European aerospace hubs (France, Germany, Italy, UK) gives the results broad applicability and multiple entry points for companies seeking collaboration.

UNIVERSITA DEGLI STUDI DI PERUGIACoordinator · IT
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVESparticipant · FR
UNIVERSITA DEGLI STUDI DI CASSINO E DEL LAZIO MERIDIONALEpartner · IT
UNIVERSITY OF NEWCASTLE UPON TYNEparticipant · UK
BRUSSELS AIRLINESparticipant · BE
UNIVERSITY OF WARWICKparticipant · UK
KAUNO TECHNOLOGIJOS UNIVERSITETASparticipant · LT
RESEARCH CENTER FOR NON DESTRUCTIVE TESTING GMBHparticipant · AT
KATHOLIEKE UNIVERSITEIT LEUVENparticipant · BE
SIEMENS AKTIENGESELLSCHAFTpartner · DE
TWI LIMITEDparticipant · UK

How to reach the team

Universita degli Studi di Perugia (Italy) — reach out to the Engineering or Physics department's NDT research group

Order a report on this consortium See UNIVERSITA DEGLI STUDI DI PERUGIA profile →

Next steps

Talk to the team behind this work.

Want to explore how NDTonAIR's inspection technologies could reduce your maintenance costs or improve defect detection? SciTransfer can connect you with the right consortium partner for your specific application.

Order a report on this topic More in Manufacturing & Industry 4.0