AI accelerates First Article Inspection (FAI) in aerospace
From hours to minutes: How AI accelerates First Article Inspection
In aerospace, quality, traceability and speed determine the success of entire supply chains. This becomes particularly evident in the First Article Inspection (FAI), a central standard process used when suppliers manufacture a component for the first time.
This is exactly where one of our current AI projects comes in: with the goal of radically accelerating a highly critical verification process, reducing costs while simultaneously increasing inspection quality and audit reliability.
The starting point: A critical but time-consuming process
When a new component is produced for the first time, the supplier creates an FAI report that consolidates all relevant documentation. Official forms 1 to 3 summarise this report and later serve as essential proof, among other things for aviation authorities.
Responsibility lies with the supply chain validator:
- Do the details in the forms match the remaining documentation?
- Are all records complete and consistent?
- Are there deviations that must be sent back to the supplier?
In practice, these reports are extensive and heterogeneous:
- 60 to 120 pages (sometimes significantly more)
- Scans, handwritten notes and different languages
- Different document types within a single PDF
Manual review takes an average of around three hours per report. If queries and correction loops arise, the process can easily stretch over several days. At the same time, high costs arise, among other things through the use of external service providers.
The solution: AI-supported verification with a human-in-the-loop
Our interdisciplinary team developed an AI-based verification tool for FAI reports within four months.
The approach was deliberately pragmatic:
- Upload of the FAI report as a PDF
- Automatic recognition and classification of relevant document types (e.g. forms, work orders, certificates of conformity)
- Rule-based and AI-supported plausibility checks
- Structured result report with clear identification of deviations
A key factor for acceptance in a quality-critical environment:
- Humans remain part of the process
- Document classifications are confirmed
- Findings can be commented on
- Final approval and signature are still provided by a responsible person
This ensures the process remains verifiable, traceable and suitable for audits.
“We reduced the analysis to just a few minutes because extraction and checks run in parallel. That was a real performance lever.” – Nicolai Schleinkofer
The impact: Speed, predictability and scalability
The greatest leverage lies clearly in the time savings:
- Instead of around 3 hours, the AI check now takes only 5 to 10 minutes per report.
- Reviews are not only faster but also far more predictable.
In addition, the project reveals considerable economic potential:
- Our internal calculations indicate potential savings of around €3.4 million.
- The main driver is the significant reduction in external service providers involved in this process.
Another advantage is parallelisation.
Where previously reports had to be reviewed one after another, today 10 to 20 FAI checks can be performed simultaneously.
Key learnings from the project
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LLMs have limitations – particularly when dealing with highly complex technical drawings.
The biggest development lever was iteratively refining extraction processes, prompts and validation logic, and presenting results in a way that remains technically verifiable.
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Organisation often outweighs technology.
In corporate environments, tool access and platform approvals can quickly become bottlenecks – an issue that must be managed proactively at an early stage.
Outlook: Scaling instead of a single solution
Following the successful proof of concept, the next step is clear:
- Broad rollout to additional supply chain teams
- Establishment as a standard tool within the FAI process
What makes this particularly exciting:
FAI is a standardised process in aerospace. This makes the approach highly transferable and scalable for other organisations, clients and teams.
