As aerospace maintenance, repair and overhaul (MRO) activity continues to accelerate, the pressure on inspection processes is intensifying. Engines are staying on wing longer, component condition is becoming less predictable, and the backlog across global fleets is placing unprecedented strain on repair cycles. In response, the industry has largely defaulted to a familiar solution: increase inspection capacity.
But according to Ben Anderson, Managing Director of Derby-based metrology specialist AddQual, that approach risks solving the wrong problem.
“The instinct is always to inspect more, or inspect faster,” he explains. “But the real challenge isn’t throughput alone — it’s decision-making. If you’re not failing components quickly and confidently, you’re simply moving the bottleneck further downstream.”
At the heart of AddQual’s approach is a principle more commonly associated with software development than aerospace engineering: fail fast. In an MRO context, that means identifying non-conforming or unrepairable components as early as possible in the process, preventing wasted time, labour and capacity on parts that will never return to service.
“In aerospace, hesitation is expensive,” Anderson continues. “Every hour spent inspecting a component that ultimately fails is capacity you’ve denied to one that could have been repaired and returned to service. Fast fail isn’t about being negative — it’s about being decisive.”
This shift in thinking is being driven by a broader transformation in how inspection is understood. No longer just a gatekeeping function, it is increasingly becoming a source of operational intelligence — one that informs repair strategy, optimises workflows and improves overall yield. Recent developments across the sector reinforce this trajectory. The collaboration between GE Aerospace and Waygate Technologies, which introduced AI-enabled, menu-directed inspection templates for engine borescope applications, highlights how structured workflows and artificial intelligence are beginning to standardise and accelerate inspection processes. By guiding inspectors, improving image capture consistency and embedding defect recognition, such systems reduce variability and enhance confidence in maintenance decisions.
For AddQual, however, this evolution goes further.“The industry is starting to see the value of structured inspection,” says Anderson. “Structure alone isn’t enough. The real opportunity lies in what happens to the data — how it’s captured, connected and used to drive action.”bThis philosophy underpins the development of MiDAS (Metrology Integrated Data Automation System), AddQual’s proprietary platform designed to transform inspection from a standalone activity into a fully integrated, data-driven process. By combining automated measurement, structured data capture and intelligent workflows, MiDAS enables manufacturers and MRO providers to move beyond pass/fail outcomes towards a more predictive and responsive model of quality.
Rather than relying on manual interpretation and fragmented datasets, engineers are presented with clear, standardised outputs that accelerate decision-making at every stage of the lifecycle. The result is faster resolution — whether that means progressing a component to repair or confidently removing it from the process.
“MiDAS is about giving engineers clarity,” Anderson explains. “It’s about removing ambiguity, reducing subjectivity and enabling consistent decisions at speed. That’s what unlocks capacity — rather than just more equipment.”
Automation also plays a critical role. Through the integration of robotic systems and AI-assisted analysis, AddQual is working to reduce reliance on manual intervention, improve repeatability and ensure that inspection keeps pace with increasingly automated production and repair environments.
“The risk for MRO providers is that inspection becomes the constraint in an otherwise modernised process,” says Anderson. “If everything else is automated, but inspection remains manual and fragmented, you create a structural bottleneck.” By contrast, a data-centric, automated approach allows inspection to scale alongside demand, while simultaneously improving quality and traceability. Crucially, this is about augmenting human expertise. “Engineers need better data,” Anderson adds.
“AI and automation should support decision-making. The goal is to make the right decision, faster, with greater confidence.” As the aerospace sector continues to invest in digital transformation, the implications are clear. Inspection a strategic lever — one that can either constrain or enable performance across the entire MRO ecosystem.
