Data acquisition
locally, but without better use of data, they do little to address rework, delayed decisions or inconsistent outcomes across the wider system. This is the gap that MiDAS has been designed
to fill. Rather than focusing on increasing inspection volume, the platform transforms how inspection data is used—structuring it, contextualising it, and feeding it back into the decision-making process in real time. By capturing part condition, monitoring process capability and enabling scenario-based analysis, MiDAS allows manufacturers to make faster, evidence-based decisions on whether to pass, repair or scrap components. The effect is a shift away from capacity-
driven thinking towards intelligence-driven performance. Instead of asking how to measure more parts, manufacturers can begin to ask how to make better decisions, earlier in the process. “We challenge our customers with that
example deliberately,” Anderson adds. “Because the answer isn’t always more equipment. Sometimes it’s a different way of thinking—using the data you already have to remove the bottlenecks altogether.” The benefits are already becoming clear.
When bottlenecks appear in qualification and inspection, the instinctive response is often to invest in more hardware—typically additional CMM capacity—to push more parts through the same process. Ben Anderson believes that reaction, while understandable, risks solving the wrong problem. “When operational pressure falls on quality
departments, the default is to buy more CMMs,” he says. “But that’s often just adding capacity to an inefficient system. You’re speeding up the same decisions, not improving them.” Anderson draws on a well-known analogy
here to reframe the conversation. “There’s a famous quote attributed to Henry Ford: ‘If I had asked people what they wanted, they would have said faster horses.’ That’s exactly the situation many manufacturers find themselves in today. The challenge isn’t to make inspection faster in isolation — it’s to rethink what inspection is actually there to do.” This shift is being enabled by the growing
adoption of digital measurement systems, which automatically capture inspection results in structured formats and make them available for analysis. Instead of isolated readings taken on the shop floor, manufacturers can now build continuous datasets that reveal patterns, trends and relationships that would otherwise remain invisible. The real constraint is not measurement capability, but decision capability. More machines may increase throughput
Instrumentation Monthly May 2026
Structured inspection data not only supports faster and more consistent decisions but also accelerates the development of less experienced inspectors, improves audit readiness and provides objective evidence for customers and regulators. In aerospace MRO environments, where
turnaround time and reliability are critical, this can translate directly into competitive advantage. More broadly, the transition from measurement to intelligence is reshaping how manufacturers think about investment. Increasingly, decisions around metrology equipment are being driven not just by accuracy or speed, but by the ability to generate, capture and integrate data within a wider digital ecosystem. The return on investment is no longer measured solely in microns, but in insight. For AddQual, this reflects a wider shift in the role of quality within manufacturing — from a necessary control function to a strategic enabler of performance. “Measurement will always be
fundamental,” Anderson concludes. “But in modern manufacturing, it’s only the starting point. The real value comes from what you do with that data — how you use it to make better decisions, faster. That’s where the next generation of competitive advantage is being built.”
AddQual
www.addqual.com
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