Metrology
CLOSING THE MANUFACTURING DATA GAP BETWEEN DESIGN, PRODUCTION AND INSPECTION
By Ian Mottashed, product manager PC-DMIS, Hexagon D 48
igitalisation has transformed manufacturing, with advanced CAD, CAM and metrology systems now standard across production environments. Engineers can design complex components, generate
automated machining strategies and verify parts to micron-level accuracy.
However, a critical challenge remains: ensuring that product data flows consistently between design, production and inspection systems. Disconnected data workflows continue to create inefficiencies, introduce risk and limit traceability – issues that become more pronounced as product complexity and quality requirements increase.
THE REALITY OF DISCONNECTED DIGITAL WORKFLOWS
In theory, modern digital manufacturing should enable seamless data flow from CAD to the shop floor and into inspection.
In practice, many organisations still operate with fragmented systems.
Design engineers develop detailed 3D models containing geometry and product manufacturing information (PMI), including GD&T, tolerances and feature definitions. Yet downstream teams often rely on 2D drawings or neutral file exports to interpret this information.
Manufacturing engineers extract dimensions to generate machining programmes, while quality teams frequently recreate inspection routines manually within metrology software. This repeated interpretation introduces inefficiencies
and increases the risk of deviation from original design intent. When issues arise, root cause analysis becomes more complex due to inconsistent or duplicated data.
MANUAL GD&T HANDLING: A PERSISTENT BOTTLENECK
One of the most significant sources of inefficiency lies in the handling of GD&T and PMI. Despite being embedded in CAD models, this information is often manually re-entered into downstream systems. For inspection engineers, this means recreating tolerances and feature relationships within metrology platforms; for manufacturing engineers, it involves interpreting tolerances to define process parameters. This approach presents two clear challenges:
Engineering inefficiency – time is spent recreating existing data rather than adding value
Risk of error – misinterpretation of complex GD&T can lead to non-conformance and rework
“For engineers working in measurement, control and instrumentation, ensuring seamless data flow is key to improving both quality and efficiency.”
As component complexity increases, these risks escalate – particularly in high-precision sectors where measurement accuracy is critical.
INTEROPERABILITY AND DATA INTEGRITY CHALLENGES
Modern manufacturing environments rely on multiple software platforms, including CAD, CAM, metrology and PLM systems.
While geometric data transfer is generally well supported, the semantic layer – GD&T, datums, feature relationships – often does not translate reliably between systems.
For metrology applications, this is a critical limitation. Inspection software must interpret not only geometry but also the tolerances that define acceptable variation.
Traditional formats such as STEP support geometry exchange but may not fully preserve model-based product information required for automated inspection programming. As a result, engineers frequently need to reconstruct this data manually, reducing efficiency and increasing the potential for error.
ENABLING DIGITAL CONTINUITY WITH MBD AND QIF
To address these challenges, manufacturers are increasingly adopting model-based definition (MBD) and standards-based data exchange frameworks such as the Quality Information Framework (QIF).
MBD establishes the 3D CAD model as the single source of truth by embedding GD&T definitions, feature characteristics, annotations and notes, as well as material and process requirements directly into the model. This eliminates reliance on separate drawings
August 2026 Instrumentation Monthly
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72
