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Aerospace Column
Francois Gau

Aerospace Column  Francois Gau

A true digital thread requires a single, authoritative source of product dimensions and definitions. Not just a pretty 3D CAD. 

What Happens When Quality “Co-Owns” the Digital Thread? 

Francois Gau

Since my early days in manufacturing, I’ve been participating in what is termed “digital twins.” It’s been largely covered and frankly overused in anything from construction planning to flight simulators. 

For us manufacturers, the relevance starts at what was termed “Industry 4.0” 15 years ago. Let’s define it. For our purpose here, we need a digital manufacturing thread, or “digital twin” from a 3D design model (CAD) to a 3D inspection model (CMM) that mirrors the physical part with all features identified and specified. Some go a little further down, like I did at one time with one of my projects: Measuring reality to plan, adjust in real time and attempt to run lights out at zero scrap. 

Since its beginnings, Industry 4.0 has moved from concept to commitment. Manufacturers are investing heavily in digital tools, AI-driven analytics, and IIoT-enabled measuring equipment. 

Yet, as I was at a Top Shops convention a few weeks ago, many leaders are asking a practical question: why does progress feel slower than promised? 

The issue is not technology maturity. It is leadership alignment. Industry 4.0 succeeds only when quality is involved, and perhaps leading, the digital thread. 

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3D Is the Foundation, Not an Add-On 

A true digital thread requires a single, authoritative source of product dimensions and definitions. Not just a pretty 3D CAD. That source is the 3D “model.” In fact, drawings, PDFs, and spreadsheets cannot support the level of automation and connectivity Industry 4.0 demands. 

Since the early 2000s, software companies attempted such a quest. But, like I wrote in my latest column, too many thought the world had to revolve around them and imposed basically the use of their terms. That would not work well with their competitors. And so forth… 

As ASME standard tried to emerge (Y14.41), other ISO and AS standard make use of Model Based Definitions (MDB). In 2013, the U.S. DoD even mandated the use of 3D models. At about the same time the QIF framework came along. Unfortunately, to this day, we still lack a clear interoperable standard and governance. Too many cooks in the kitchen. Some do better than others at ballooning/reading 3D-MBD. 

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Unfortunately, to this day, we still lack a clear interoperable standard and governance. Too many cooks in the kitchen. 

Model-Based Definition (MBD) elevates the CAD model from geometry to governance. Dimensions, GD&T, tolerances, notes, and inspection intent are embedded directly in the model. When implemented correctly, the model becomes the contract—internally and externally. 

This shift matters because downstream systems do not interpret ambiguity well. AI, automation, and analytics require structured data. The 3D model, done right, provides it. 

Quality Must Drive the Bus 

In many organizations, quality is still positioned as a downstream verification function. Inspection confirms what engineering and manufacturing have already decided. That approach breaks the digital thread before it begins. 

Industry 4.0 requires quality participation upstream in the quote process. When quality co-owns the model with engineering, it owns inspection requirements clarity, risk identification, and planning discipline. Inspection becomes confirmation—not discovery. 

This is not a philosophical shift. It is an operational necessity. 

From Quote to Shipment: Model, Model, Model 

The value of MBD is realized across the entire lifecycle: 

  • At the quote stage, structured model data enables accurate assessment of tolerance complexity, inspection effort, and process risk. AI-driven quoting tools depend on this consistency. 
  • During contract review and PO acceptance, the same model validates requirements once again—eliminating redundant interpretation and reducing review cycles. 

Process engineering builds directly from the model. Toolpaths, routings, and work instructions reference the same features that inspection will later verify. ERP systems link operations, control plans, and resources back to model characteristics. 

When machining and inspection execute, there is no translation step. The digital thread remains intact because the model never changes its role. 

Ballooning, Reinvented 

Traditional ballooning extracts inspection characteristics from drawings through manual effort. It is time-consuming and prone to inconsistency. 

MBD enables automated characteristic extraction. Features are already defined. Tolerances are already structured. Inspection plans can be generated, reused, and updated digitally. 

Quality engineers shift focus from documentation to decision-making—prioritizing risk, capability, and control strategy. 

AI and IIoT: Multipliers, Not Replacements 

AI and IIoT do not replace quality fundamentals; they amplify them. 

Machine learning models can analyze inspection data tied directly to model features, identifying trends and predicting risk. Control plans evolve based on evidence, not intuition. 

IIoT-enabled machines and inspection systems feed real-time data back into the digital thread. Process drift is detected earlier. Corrective action occurs before nonconformance becomes scrap. 

None of this is possible without a structured, model-based foundation. 

Conclusion 

  • 3D Model-Based Definition is the backbone of the digital thread. 
  • Industry 4.0 succeeds when quality leads upstream decisions. 
  • MBD enables automated planning and inspection at scale. 
  • AI and IIoT deliver value only when driven by structured model data. 
  • Quality assurance improves when planning and control are equally strong. 

Opening Background and Pull Quote Image Source: gorodenkoff / iStock / Getty Images Plus via Getty Images.

Francois Gau is the CEO of GrowthHive. For more information, email francois@growthhive-strategy.com