3D CIC 2026: Notes from the Front Lines of Model-Based Engineering

The conversation at 3D CIC has evolved. As it should on the 10th anniversary of this industry leading model-based event. This article will be updated during the event to capture stories and insights from the event. Check back as this post evolves this week.

This is no longer a conference about whether Model-Based Definition (MBD) drives valuable transformation. That debate is settled. The discussion has shifted to something more operational and more urgent: How do we make model-based data interoperable, persistent, governable, and usable across complex, multi-system enterprises?  Let's dig into how that's actually happening.

Day 1 Recap

Day 1 sessions reflected a maturing industry. Less theory. More implementation reality. More hard-earned lessons.

Below are field notes from Day 1, with additional sections to be added as the event progresses.

Persistent IDs: Driving Machine Readable Data Consistency Across Systems

In her session, Stephanie Locks-Hartle of Lockheed Martin offered a simple but powerful description of Persistent IDs (PID): “PIDs are technically human readable, but they are not human meaningful.”

Persistent IDs are not designed for engineers to interpret manually. They are designed for systems to reference features without ambiguity. Engineering, manufacturing, and inspection systems need to point to the exact same characteristic and know they are referring to the same feature. 

She described PIDs as essentially Social Security numbers for product features.

If automated interoperability and traceability across the digital thread is the goal, feature identity cannot be approximate. It must be persistent and machine-readable.

The role of the “Checker” in the quest for MBD excellence

Ashley Schmidt of Woodward focused on a practical reality that often gets less attention: Design validation by MBD practice experts: The "Checkers" of MBD excellence.

One slide posed a deceptively simple question: When is the checker’s job actually done?

GD&T is functional. Is their job complete? Model structure is good. Job complete? All GD&T is semantically linked. Job complete? (MBD) Human readable and machine readable. Job complete?

The answer across all of these was no, there is always opportunity for the human-in-the-loop "checker" to ensure quality and accuracy.

In drawing-centric workflows, the boundaries of validation were clearer. In structured model-based environments, validation becomes more nuanced. The checker is no longer reviewing a static document but evaluating structured data, feature definitions, and downstream implications.

As model-based workflows scale, governance does not disappear. It becomes more embedded in the data itself.

The takeaway is clear: digital transformation does not eliminate accountability. It reshapes it.

Moving Boulders, Rocks, and Sand: The Scale of Data Complexity

Max Gravel of Moog Inc. shared a memorable analogy:

• Drawings are like moving boulders. All in one, but heavy, and difficult to start over.
• Model-Based Definition is like moving rocks. Easier to move, but a lot of pieces to manage.
• Model-Based Systems Engineering is like moving sand. Highly complex data sets, easy to lose bits of information, data integrity is critical. 

As data becomes more granular and interconnected, the volume and complexity increase exponentially.

He also delivered one of the most direct warnings of the day: “If you’re using advanced technology, including AI, and working with bad or dirty data, you’re just going to hurt yourself faster than you ever have before.”

The message was consistent with several sessions: AI does not compensate for poor data foundations. It amplifies whatever you feed it.

Data quality is no longer a best practice. It is a prerequisite for MBD value.

Standards at Scale: Operationalizing AP242 and QIF

David Doody from Ford Motor Company discussed efforts within Ford’s Powertrain division to fully leverage standards such as AP242 and QIF downstream into automated inspection.

Standards provide the mechanism for interoperability. But implementation within large enterprises introduces additional complexity.

One challenge highlighted was operating within both Siemens and Dassault environments inside the same division. Multi-platform realities introduce friction that standards alone do not eliminate.

The work now is less about defining standards and more about operationalizing them inside real-world system landscapes.

Day 2 to bring more MBD insight

More to follow this week as the event unfolds.