That question was everywhere at 3D CIC 2026. And it drove the conversations that have evolved greatly over the last 10 years of this industry-leading model-based event that Anark has been a part of from the very beginning.
The 3D Collaboration and Interoperability Congress (3D CIC) brings together engineers, manufacturers, standards organizations, and software providers focused on solving real-world challenges in model-based engineering and digital thread interoperability. The event has become one of the most important venues for sharing implementation lessons, advancing open standards, and exploring how model-based data flows across complex engineering ecosystems.
Across nearly every session, one message was clear: Model-based engineering is no longer an experiment. The real challenge now is operationalizing model-based data across systems, organizations, and lifecycle stages.
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.
Many 3D CIC sessions reflected a maturing industry. Less theory. More implementation reality. More hard-earned lessons such as:
In her session, Stephanie Locks (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 and it must be persistent and machine-readable.
Ashley Schmidt (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 and it becomes more embedded in the data itself. The takeaway is clear: digital transformation does not eliminate accountability. It reshapes it.
Max Gravel (Moog Inc.) shared a memorable analogy:
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 Max was providing was consistent with several others 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.
Max also pointed out that there is not a simple connection from Engineering to Manufacturing and Quality. PID's need to be able to trace from Design to different Manufacturing "States" in a way that can streamline processes and provide a level of independence between Engineering and Manufacturing that needs to break a design down into these states while tracking.
David Doody (Ford Motor Company) discussed efforts within Ford’s Powertrain division to fully leverage standards such as STEP 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 and these 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.
Bill Bernstein (Air Force Research Laboratory) talk focused on the challenge of connecting model-based design data with real manufacturing outcomes across the digital thread.
He described a standards-based framework that links the as-designed model to the as-manufactured product using interoperable data formats such as STEP AP242 (design), QIF (quality/inspection), and MTConnect (manufacturing execution).
The key takeaway: using open standards to connect design, manufacturing, and inspection data can make the digital thread more reliable, interoperable, and scalable across heterogeneous manufacturing environments.
Daniel Campbell (Rubypoint) explained how product characteristics such as tolerances, requirements, and inspection attributes can be treated as structured digital objects that connect design, manufacturing, and quality data.
Using the DMSC Model-Based Characteristics (MBC) framework and standards like QIF, these characteristics become traceable across the product lifecycle, improving automation and digital thread continuity.
Karen Wylie & Will Smith (Action Engineering) described the effort to create a reference dataset that aligns with multiple MBD standards to test interoperability across CAD, PLM, quality, and downstream systems. The work highlighted the practical challenges of interpreting standards consistently and building datasets that represent real manufacturing scenarios.
The goal was to provide the industry with a common benchmark model that helps organizations validate tools, workflows, and standards implementations as model-based engineering adoption grows.
Anark has been working with this dataset for a few months now and was so excited about it we made it the backdrop of our new banner stand for 2026. We expect many more conversations on "The Ball Valve" in the coming months. Stay tuned for our version of a standalone HTML file of this model.
Some of the most interesting insights did not come from formal presentations but from conversations happening throughout the conference. Engineers discussed the realities of:
Implementing model-based workflows across multiple CAD systems
Connecting inspection data to design characteristics
Managing persistent identifiers across product lifecycles
Linking manufacturing data back into the digital thread
These organizations are moving beyond pilot projects and the real focus now is operationalizing model-based engineering at enterprise scale.
One of the most unique aspects of 3D CIC is the community itself. Unlike oversized trade shows, the event creates an environment where engineers, standards leaders, and technology providers openly exchange ideas and experiences.
Technical discussions continue long after sessions end at dinner, over drinks and each year, the conference concludes with what has become a tradition of the 3D CIC karaoke night. After several days of deep discussions about digital engineering, attendees gathered for an evening of music and strong renditions of classic rock, hip hop, country and current pop favorites.
It is a reminder that while the challenges of digital engineering are complex, the community solving them remains refreshingly human.
This year’s event also marked an important milestone for the 3D CIC community.
As part of the conference’s 10th anniversary, several attendees were recognized for their long-standing participation in the event and their contributions to advancing model-based engineering practices across industry.
Image: Celebrating a decade of the 3D CIC community. Patrick Dunfey (left) and Jim Martin (right) accepted recognition on behalf of Anark from Jennifer Herron, CEO of Action Engineering.
Anark was honored for ten years of sponsoring and supporting the event, a recognition accepted by Patrick Dunfey, representing Anark’s ongoing commitment to advancing the model-based enterprise.
In addition, Jim Martin, Anark’s Director of Customer Engagement, received recognition for attending all ten years of the conference, a testament to his deep involvement in the model-based engineering community.
Moments like these reflect what makes 3D CIC unique. Beyond the technical sessions and standards discussions, the event has built a tight-knit community of engineers, practitioners, and industry leaders who continue to push model-based engineering forward year after year.
The conversations that begin at 3D CIC rarely end when the conference closes.
From persistent identifiers and interoperability standards to manufacturing data integration and inspection automation, the themes at this year’s conference reflect an industry actively shaping the future of model-based engineering. The model-based enterprise is no longer theoretical.
The next phase of the industry will be defined by how effectively organizations make model-based data:
Interoperable
Governable
Persistent
Usable across the full product lifecycle
And the organizations that solve those challenges will define the next generation of digital engineering.