What kind of 3D are we talking about, anyway? Chad Knight argues the case for a cross-industry framework of his own creation, intended to tackle the language barriers that exist between engineers from different disciplines
Over the past several years, I’ve been building a taxonomy and ontology of digital geometry. My goal is to develop this into a framework that the industry can use. At its foundation is something I call ‘the 3D paradigms’, in recognition of the fact that 3D is not one technology, but three.
Entertainment invented one kind to make things look real on screens. Engineering invented a different kind to make machines cut materials precisely. Medicine invented a third kind to capture what’s inside physical bodies. Each industry developed tools, file formats and vocabulary around their own versions and had no reason to align them.
But designing and manufacturing footwear requires aspects of all three. It demands visualisation for marketing and design review, precision surfaces for tooling and manufacturing, and volumetric data for lattices, cushioning simulation and fit analysis. In one product category, we observe three technological traditions that evolved completely separately.
With this in mind, the taxonomy I’ve built provides neutral terminology that spans all three paradigms. It enables people from different backgrounds to talk about geometry without accidentally using words that mean different things in their respective industries.
Overcoming confusion
Here’s what paradigm confusion looks like in practice: A design team builds a shoe model using entertainment software. It’s polygon-based, built to look right on screen, with topology optimised for rendering.
Leadership greenlights samples and the file is sent to engineering, which opens it to find geometry that no machine can interpret, just a shell of approximated facets.
Days are spent rebuilding the entire sole from scratch in NURBS. Everyone asks why. The answer is often framed as a tech issue or a skill gap – but in fact, it’s neither. The two teams were working in fundamentally different geometric paradigms, and nobody had the vocabulary to see the boundary, let alone manage it.
The framework I’ve built gives organisations and practitioners that vocabulary. It classifies geometry by how it’s defined mathematically, not by what software created it or what industry uses it.
The taxonomy starts at the lowest level of geometry: points, curves, surfaces, volumes. It traces how those elements combine into larger constructs, and how different mathematical definitions – explicit, parametric, implicit – encode shape in fundamentally different ways, each with its own strengths and costs.
It also maps the spectrum of creation methods, from manual modelling, through parametric and procedural approaches, to simulation and fully generative systems. Each step delegates more decisions to software and demands different skills to control.
Critically, the taxonomy doesn’t invent classifications from scratch. Instead, it maps against existing industry standards like ISO/STEP for engineering, USD for entertainment, and DICOM and Houdini for medical and volumetrics. That grounding is what allows it to function as neutral territory where those existing structures can finally reference each other.
The goal isn’t to replace anyone’s existing vocabulary. It’s to provide a translation layer where a designer and a manufacturing engineer can identify where their workflows connect and where they don’t.
A shared vocabulary to describe paradigm boundaries doesn’t exist and that’s why so many 3D investments underperform
Why this matters
A shared vocabulary to describe paradigm boundaries doesn’t exist. That’s the core problem and it’s why so many 3D investments underperform.
Organisations experiencing friction in their 3D workflows often can’t diagnose it because they don’t have the language.
Problems at the boundaries look like communication issues, skill gaps or platform failures. They’re none of those things. They’re translation problems, and you can’t solve a translation problem without a dictionary.
This is becoming increasingly important, especially as generative AI models enter the picture, because they don’t naturally output clean polygon topology or NURBS surfaces. They operate in volumetric representations: neural radiance fields, Gaussian splats, implicit functions.
To solve the translation problem, my framework makes visible what’s currently invisible. When a hand-off failure between design and engineering isn’t a people problem but a geometric translation problem, the framework exposes the actual boundary so that it can be addressed. It changes how organisations evaluate investments and it creates a foundation for cross-functional fluency.
The framework is developed, but to span three paradigms, my vision is to build a council for 3D leaders with genuine depth in entertainment pipelines, CAD engineering and volumetric workflows.
If that sounds like your world and this work interests you, I’d welcome the conversation.
About the author:
Chad Knight is former head of 3D design at Nike and now CEO of Super Digital.
For over 15 years, he has worked as a 3D practitioner at major footwear brands, integrating 3D workflows into traditional footwear manufacturing for faster prototyping and complex digital modelling www.linkedin.com/in/chadknight
This article first appeared in DEVELOP3D Magazine
DEVELOP3D is a publication dedicated to product design + development, from concept to manufacture and the technologies behind it all.
To receive the physical publication or digital issue free, as well as exclusive news and offers, subscribe to DEVELOP3D Magazine here
