Democratising Design (2025)
Democratising Design
Bridging the divide between imagination and production
Democratising Design
Sketches are the visual cues for AI …
Democratising Design
… becoming functional renders …
Democratising Design
… and tangible reality
Democratising Design
Precision design for customisation
Democratising Design
Freedom of style decisions
Democratising Design
Personal expression for everyday objects
Democratising Design
Maximising use of printer capabilities
Democratising Design
Bridging the divide between imagination and production
Democratising Design
Sketches are the visual cues for AI …
Democratising Design
… becoming functional renders …
Democratising Design
… and tangible reality
Democratising Design
Precision design for customisation
Democratising Design
Freedom of style decisions
Democratising Design
Personal expression for everyday objects
Democratising Design
Maximising use of printer capabilities
Democratising Design (2025)
Exploring Artificial Intelligence and Procedural Modelling in Multi-material 3D Printing
Chantal Teneza
Artificial intelligence (AI) is rapidly transforming the landscape of design. Across disciplines, it offers unprecedented opportunities to simplify complex processes, reduce barriers to entry, and accelerate creativity. Nowhere is this more evident than in additive manufacturing (AM), where AI is beginning to change how designers imagine, model, and ultimately produce physical objects. Among the most promising areas of AM is multimaterial 3D printing (MMP), a process that allows the creation of objects composed of multiple materials within a single print. This technology makes it possible to combine varied textures, colours, and physical properties—from flexible to rigid, or opaque to translucent—in ways that were previously unattainable.
Yet despite its potential, multimaterial printing remains largely inaccessible to many designers, artists, and makers. The reason is not the hardware itself, but the steep technical learning curve imposed by traditional computer-aided design (CAD) systems. To harness the full capability of MMP, users must engage with complex procedural modelling software, mastering layers of technical detail before their creative visions can be realised. As a result, access to these advanced tools is often restricted to highly trained professionals, limiting the broader adoption of what should be a transformative design process. The rise of large language models (LLMs) is beginning to shift this dynamic. These models already help users generate and refine two-dimensional concepts with ease, offering more intuitive ways to sketch, iterate, and communicate ideas. However, moving from a 2D vision to a precise, manufacturable 3D file remains a formidable challenge. The existing procedural modelling tools—such as Blender and Houdini—are powerful but intimidating, requiring expert knowledge of geometry, textures, and digital workflows. For many, the complexity of these systems stands in sharp contrast to the apparent simplicity of AI-driven ideation.
This research sought to address that gap by exploring Vizcom, an AI platform built by and for Industrial Designers, alongside the Stratasys J850, the only 3D printer currently able to combine multiple colours, transparency, and material flexibility within a single object.
Vizcom allows designers to create striking 2D renders composed of pixels, but these remain digital images on a screen. The J850, working with voxels—the three-dimensional counterpart of pixels—can translate those renders into tangible objects, preserving fine detail and material qualities. By linking intuitive AI tools with advanced voxel-based printing, the research tested how effectively 2D visions can become 3D realities, and how far AI can go in bridging the divide between imagination and production.
One key limitation emerged clearly: while AI platforms excel at generating images that convey colours, textures, and forms, these outputs are not immediately compatible with 3D printers. They lack the structured data needed to communicate physical properties such as hardness, flexibility, or layered composition. To make these AI-generated designs printable, they must still be “translated” through procedural modelling tools—a process that reintroduces the very technical barriers that AI was meant to reduce.
Nevertheless, the findings demonstrated genuine promise. With careful integration, it is possible to create workflows where a designer’s two-dimensional vision is transformed more intuitively into a tangible three-dimensional reality. This does not eliminate the need for technical expertise altogether, but it shows a pathway toward democratising access to advanced manufacturing technologies. By combining AI-driven creativity with supportive design platforms and state-of-the-art hardware, the future of multimaterial 3D printing may become more inclusive, accessible, and imaginative than ever before.
This project was supported by the New Zealand Product Accelerator and MADE research group.
Materials and Processes
Software
Vizcom, Houdini, Blender, GrabCAD
Hardware
Stratasys J850
Project Level:
Master of Design Innovation (MDI) thesis, supervisor Ross Stevens
