Algorithmic Approaches to Interfacing Different Materials Using Inkjet Multi-Material 3D Printers

As the field of multi-material additive manufacturing (AM) advances, fabricated designs have become increasingly complex. As resolution improves, new algorithmic methods are needed to keep up with the exponentially increasing computational demands. To solve this problem, the shader-like "fablet" was developed to procedurally compute patterns voxel-by-voxel on the scale of billions of voxels [11, 12]. Fablets are powerful programs that allow impressive manipulations of the internal structure of voxelized meshes. However, using fablets to process features on the surface of a mesh is a relatively unexplored idea, even though the results can be incredibly useful in additive manufacturing. For example, a persistent challenge in the area of study is how best to interface two materials with different properties across their shared surface that may not bond well on their own. Work has been done with algorithmic approaches to creating composite materials with additive manufacturing - these studies focus on biomimetic patterns that can be applied over a volume to maximize interconnection or realize a particular property [2, 3]. However, little work has been done processing patterns like these fit over entire surfaces of a mesh. In this paper, algorithmic approaches are introduced which allow a user to easily design parts with customized, intricate surface patterns that are much more complex than the inputted meshes themselves, specifically using Inkbit’s Vista printer and software. Using these algorithmic approaches, a user can define a wide variety procedural or handmade patterns applied to the surface of a mesh in order to produce a voxelized representation of the part, as needed by the printer.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Blazes, Christopher

Advisors dc:contributor.advisor

• Durand, Fredo
• Chen, Desai

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/147489

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/147489