WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures
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3745778.3766662.pdf
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9.41 MB
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Author(s) • • • • • • • • •
Faruqi, Faraz
Paonaskar, Josha
Schuler, Riley
Prevey, Aiden
Taylor, Carson
Tak, Anika
Guinto, Anthony
Shilamkar, Eeshani
Cheenaruenthong, Natarith
Nisser, Martin
Date Issued
November 19, 2025
Publisher
ACM|ACM Symposium on Computational Fabrication
Citation
Faraz Faruqi, Josha Paonaskar, Riley Schuler, Aiden Prevey, Carson Taylor, Anika Tak, Anthony Guinto, Eeshani Shilamkar, Natarith Cheenaruenthong, and Martin Nisser. 2025. WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures. In Proceedings of the ACM Symposium on Computational Fabrication (SCF '25). Association for Computing Machinery, New York, NY, USA, Article 6, 1–15.
Version
Final published version
Abstract
This paper introduces WireBend-kit, a desktop wirebending machine and computational design tool for creating 3D wireframe structures. Combined, they allow users to rapidly and inexpensively create custom 3D wireframe structures from aluminum wire. Our design tool is implemented in freely available software and allows users to generate virtual wireframe designs and assess their fabricability. A path-planning procedure automatically converts the wireframe design into fabrication instructions for our machine while accounting for material elasticity and kinematic error sources. The custom machine costs $293 in parts and can form aluminum wire into 3D wireframe structures through an ordered sequence of feed, bend, and rotate instructions. Our technical evaluation reveals our system’s ability to overcome odometrically accumulating errors inherent to wirebending in order to produce accurate 3D structures from inexpensive hardware. Finally, we provide application examples demonstrating the design space enabled by Wirebend-kit.
Description
SCF ’25, Cambridge, MA, USA
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3745778.3766662