Open Source Factory: Democratizing Large-Scale Fabrication Systems

  • Zivkovic S
  • Battaglia C
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Abstract

Open source frameworks have enabled widespread access to desktop scale additive manufacturing technology and critical software, but very few large scale or industrial open source equipment platforms exist. As research trajectories continue to move towards large scale experimentation and full scale building construction in the area of robotic and digital fabrication, access to industrial fabrication equipment is critical. Large scale digital fabrication equipment usually requires extensive start-up investments which becomes a prohibitive factor for open research. Expanding on the idea of the Fab Lab as well as the RepRap movement, the Open Source Factory takes advantage of disciplinary expertise and trans-disciplinary knowledge in construction machine design accumulated over the past decade. With the goal to democratize access to large scale industrial fabrication equipment, the paper outlines the creation of two full scale fabrication systems: a RepRap based large scale 3-axis open source CNC gantry and a 6-axis industrial robot system based on a decommissioned Kuka KR200/2. Both machines offer radically different economic frameworks for implementing research in advanced full scale robotic fabrication into contexts of pedagogy, the research lab, practice, or small scale local building industry. The research demonstrates that such equipment can be implemented by building on the current knowledge base in the field. If industrial robots and other large scale fabrication tools become accessible for all, the collective sharing of research and the development of new ideas in the area of full scale robotic building construction can be substantially accelerated.

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APA

Zivkovic, S., & Battaglia, C. (2022). Open Source Factory: Democratizing Large-Scale Fabrication Systems. In Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) (pp. 660–669). ACADIA. https://doi.org/10.52842/conf.acadia.2017.660

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