Phase Change explores opportunities to overcome tooling limitations in the formation of individualized
thermoplastic building components through the development of a speculative additive manufacturing
technology (AMT). Using automated material deposition, the workshop experimented with the translation of the
rigid ideal of computational design space to the soft reality of an uncertain built environment as mediated by the
industrial robotic work cell. In this case, the industrial robot precisely translates the digital geometry but the final
form is characterized by the behavior of the thermoplastic material during deposition and phase-change. The
resulting artifacts emerge from an integration of the precise and the imprecise through a feedback loop between
the digital design environment and the fabricated reality through a series of material experiments using real time
vision sensing technology. Material properties are considered intrinsic to the design process and the robotically
controlled fabrication process is saturated with feedback from the behavioral logics of the material itself.
The exploration of complex material behavior during deposition and phase-change extended to the development
of a novel additive manufacturing technology through the combination of generic robotic manipulators and
custom end effectors aimed at overcoming perceived limitations of scale and production time seen in many
existing AMT. The introduction of additive processes begins to speculate on fabrication scenarios that distance
themselves from current linear file-to-factory methods and industrialized production where the outcome is
precisely defined.
During the development of this informal AM technology, two prototypical production methods were tested. The
first scenario involved a multiple robotic workcell where a single robot deposited stock materials as the second
machine sintered the material into homogenous shapes. While this strategy takes advantage of the controlled
robotic deposition, and localized sintering may offer new design opportunities, it was ultimately at odds with the
desired production rate. The second prototypical process tested a low volume-manufacturing scenario whereby
material is automatically deposited to produce unique elements and uniform sintering occurs in a large format
heating bed or tunnel kiln. Real-time process feedback utilizes comparative vision sensing technology to ensure
the printed component meets intended design criteria such as density and thickness.
Workshop Chairs / Participants
Kadri Tamre, University of Innsbruck
Nathan King, Harvard University Graduate School of Design
Georg Grasser, University of Innsbruck
Galo Moncayo, University of Innsbruck
Chip Clark, Virginia Polytechnic Institute and State University
Shayani Fernando, University of Sydney
Kim Ki Woong, University of Pennsylvania
Matt Culver, University of Tennessee
