Carnegie Mellon University
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Soft Technologies

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posted on 2024-12-12, 18:37 authored by Lea AlbaughLea Albaugh

 This work explores soft technologies in computational fabrication: ways of creating with materials that are flexible, dynamic, and/or uncertain. Soft fabrication  systems can be built to work with unusual materials, and to adapt to current and  futures needs; they can be appropriate to a wide variety of contexts, including  those outside of industrial and production work such as materials research labs  or personal creative practice. 

 I develop the lens of “softness” through a combination of technical systems development and design inquiry, resulting in computational fabrication systems  which explore softness at the levels of physical materials, contexts of use, and the  workflows that bridge between them. In documenting the individual systems, I  provide a number of supporting contributions, including techniques for producing complex mechanisms with machine knitting, demonstrations of inexpensive  and easily deployable camera-based sensing for fabrication tasks, and insights  from creative practitioners. Uniting the findings from these, I construct a conceptual frame and a set of system-building tactics that can be used to create flexible  and adaptable computational fabrication systems, with implications for how  complex materials can be used, by whom, and in what contexts 

Funding

CAREER: Interactive Morphing Materials

Directorate for Computer & Information Science & Engineering

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Fostering Aptitudes, Attitudes and Aspirations of Girls in STEM Through 4D Printing of Robotic Materials

Directorate for Computer & Information Science & Engineering

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CHS: Small: Expanding the Design Space for Interactive Objects Through Development of Advanced 3D Printers and Printing Technology

Directorate for Computer & Information Science & Engineering

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Planning Grant: Engineering Research Center for Convergence of Scalable and Sustainable Digital Fabrication of Smart Textiles

Directorate for Engineering

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History

Date

2024-09-01

Degree Type

  • Dissertation

Department

  • Human-Computer Interaction Institute

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Scott Hudson Lining Yao

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