Computational Fabrication and Assembly for In Situ Manufacturing
<|reference_start|>Computational Fabrication and Assembly for In Situ Manufacturing: Fabrication today relies on disparate, large machines spread across industrial facilities. These are operated by domain experts to construct and assemble artefacts in sequential steps from large numbers of parts. This traditional, centralized mass manufacturing paradigm is characterized by large capital costs and inflexibility to changing needs, complex global supply chains hinged on economic and political stability, and waste and over-manufacturing of uniform artefacts that fail to meet the technical and personal needs of today's diverse individuals and use cases. Today, these challenges are particularly severe at points of need, such as the space environment. The space environment is remote and unpredictable, and the ability to manufacture in situ offers unique opportunities to address new challenges as they arise. However, the challenges faced in space are often mirrored on Earth. In hospitals, disaster zones, low resource environments and laboratories, the ability to manufacture customized artefacts at points of need can significantly enhance our ability to respond rapidly to unforeseen events. In this thesis, I introduce digital fabrication platforms with co-developed hardware and software that draw on tools from robotics and human-computer interaction to automate manufacturing of customized artefacts at the point of need. Highlighting three research themes across fabrication machines, modular assembly, and programmable materials, the thesis will cover a digital fabrication platform for producing functional robots, a modular robotic platform for in-space assembly deployed in microgravity, and a method for programming magnetic material to selectively assemble.<|reference_end|>
@article{nisser2024computational,
    title={Computational Fabrication and Assembly for In Situ Manufacturing},
    author={Martin Nisser},
    journal={arXiv preprint arXiv:2405.12436},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12436},
    primaryClass={cs.RO cs.ET}
}