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    Towards Data and Model Interoperability for Industrial Extended Reality in Manufacturing

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    Date
    5/9/2023 1
    2023-05-09
    Author
    Bernstein, William Z.
    Bowman, Andrew
    Durscher, Ryan
    Gillman, Andrew
    Donegan, Sean
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    Abstract
    Extended reality (XR) technologies have realized significant value for design, manufacturing, and sustainment processes. However, industrial XR, or XR implemented within industrial applications, suffers from scalability and flexibility challenges due to fundamental gaps with interoperability between data, models, and workflows. Though there has been a number of recent efforts to improve the interoperability of industrial XR technologies, progress has been hindered by an innate separation between the domain-specific models (e.g., manufacturing execution data, material specifications, and product manufacturing information) with XR (often-standard) processes (e.g., multiscale spatial representations and data formats optimized for run-time presentation). In this paper, we elaborate on promising research directions and opportunities around which the manufacturing and visualization academic community can rally. To establish such research directions, we (1) conducted a meta-review on well-established state-of-the-art review articles that have already presented in-depth surveys on application areas for industrial XR, such as maintenance, assembly, and inspection and (2) mapped those findings to publicly published priorities from across the US Department of Defense. We hope that our presented research agenda will spur interdisciplinary work across academic silos, i.e., manufacturing and visualization communities, and engages either community within work groups led by the other, e.g., within standards development organizations.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4294504
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