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    Object Partitioning for Support-Free 3D-Printing

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    Date
    2019
    Author
    Karasik, Eli
    Fattal, Raanan
    Werman, Michael
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    Abstract
    Fused deposition modeling based 3D-printing is becoming increasingly popular due to it's low-cost and simple operation and maintenance. While it produces rugged prints made from a wide range of materials, it suffers from an inherent printing limitation where it cannot produce overhanging surfaces of non-trivial size. This limitation can be handled by constructing temporary support-structures, however this solution involves additional material costs, longer print time, and often a fair amount of labor in removing it. In this paper we present a new method for partitioning general solid objects into a small number of parts that can be printed with no support. The partitioning is computed by applying a sequence of cutting-planes that split the object recursively. Unlike existing algorithms, the planes are not chosen at random, rather they are derived from shape analysis routines that identify and resolve various commonly-found geometric configurations. In addition, we guide this search by a revised set of conditions that both ensure the objects' printability as well as realistically model the printing capabilities of the printer at hand. Evaluation of the new method demonstrates its ability to efficiently obtain support-free partitionings typically containing fewer parts compared to existing methods that rely on support-structures.
    BibTeX
    @article {10.1111:cgf.13639,
    journal = {Computer Graphics Forum},
    title = {{Object Partitioning for Support-Free 3D-Printing}},
    author = {Karasik, Eli and Fattal, Raanan and Werman, Michael},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13639}
    }
    URI
    https://doi.org/10.1111/cgf.13639
    https://diglib.eg.org:443/handle/10.1111/cgf13639
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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