IMPROVING 3D PRINTED PART QUALITY USING ARTIFICAL NEURAL NETWORKS OF THE GENERATIVE ADVERSARIAL TYPE
Abstract
The challenges for digital manufacturing today are vast. Challenges like reproducibility and
mechanical properties preservation are crucial. Currently, 3D printed parts are affected by each
build setup. The thermal diffusion occurring in the process affects the final product once it has
cooled down.
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Recommended Citation
INC, HP, "IMPROVING 3D PRINTED PART QUALITY USING ARTIFICAL NEURAL NETWORKS OF THE GENERATIVE ADVERSARIAL TYPE", Technical Disclosure Commons, (December 23, 2019)
https://www.tdcommons.org/dpubs_series/2814
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