Generalisable 3D printing error detection and correction via multi-head neural networks

Material extrusion is the most widespread additive manufacturing method but its application in end-use products is limited by vulnerability to errors. Humans can detect errors but cannot provide continuous monitoring or real-time correction. Existing automated approaches are not generalisable across...

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Detalles Bibliográficos
Autores principales: Brion, Douglas A. J., Pattinson, Sebastian W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9378646/
https://www.ncbi.nlm.nih.gov/pubmed/35970824
http://dx.doi.org/10.1038/s41467-022-31985-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9378646/
https://www.ncbi.nlm.nih.gov/pubmed/35970824
http://dx.doi.org/10.1038/s41467-022-31985-y

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