Data Publication

Python tools for measuring filament defects in embedded 3D printing

Leanne Friedrich Author's orcid, Ross Gunther Author's orcid, Jonathan Seppala Author's orcid
Contact: Jonathan Seppala.
Identifier: doi:10.18434/mds2-2564
Version: 1.0... First Released: 2022-04-25 Revised: 2022-04-25
In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. This repository includes Python code for analyzing and managing images and videos of the printing process during extrusion of single filaments. The zip file contains the state of the code when the associated paper was submitted. The link to the GitHub page goes to version 1.0.0, which is the same as the code attached here. From there, you can also access the current state of the code.

Associated with: L. Friedrich, R. Gunther, J. Seppala, Suppression of filament defects in embedded 3D printing, 2022, submitted for publication
Research Areas
NIST R&D: Mathematics and Statistics: Image and signal processingManufacturing: Process measurement and controlManufacturing: BiomanufacturingManufacturing: Additive manufacturingMaterials: Polymers
Keywords: pythondigital image analysiscomputer vision3D printingadditive manufacturingShow more...
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Data and related material can be found at the following locations:
  GitHub page for version 1.0.1
GitHub page for version 1.0.1
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Version: 1.0... First Released: 2022-04-25 Revised: 2022-04-25
Cite this dataset
Leanne Friedrich, Ross Gunther, Jonathan Seppala (2022), Python tools for measuring filament defects in embedded 3D printing, National Institute of Standards and Technology, https://doi.org/10.18434/mds2-2564 (Accessed 2025-07-03)
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