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: Leanne Friedrich..
Identifier: doi:10.18434/mds2-2564
Version: 1.0... First Released: 2022-04-25 Revised: 2022-04-25

Abstract

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 Topics: Mathematics and Statistics: Image and signal processing, Manufacturing: Process measurement and control, Manufacturing: Biomanufacturing, Manufacturing: Additive manufacturing, Materials: Polymers    
Subject Keywords: python, digital image analysis, computer vision, 3D printing, additive manufacturing, openCV    

Data Access

These data are public. Access rights statement:
Purchase is not required for data downloading. Users must complete registration form to download data.
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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About This Dataset

Version: 1.0... First Released: 2022-04-25 Revised: 2022-04-25
Cite this dataset
Friedrich, Leanne, Gunther, Ross, Seppala, Jonathan (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 2024-07-15)
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