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Cited by 208

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Improvement of quality of 3D printed objects by elimination of microscopic structural defects in fused deposition modeling

Open access
Gordeev, Evgeniy G., Galushko, Alexey S., Ananikov, Valentine P.·2018·PLOS ONE

Abstract

Additive manufacturing with fused deposition modeling (FDM) is currently optimized for a wide range of research and commercial applications. The major disadvantage of FDM-created products is their low quality and structural defects (porosity), which impose an obstacle to utilizing them in functional prototyping and direct digital manufacturing of objects intended to contact with gases and liquids. This article describes a simple and efficient approach for assessing the quality of 3D printed objects. Using this approach it was shown that the wall permeability of a printed object depends on its geometric shape and is gradually reduced in a following series: cylinder > cube > pyramid > sphere > cone. Filament feed rate, wall geometry and G-code-defined wall structure were found as primary parameters that influence the quality of 3D-printed products. Optimization of these parameters led to an overall increase in quality and improvement of sealing properties. It was demonstrated that high quality of 3D printed objects can be achieved using routinely available printers and standard filaments.

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Metadata

Authors
Gordeev, E. G., Galushko, A. S., & Ananikov, V. P.
Venue
PLOS ONE
Published
2018-06-07
Volume
13
Issue
6
Pages
e0198370
ISSN
1932-6203 (ISSN-L)
OpenAlex
W2805920171
Cited by
208
References
3
FWCI
13.01
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Improvement of quality of 3D printed objects by elimination of microscopic structural defects in fused deposition modeling. https://app.cochat.ai/papers/10.1371/journal.pone.0198370
The paper
Gordeev, E. G., Galushko, A. S., & Ananikov, V. P. (2018). Improvement of quality of 3D printed objects by elimination of microscopic structural defects in fused deposition modeling. PLOS ONE. https://doi.org/10.1371/journal.pone.0198370

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.