Results 61 to 70 of about 41,006 (346)

Influence of Manufacturing Parameters and Post Processing on the Electrical Conductivity of Extrusion-Based 3D Printed Nanocomposite Parts [PDF]

open access: yes, 2020
The influence of manufacturing parameters of filament extrusion and extrusion-based Additive Manufacturing (AM), as well as different post processing techniques, on the electrical conductivity of 3D printed parts of graphene nanoplatelets (GNP ...
Gacía, Joshua   +3 more
core   +2 more sources

Parametric Effects of Fused Filament Fabrication Approach on Surface Roughness of Acrylonitrile Butadiene Styrene and Nylon-6 Polymer

open access: yesMaterials, 2022
This research objective is to optimize the surface roughness of Nylon-6 (PA-6) and Acrylonitrile Butadiene Styrene (ABS) by analyzing the parametric effects of the Fused Filament Fabrication (FFF) technique of Three-Dimensional Printing (3DP) parameters.
Ray Tahir Mushtaq   +4 more
semanticscholar   +1 more source

Digital design of medical replicas via desktop systems: shape evaluation of colon parts [PDF]

open access: yes, 2018
In this paper, we aim at providing results concerning the application of desktop systems for rapid prototyping of medical replicas that involve complex shapes, as, for example, folds of a colon.
Bici, Michele   +7 more
core   +1 more source

Emerging Research in Conductive Materials for Fused Filament Fabrication: A Critical Review

open access: yesAdvanced Engineering Materials, 2022
The progress of Industry 4.0 and the advancement of robotic design are revealing a significant gap in the capabilities of current manufacturing techniques and the selection of materials that are available in electronics.
Dejana Pejak Simunec, A. Sola
semanticscholar   +1 more source

Electromagnetic analysis and performance comparison of fully 3D-printed antennas [PDF]

open access: yes, 2019
In this work, the possibility of directly prototyping antennas by exploiting additive manufacturing 3D-printing technology is investigated. In particular, the availability of printable filaments with interesting conductive properties allows for printing ...
Casula, A.   +8 more
core   +1 more source

Process control testing for fused filament fabrication [PDF]

open access: yesRapid Prototyping Journal, 2017
Purpose The purpose of this research is to determine what tests can be most useful in quality assurance and control when using fused filament fabrication (FFF) 3D printing machines. The quality of the bond between layers is critical for the structural integrity of the fused filament fabricated parts.
Stephen AO, Dalgarno KW, Munguia J
openaire   +3 more sources

3D Printing: Developing Countries Perspectives [PDF]

open access: yes, 2014
For the past decade, 3D printing (3DP) has become popular due to availability of low-cost 3D printers such as RepRap and Fab@Home; and better software, which offers a broad range of manufacturing platform that enables users to create customizable ...
Ishengoma, Fredrick R., Mtaho, Adam B.
core   +1 more source

Alumina Manufactured by Fused Filament Fabrication: A Comprehensive Study of Mechanical Properties and Porosity

open access: yesPolymers, 2022
This article deals with a comprehensive study of the processing and mechanical properties of the ceramic material Al2O3 on Fused Filament Fabrication technology (FFF).
Veronika Truxová   +4 more
semanticscholar   +1 more source

A Parametric Study of Part Distortions in FDM Using 3D FEA [PDF]

open access: yes, 2006
We developed a finite element model to simulate the fused deposition modeling (FDM) process. The model considers the coupled thermal and mechanical analysis and incorporates the element activation function to mimic the additive nature of FDM.
Chou, Y. Kevin, Zhang, Yizhuo
core   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

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