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Experiment-Based Process Modeling and Optimization for High-Quality and Resource-Efficient FFF 3D Printing

Elkaseer, Ahmed 1; Schneider, Stella 1; Scholz, Steffen G. ORCID iD icon 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)


This article reports on the investigation of the effects of process parameters and their interactions on as-built part quality and resource-efficiency of the fused filament fabrication 3D printing process. In particular, the influence of five process parameters: infill percentage, layer thickness, printing speed, printing temperature, and surface inclination angle on dimensional accuracy, surface roughness of the built part, energy consumption, and productivity of the process was examined using Taguchi orthogonal array (L50) design of experiment. The experimental results were analyzed using ANOVA and statistical analysis, and the parameters for optimal responses were identified. Regression models were developed to predict different process responses in terms of the five process parameters experimentally examined in this study. It was found that dimensional accuracy is negatively influenced by high values of layer thickness and printing speed, since thick layers of printed material tend to spread out and high printing speeds hinder accurate deposition of the printed material. In addition, the printing temperature, which regulates the viscosity of the used material, plays a significant role and helps to minimize the dimensional error caused by thick layers and high printing speeds, whereas the surface roughness depends very much on surface inclination angle and layer thickness, which together determine the influence of the staircase effect. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000119124
Veröffentlicht am 08.05.2020
DOI: 10.3390/app10082899
Zitationen: 62
Web of Science
Zitationen: 53
Zitationen: 66
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Karlsruhe Nano Micro Facility (KNMF)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2076-3417
KITopen-ID: 1000119124
HGF-Programm 43.22.03 (POF III, LK 01) Printed Materials and Systems
Weitere HGF-Programme 49.01.12 (POF III, LK 02) 3D Printing
Erschienen in Applied Sciences
Verlag MDPI
Band 10
Heft 8
Seiten Article: 2899
Vorab online veröffentlicht am 22.04.2020
Schlagwörter Proposal ID: 2018-021025469; 3DP
Nachgewiesen in Dimensions
Web of Science
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