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Load-dependent path planning method for 3D printing of continuous fiber reinforced plastics

Wang, Ting 1; Li, Nanya 1; Link, Guido 1; Jelonnek, John 1; Fleischer, Jürgen 2; Dittus, Jörg 2; Kupzik, Daniel 2
1 Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM), Karlsruher Institut für Technologie (KIT)
2 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

3D printing, to print continuous fiber reinforced plastics (CFRPs) has advantages of manufacturing complex shape and short production cycle. Due to anisotropic mechanical properties of continuous fibers, the paving direction of the fibers determines the mechanical strengths of the printed CFRPs. In this paper, a novel load-dependent path planning (LPP) method has been proposed to generate printing path for CFRPs, which exactly follows the load transmission path of the parts and could provide higher mechanical properties. A topology optimization method is applied to simplify the original disordered load distribution. In the developed Stress Vector Tracing (SVT) algorithm, the printing paths are generated along the load transmission path with the variable spacing of adjacent paths. The LPP method has been compared with the state-of-the-art printing path planning method for continuous fibers and shown better load-bearing and printability.

Postprint §
DOI: 10.5445/IR/1000126267
Veröffentlicht am 13.12.2021
DOI: 10.1016/j.compositesa.2020.106181
Zitationen: 44
Web of Science
Zitationen: 32
Zitationen: 43
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM)
Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 01.2021
Sprache Englisch
Identifikator ISSN: 1359-835X
KITopen-ID: 1000126267
HGF-Programm 34.12.01 (POF III, LK 01) Multiphasen und thermische Prozesse
Weitere HGF-Programme 38.03.02 (POF IV, LK 01) Power-based Fuels and Chemicals
Erschienen in Composites / A
Verlag Elsevier
Band 140
Seiten Article: 106181
Vorab online veröffentlicht am 28.10.2020
Nachgewiesen in Web of Science
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