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Dimensional Errors Due to Overhanging Features in Laser Powder Bed Fusion Parts Made of Ti-6Al-4V

Charles, Amal; Elkaseer, Ahmed; Thijs, Lore; Scholz, Steffen G.

Abstract:
The rise in popularity of Additive Manufacturing technologies and their increased adoption for manufacturing have created a requirement for their fast development and maturity. However,there is still room for improvement when compared with conventional manufacturing in terms of the predictability, quality, and robustness. Statistical analysis has proven to be an excellent tool for developing process knowledge and optimizing different processes efficiently and effectively.This paper uses a novel method for printing overhanging features in Ti-6Al-4V metal parts, by varying process parameters only within the down-facing area, and establishes a methodology for predicting dimensional errors in flat 45◦down-facing surfaces. Using the process parameters laser power, scan speed, scan spacing, scan pattern, and layer thickness, a quadratic regression equation is developed and tested. An Analysis of variance (ANOVA) analysis concluded that, within the down-facing area,the laser power is the most significant process parameter, followed by the layer thickness and scans peed. Comparatively, the scanning pattern is determined to be insignificant, which is explained by the small down-facing area where the various scanning patterns play no role. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000119122
Veröffentlicht am 08.05.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2076-3417
KITopen-ID: 1000119122
HGF-Programm 43.22.03 (POF III, LK 01)
Printed Materials and Systems
Erschienen in Applied Sciences
Band 10
Heft 7
Seiten Article: 2416
Vorab online veröffentlicht am 01.04.2020
Schlagwörter Additive Manufacturing; regression; laser powder bed fusion; statistical analysis
Nachgewiesen in Scopus
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