A Pore Classification System for the Detection of Additive Manufacturing Defects Combining Machine Learning and Numerical Image Analysis
Author:
Affiliation:
1. Leibniz-Institute for Materials Engineering-IWT, Badgasteiner Str. 3, 28359 Bremen, Germany
2. Department of Mathematics and Computer Science, University of Bremen, Bibliothekstr. 5, 28359 Bremen, Germany
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/58/1/122/pdf
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3. Influence of defects on mechanical properties of Ti-6Al-4V components produced by selective laser melting and electron beam melting;Gong;Mater. Des.,2015
4. An investigation into the effect of process parameters on melt pool geometry, cell spacing, and grain refinement during laser powder bed fusion;Keshavarzkermani;Opt. Laser Technol.,2019
5. Effect of energy density on the microstructure and texture evolution of Ti-6Al-4V manufactured by laser powder bed fusion;Potenza;Mater. Charact.,2020
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