Cargando…
Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples
Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore th...
Autores principales: | Mengesha, Betelhiem N., Grizzle, Andrew C., Demisse, Wondwosen, Klein, Kate L., Elliott, Amy, Tyagi, Pawan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532521/ https://www.ncbi.nlm.nih.gov/pubmed/37763580 http://dx.doi.org/10.3390/ma16186301 |
Ejemplares similares
-
The usefulness of additive manufacturing (AM) in COVID-19
por: Equbal, Azhar, et al.
Publicado: (2021) -
An effective device to enable consistent scratches for in vitro scratch assays
por: Chen, Sixun, et al.
Publicado: (2023) -
Additive manufacturing-enabled design, manufacturing, and lifecycle performance
por: Peng, Tao, et al.
Publicado: (2020) -
Smart Build-Plate for Metal Additive Manufacturing Processes
por: Hehr, Adam, et al.
Publicado: (2020) -
Structural Integrity of Polymeric Components Produced by Additive Manufacturing (AM)—Polymer Applications
por: Martins, Rui F., et al.
Publicado: (2021)