Cargando…
Predicting the Printability in Selective Laser Melting with a Supervised Machine Learning Method
Though selective laser melting (SLM) has a rapidly increasing market these years, the quality of the SLM-fabricated part is extremely dependent on the process parameters. However, the current metallographic examination method to find the parameter window is time-consuming and involves subjective ass...
Autores principales: | Chen, Yingyan, Wang, Hongze, Wu, Yi, Wang, Haowei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698234/ https://www.ncbi.nlm.nih.gov/pubmed/33182718 http://dx.doi.org/10.3390/ma13225063 |
Ejemplares similares
-
Printability and Microstructure of Selective Laser Melting of WC/Co/Cr Powder
por: Campanelli, Sabina Luisa, et al.
Publicado: (2019) -
Strategy of Residual Stress Determination on Selective Laser Melted Al Alloy Using XRD
por: Chen, Yujiong, et al.
Publicado: (2020) -
Machine Learning in Predicting Printable Biomaterial Formulations for Direct Ink Writing
por: Chen, Hongyi, et al.
Publicado: (2023) -
A New Method for Automatic Detection of Defects in Selective Laser Melting Based on Machine Vision
por: Lin, Zhenqiang, et al.
Publicado: (2021) -
Selective Laser Melting of Aluminum and Its Alloys
por: Wang, Zhi, et al.
Publicado: (2020)