Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples.
Despite the advantages of additive manufacturing, its widespread adoption is still hindered by the poor quality of the fabricated parts. Advanced machine learning techniques to predict part quality can improve repeatability and open additive manufacturing to various industries. This study aims to ac...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316600 |
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