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Material-agnostic machine learning approach enables high relative density in powder bed fusion products
This study introduces a method that is applicable across various powder materials to predict process conditions that yield a product with a relative density greater than 98% by laser powder bed fusion. We develop an XGBoost model using a dataset comprising material properties of powder and process c...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582079/ https://www.ncbi.nlm.nih.gov/pubmed/37848436 http://dx.doi.org/10.1038/s41467-023-42319-x |