Unraveling process-microstructure-property correlations in powder-bed fusion additive manufacturing through information-rich surface features with deep learning
A machine learning (ML)–based framework has been developed to optimize the process parameters and unravel the paramount process–microstructure–property (PMP) relationships rapidly and precisely, which is demonstrated using electron beam melting (EBM®)-processed Ti–6Al–4V alloy. The process maps are...
Main Authors: | Wang, Chengcheng, Chandra, Shubham, Huang, Sheng, Tor, Shu Beng, Tan, Xipeng |
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Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/170435 |
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