Unraveling process-microstructure-property correlations in powder-bed fusion additive manufacturing through information-rich surface features with deep learning

• Main Authors: Wang, Chengcheng, Chandra, Shubham, Huang, Sheng, Tor, Shu Beng, Tan, Xipeng
• 其他作者: School of Mechanical and Aerospace Engineering
• 格式: Article
• 語言: English
• 出版: 2023
• 主題: Engineering::Mechanical engineering; Additive Manufacturing; Machine Learning
• 在線閱讀: https://hdl.handle.net/10356/170435
• 機構: Nanyang Technological University

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...