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Zhuo Yang, Jaehyuk Kim, Yan Lu, Albert T. Jones, Paul Witherell, Ho Yeung, Hyunwoong Yang
Metal powder bed fusion-based additive manufacturing (AM) processes have gained widespread adoption for producing complex parts with high performance. However
Hyunwoong Ko, Zhuo Yang, Yande Ndiaye, Paul Witherell, Yan Lu
Data analytics with Machine Learning (ML) and Artificial Intelligence (AI) offers high potential to continuously transform AM data to newfound knowledge of
Zhuo Yang, Brandon Lane, Yan Lu, Ho Yeung, Jaehyuk Kim, Yande Ndiaye, Sundar Krishnamurty
Cooling rate is a decisive index to characterize melt pool solidification and determine local microstructure formation in metal powder bed fusion processes
Jaehyuk Kim, Yan Lu, Zhuo Yang, Hyunwoong Ko, Dongmin Shin, Yosep Oh
Real-time monitoring for Additive Manufacturing (AM) processes can greatly benefit from spatial-temporal modeling using deep learning. However, existing, deep