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Displaying 1 - 8 of 8

Investigating Statistical Correlation Between Multiple In-Situ Monitoring Datasets for Powder Bed Fusion Additive Manufacturing

August 24, 2022
Author(s)
Zhuo Yang, Yan Lu, Milica Perisic, Yande Ndiaye, Adnan Gujjar, Fan-Tien Cheng, Haw-Ching Yang
In-situ measurements provide vast information for additive manufacturing process understanding and real-time control. Data from various monitoring techniques observes different characteristics of a build process. Fusing multi-modal in-situ monitoring data

IN-PROCESS DATA FUSION FOR PROCESS MONITORING AND CONTROL OF METAL ADDITIVE MANUFACTURING

November 17, 2021
Author(s)
Zhuo Yang, Yan Lu, Simin Li, Jennifer Li, Yande Ndiaye, Hui Yang, Sundar Krishnamurty
To accelerate the adoption of Metal Additive Manufacturing (MAM) for production, an understanding of MAM process-structure-property (PSP) relationships is indispensable for quality control. A multitude of physical phenomena involved in MAM necessitates the

Machine Learning based Continuous Knowledge Engineering for Additive Manufacturing

September 19, 2019
Author(s)
Hyunwoong Ko, Yan Lu, Paul W. Witherell, Ndeye Y. Ndiaye
Additive manufacturing (AM) assisted by a digital twin is expected to revolutionize the realization of high-value and high-complexity functional parts on a global scale. With machine learning (ML) introduced in the AM digital twin, AM data are transformed