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Byung Gun Joung
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Deep learning based approach for identifying conventional machining processes from CAD data
D Peddireddy, X Fu, H Wang, BG Joung, V Aggarwal, JW Sutherland, ...
Procedia Manufacturing 48, 915-925, 2020
272020
Identifying manufacturability and machining processes using deep 3D convolutional networks
D Peddireddy, X Fu, A Shankar, H Wang, BG Joung, V Aggarwal, ...
Journal of Manufacturing Processes 64, 1336-1348, 2021
232021
Development and application of a method for real time motor fault detection
BG Joung, WJ Lee, A Huang, JW Sutherland
Procedia Manufacturing 49, 94-98, 2020
172020
Anomaly detection and inter-sensor transfer learning on smart manufacturing datasets
M Abdallah, BG Joung, WJ Lee, C Mousoulis, N Raghunathan, ...
Sensors 23 (1), 486, 2023
92023
Perspectives on future research directions in green manufacturing for discrete products
MJ Triebe, S Deng, JR Pérez-Cardona, BG Joung, H Wu, N Shakelly, ...
Green Manufacturing Open 1 (IS-J 11,041), 2023
52023
Environmental and economic performance of different maintenance strategies for a product subject to efficiency erosion
WJ Lee, BG Joung, JW Sutherland
Journal of Cleaner Production 389, 135340, 2023
22023
Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management
BG Joung, Z Li, JW Sutherland
International Manufacturing Science and Engineering Conference 85819 …, 2022
2022
A review of research on smart manufacturing in support of environmental sustainability
A Huang, M Triebe, Z Li, H Wu, BG Joung, JW Sutherland
International Journal of Sustainable Manufacturing 5 (2-4), 132-163, 2022
2022
A digital low-dropout (DLDO) regulator with 14dB power supply rejection enhancement
BG Joung, Y Seo, C Kim
2016 International SoC Design Conference (ISOCC), 353-354, 2016
2016
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