| 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 | 31 | 2020 |
| 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 | 24 | 2021 |
| 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 | 20 | 2020 |
| 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 | 13 | 2023 |
| 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 | 5 | 2023 |
| 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 | 3 | 2023 |
| Bearing Anomaly Detection in an Air Compressor using an LSTM and RNN-Based Machine Learning Model BG Joung, C Nath, Z Li, JW Sutherland | | 2024 |
| 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 |
