| Predictive analytics model for power consumption in manufacturing SJ Shin, J Woo, S Rachuri Procedia Cirp 15, 153-158, 2014 | 184 | 2014 |
| Data analytics using simulation for smart manufacturing G Shao, SJ Shin, S Jain Proceedings of the winter simulation conference 2014, 2192-2203, 2014 | 162 | 2014 |
| A conceptual framework for the ubiquitous factory JS Yoon, SJ Shin, SH Suh International Journal of Production Research 50 (8), 2174-2189, 2012 | 143 | 2012 |
| Reincarnation of G-code based part programs into STEP-NC for turning applications SJ Shin, SH Suh, I Stroud Computer-Aided Design 39 (1), 1-16, 2007 | 124 | 2007 |
| Manufacturing data analytics using a virtual factory representation S Jain, G Shao, SJ Shin International Journal of Production Research 55 (18), 5450-5464, 2017 | 121 | 2017 |
| UbiDM: A new paradigm for product design and manufacturing via ubiquitous computing technology SH Suh, SJ Shin, JS Yoon, JM Um International Journal of Computer Integrated Manufacturing 21 (5), 540-549, 2008 | 115 | 2008 |
| STEP-compliant CNC system for turning: Data model, architecture, and implementation SH Suh, DH Chung, BE Lee, S Shin, I Choi, KM Kim Computer-Aided Design 38 (6), 677-688, 2006 | 109 | 2006 |
| Energy efficiency of milling machining: Component modeling and online optimization of cutting parameters SJ Shin, J Woo, S Rachuri Journal of Cleaner Production 161, 12-29, 2017 | 96 | 2017 |
| Developing a big data analytics platform for manufacturing systems: architecture, method, and implementation J Woo, SJ Shin, W Seo, P Meilanitasari The International Journal of Advanced Manufacturing Technology 99 (9), 2193-2217, 2018 | 78 | 2018 |
| A decision-guidance framework for sustainability performance analysis of manufacturing processes DB Kim, SJ Shin, G Shao, A Brodsky The International Journal of Advanced Manufacturing Technology 78, 1455-1471, 2015 | 53 | 2015 |
| Developing a virtual machining model to generate MTConnect machine-monitoring data from STEP-NC SJ Shin, J Woo, DB Kim, S Kumaraguru, S Rachuri International Journal of Production Research 54 (15), 4487-4505, 2016 | 52 | 2016 |
| Real-time anomaly detection using convolutional neural network in wire arc additive manufacturing: molybdenum material HW Cho, SJ Shin, GJ Seo, DB Kim, DH Lee Journal of Materials Processing Technology 302, 117495, 2022 | 51 | 2022 |
| Developing a decision support system for improving sustainability performance of manufacturing processes SJ Shin, DB Kim, G Shao, A Brodsky, D Lechevalier Journal of Intelligent Manufacturing 28, 1421-1440, 2017 | 41 | 2017 |
| Towards a virtual factory prototype S Jain, D Lechevalier, J Woo, SJ Shin 2015 Winter Simulation Conference (WSC), 2207-2218, 2015 | 40 | 2015 |
| Predictive modeling for machining power based on multi-source transfer learning in metal cutting YM Kim, SJ Shin, HW Cho International Journal of Precision Engineering and Manufacturing-Green …, 2022 | 28 | 2022 |
| Decision guidance methodology for sustainable manufacturing using process analytics formalism G Shao, A Brodsky, SJ Shin, DB Kim Journal of Intelligent Manufacturing 28, 455-472, 2017 | 27 | 2017 |
| Simulating a virtual machining model in an agent-based model for advanced analytics D Lechevalier, SJ Shin, S Rachuri, S Foufou, YT Lee, A Bouras Journal of intelligent manufacturing 30, 1937-1955, 2019 | 26 | 2019 |
| A green productivity based process planning system for a machining process SJ Shin, SH Suh, I Stroud International Journal of Production Research 53 (17), 5085-5105, 2015 | 26 | 2015 |
| Standard data-based predictive modeling for power consumption in turning machining SJ Shin, J Woo, S Rachuri, P Meilanitasari Sustainability 10 (3), 598, 2018 | 22 | 2018 |
| A holonic-based self-learning mechanism for energy-predictive planning in machining processes SJ Shin, YM Kim, P Meilanitasari Processes 7 (10), 739, 2019 | 21 | 2019 |
