A survey on AI-driven digital twins in industry 4.0: Smart manufacturing and advanced robotics Z Huang, Y Shen, J Li, M Fey, C Brecher Sensors 21 (19), 6340, 2021 | 191 | 2021 |
Hybrid learning-based digital twin for manufacturing process: Modeling framework and implementation Z Huang, M Fey, C Liu, E Beysel, X Xu, C Brecher Robotics and Computer-Integrated Manufacturing 82, 102545, 2023 | 30 | 2023 |
Calculation and finite element analysis of the temperature field for high-speed rail bearing based on vibrational characteristics J Xu, J Zhang, Z Huang, L Wang Journal of Vibroengineering 17 (2), 720-732, 2015 | 14 | 2015 |
Edge computing-based virtual measuring machine for process-parallel prediction of workpiece quality in metal cutting Z Huang, M Wiesch, M Fey, C Brecher Procedia CIRP 107, 363-368, 2022 | 5 | 2022 |
Literal-aware knowledge graph embedding for welding quality monitoring: a bosch case Z Tan, B Zhou, Z Zheng, O Savkovic, Z Huang, IG Gonzalez, A Soylu, ... International Semantic Web Conference, 453-471, 2023 | 4 | 2023 |
Prior knowledge-embedded machine learning-driven cutting force monitoring in machinery industry Z Huang, T Xi, M Fey, C Brecher 2022 International Conference on Electrical, Computer and Energy …, 2022 | 4 | 2022 |
Ai-driven digital process twin via networked digital process chain Z Huang, T Xi, M Fey, C Brecher 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf …, 2022 | 1 | 2022 |