标题/作者	年份
Digital Twin for maintenance: A literature review I Errandonea, S Beltrán, S Arrizabalaga Computers in Industry 123, 103316	2020
A requirements driven digital twin framework: Specification and opportunities J Moyne, Y Qamsane, EC Balta, I Kovalenko, J Faris, K Barton, DM Tilbury IEEE Access 8, 107781-107801	2020
Remaining useful life prediction and predictive maintenance strategies for multi-state manufacturing systems considering functional dependence X Han, Z Wang, M Xie, Y He, Y Li, W Wang Reliability Engineering & System Safety 210, 107560	2021
Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework SS Kamble, A Gunasekaran, H Parekh, V Mani, A Belhadi, R Sharma Technological Forecasting and Social Change 176, 121448	2022
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
Maintenance 4.0 technologies–new opportunities for sustainability driven maintenance M Jasiulewicz-Kaczmarek, S Legutko, P Kluk Management and production engineering review 11	2020
Digital twin design for real-time monitoring–a case study of die cutting machine KJ Wang, YH Lee, S Angelica International Journal of Production Research 59 (21), 6471-6485	2021
A deep learning model for predictive maintenance in cyber-physical production systems using lstm autoencoders X Bampoula, G Siaterlis, N Nikolakis, K Alexopoulos Sensors 21 (3), 972	2021
Digital twin for smart manufacturing: A review of concepts towards a practical industrial implementation L Lattanzi, R Raffaeli, M Peruzzini, M Pellicciari International Journal of Computer Integrated Manufacturing 34 (6), 567-597	2021
Digital twins in product lifecycle for sustainability in manufacturing and maintenance I Rojek, D Mikołajewski, E Dostatni Applied Sciences 11 (1), 31	2020
Intelligent maintenance systems and predictive manufacturing J Lee, J Ni, J Singh, B Jiang, M Azamfar, J Feng Journal of Manufacturing Science and Engineering 142 (11), 110805	2020
Digital twin–driven aero-engine intelligent predictive maintenance M Xiong, H Wang, Q Fu, Y Xu The International Journal of Advanced Manufacturing Technology 114 (11-12 …	2021
Degradation curves integration in physics-based models: Towards the predictive maintenance of industrial robots P Aivaliotis, Z Arkouli, K Georgoulias, S Makris Robotics and computer-integrated manufacturing 71, 102177	2021
Digital twins in human understanding: a deep learning-based method to recognize personality traits J Sun, Z Tian, Y Fu, J Geng, C Liu International Journal of Computer Integrated Manufacturing 34 (7-8), 860-873	2021
End-to-end industrial IoT platform for Quality 4.0 applications IT Christou, N Kefalakis, JK Soldatos, AM Despotopoulou Computers in Industry 137, 103591	2022
A novel predictive maintenance method based on deep adversarial learning in the intelligent manufacturing system C Liu, D Tang, H Zhu, Q Nie IEEE access 9, 49557-49575	2021
Digital Twin models in industrial operations: State‐of‐the‐art and future research directions TY Melesse, V Di Pasquale, S Riemma IET Collaborative Intelligent Manufacturing 3 (1), 37-47	2021
Unified modeling for digital twin of a knowledge-based system design H Wang, H Li, X Wen, G Luo Robotics and Computer-Integrated Manufacturing 68, 102074	2021
User acceptance of virtual reality technology for practicing digital twin-based crisis management PK Kwok, M Yan, T Qu, HYK Lau International Journal of Computer Integrated Manufacturing 34 (7-8), 874-887	2021
Past, present, and future research of digital twin for smart manufacturing YH Son, GY Kim, HC Kim, C Jun, SD Noh Journal of Computational Design and Engineering 9 (1), 1-23	2022

1 - 20

计算机程序会自动估算并确定日期和引用次数。