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Zhang, Ming, Lu, Yang, Hu, Youxi, Amaitik, Nasser and Xu, Yuchun (2022). Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization. Sustainability, 14 (9),

Zhang, Ming, Amaitik, Nasser, Wang, Zezhong, Xu, Yuchun, Maisuradze, Alexander, Peschl, Michael and Tzovaras, Dimitrios (2022). Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction. Applied Sciences, 12 (7),

Amaitik, Nasser, Zhang, Ming, Wang, Zezhong, Xu, Yuchun, Thomson, Gareth A., Xiao, Yiyong, Kolokas, Nikolaos, Maisuradze, Alexander, Garcia, Oscar, Peschl, Michael and Tzovaras, Dimitrios (2022). Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing. Circular Economy and Sustainability ,

Zhang, Ming, Amaitik, Nasser, Xu, Yuchun, Rossini, Rosaria, Bosi, Ilaria and Cedola, Ariel Pablo (2021). A New Implementation of Digital Twins for Fault Diagnosis of Large Industrial Equipment. Journal of Robotics and Mechanical Engineering Research, 1 (1),

Zhang, Ming, Wang, Duo, Amaitik, Nasser and Xu, Yuchun (2022). A Distributional Perspective on Remaining Useful Life Prediction with Deep Learning and Quantile Regression. IEEE Open Journal of Instrumentation and Measurement ,