标题/作者	年份
Predictive maintenance in the Industry 4.0: A systematic literature review T Zonta, CA Da Costa, R da Rosa Righi, MJ de Lima, ES da Trindade, ... Computers & Industrial Engineering 150, 106889	2020
Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0 ZM Çınar, A Abdussalam Nuhu, Q Zeeshan, O Korhan, M Asmael, ... Sustainability 12 (19), 8211	2020
Challenges to IoT-enabled predictive maintenance for industry 4.0 M Compare, P Baraldi, E Zio IEEE Internet of Things Journal 7 (5), 4585-4597	2019
Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics JJM Jimenez, S Schwartz, R Vingerhoeds, B Grabot, M Salaün Journal of manufacturing systems 56, 539-557	2020
Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry A Theissler, J Pérez-Velázquez, M Kettelgerdes, G Elger Reliability engineering & system safety 215, 107864	2021
Deep learning methods for sensor based predictive maintenance and future perspectives for electrochemical sensors S Namuduri, BN Narayanan, VSP Davuluru, L Burton, S Bhansali Journal of The Electrochemical Society 167 (3), 037552	2020
Maintenance 4.0 technologies–new opportunities for sustainability driven maintenance M Jasiulewicz-Kaczmarek, S Legutko, P Kluk Management and production engineering review 11	2020
Transfer learning for remaining useful life prediction based on consensus self-organizing models Y Fan, S Nowaczyk, T Rögnvaldsson Reliability Engineering & System Safety 203, 107098	2020
Deep reinforcement learning based resource management for DNN inference in industrial IoT W Zhang, D Yang, H Peng, W Wu, W Quan, H Zhang, X Shen IEEE Transactions on Vehicular Technology 70 (8), 7605-7618	2021
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects O Serradilla, E Zugasti, J Rodriguez, U Zurutuza Applied Intelligence 52 (10), 10934-10964	2022
Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review J Leukel, J González, M Riekert Journal of Manufacturing Systems 61, 87-96	2021
An artificial intelligence-based collaboration approach in industrial iot manufacturing: Key concepts, architectural extensions and potential applications P Trakadas, P Simoens, P Gkonis, L Sarakis, A Angelopoulos, ... Sensors 20 (19), 5480	2020
A genetic algorithm optimized RNN-LSTM model for remaining useful life prediction of turbofan engine KT Chui, BB Gupta, P Vasant Electronics 10 (3), 285	2021
Using an autoencoder in the design of an anomaly detector for smart manufacturing AL Alfeo, MGCA Cimino, G Manco, E Ritacco, G Vaglini Pattern Recognition Letters 136, 272-278	2020
Data-driven fault diagnosis for electric drives: A review D Gonzalez-Jimenez, J Del-Olmo, J Poza, F Garramiola, P Madina Sensors 21 (12), 4024	2021
Interpretable Machine Learning: A brief survey from the predictive maintenance perspective S Vollert, M Atzmueller, A Theissler 2021 26th IEEE international conference on emerging technologies and factory …	2021
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
KSPMI: a knowledge-based system for predictive maintenance in industry 4.0 Q Cao, C Zanni-Merk, A Samet, C Reich, FDB De Beuvron, A Beckmann, ... Robotics and Computer-Integrated Manufacturing 74, 102281	2022
DeepHealth: A self-attention based method for instant intelligent predictive maintenance in industrial Internet of Things W Zhang, D Yang, Y Xu, X Huang, J Zhang, M Gidlund IEEE Transactions on Industrial Informatics 17 (8), 5461-5473	2020
A survey on data-driven predictive maintenance for the railway industry N Davari, B Veloso, GA Costa, PM Pereira, RP Ribeiro, J Gama Sensors 21 (17), 5739	2021

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