[1] Ahmad, R., & Kamaruddin, S. (2012). An overview of time-based and condition-based maintenance in industrial application. Computers & Industrial Engineering, 63(1), 135-149.
[2] Carvalho, T. P., et al. (2019). A review of machine learning and Internet of Things (IoT) in smart maintenance. Computers in Industry, 107, 100-117.
[3] Fumeo, E., et al. (2015). Machine learning applications in railway asset management: A review. Transportation Research Part C: Emerging Technologies, 72, 53-67.
[4] Heidari, M., et al. (2021). AI-powered predictive maintenance in renewable energy systems: A review. Renewable and Sustainable Energy Reviews, 135, 110239.
[5] Jardine, A. K., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483-1510.
[6] Kusiak, A., et al. (2013). Maintenance optimization of wind turbines using data-driven approaches. Renewable Energy, 45, 11-16.
[7] Na, J., et al. (2020). Predictive maintenance for water management using artificial intelligence: A systematic review. Journal of Environmental Management, 258, 110038.
[8] Nguyen, T., et al. (2022). Artificial intelligence in predictive maintenance: A bibliometric analysis and research agenda. Journal of Manufacturing Technology Management, 33(3), 480-499.
[9] Olejnik, S., et al. (2020). The importance of AI-based maintenance in critical infrastructure. Sustainability, 12(23), 10092.
[10] Ren, X., et al. (2021). Predictive maintenance using deep learning: A case study in wind energy. IEEE Transactions on Industrial Informatics, 17(8), 5486-5495.
[11] Schwabacher, M., & Goebel, K. (2007). A survey of artificial intelligence for prognostics. AAAI Fall Symposium: AI for Prognostics, 1-8.
[12] Van Thienen, P., et al. (2020). AI-based predictive maintenance for water distribution systems: Challenges and opportunities. Water Research, 170, 115353.
[13] Zhang, Q., et al. (2019). Deep learning for predictive maintenance of industrial equipment: A review. IEEE Access, 7, 62624-62634.
[14] Zhao, Z., et al. (2020). An artificial intelligence approach to predictive maintenance for telecommunications. Journal of Telecommunications and Information Technology, 2, 100-111.
[15] Zhou, X., et al. (2022). AI-enabled predictive maintenance for smart energy grids: A review. Energy Reports, 8, 3597-3610.
[16] Zio, E. (2013). Prognostics and health management of industrial equipment: A review. Annual Reviews in Control, 37(1), 1-16.
[17] Zonta, T., et al. (2020). Predictive maintenance in the Industry 4.0: A systematic literature review. Computers & Industrial Engineering, 150, 106889.
