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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Maintenance optimisation of multicomponent systems using hierarchical coordinated reinforcement learning
Yifan Zhou, Bangcheng Li, Tian Ran Lin
Reliability Engineering & System Safety (2021) Vol. 217, pp. 108078-108078
Closed Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

A prognostic driven predictive maintenance framework based on Bayesian deep learning
Liangliang Zhuang, Ancha Xu, Xiaolin Wang
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109181-109181
Closed Access | Times Cited: 91
A deep reinforcement learning approach for rail renewal and maintenance planning
Reza Karami Mohammadi, Qing He
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108615-108615
Closed Access | Times Cited: 48
Artificial-intelligence-based maintenance decision-making and optimization for multi-state component systems
Van-Thai Nguyen, Phuc Do, Alexandre Vosin, et al.
Reliability Engineering & System Safety (2022) Vol. 228, pp. 108757-108757
Open Access | Times Cited: 48
Reinforcement and deep reinforcement learning-based solutions for machine maintenance planning, scheduling policies, and optimization
Oluwaseyi Ogunfowora, Homayoun Najjaran
Journal of Manufacturing Systems (2023) Vol. 70, pp. 244-263
Open Access | Times Cited: 39
A hybrid CNN-LSTM model for joint optimization of production and imperfect predictive maintenance planning
Hassan Dehghan Shoorkand, Mustapha Nourelfath, Adnène Hajji
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109707-109707
Closed Access | Times Cited: 39
Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning
Pablo G. Morato, C.P. Andriotis, Konstantinos G. Papakonstantinou, et al.
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109144-109144
Open Access | Times Cited: 30
Applications of Reinforcement Learning for maintenance of engineering systems: A review
Alberto Pliego Marugán
Advances in Engineering Software (2023) Vol. 183, pp. 103487-103487
Closed Access | Times Cited: 27
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units
Pegah Rokhforoz, Mina Montazeri, Olga Fink
Reliability Engineering & System Safety (2023) Vol. 232, pp. 109081-109081
Open Access | Times Cited: 23
Importance measure-based maintenance strategy optimization: Fundamentals, applications and future directions in AI and IoT
Hongyan Dui, Xinmin Wu, Shaomin Wu, et al.
Frontiers of Engineering Management (2024) Vol. 11, Iss. 3, pp. 542-567
Closed Access | Times Cited: 13
Multi-agent deep reinforcement learning-based maintenance optimization for multi-dependent component systems
Phuc Do, Van-Thai Nguyen, Alexandre Voisin, et al.
Expert Systems with Applications (2024) Vol. 245, pp. 123144-123144
Open Access | Times Cited: 11
A deep reinforcement learning-driven multi-objective optimization and its applications on aero-engine maintenance strategy
Zeqi Wei, Zhibin Zhao, Zheng Zhou, et al.
Journal of Manufacturing Systems (2024) Vol. 74, pp. 316-328
Closed Access | Times Cited: 9
Deep learning for safety assessment of nuclear power reactors: Reliability, explainability, and research opportunities
Abiodun Ayodeji, Muritala Alade Amidu, Samuel Abiodun Olatubosun, et al.
Progress in Nuclear Energy (2022) Vol. 151, pp. 104339-104339
Open Access | Times Cited: 36
A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities
Qin Zhang, Yu Liu, Tangfan Xiahou, et al.
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109239-109239
Closed Access | Times Cited: 17
Maintenance optimization considering the mutual dependence of the environment and system with decreasing effects of imperfect maintenance
Shuyuan Gan, Hengheng Hu, David W. Coit
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109202-109202
Closed Access | Times Cited: 16
A hybrid deep learning approach to integrate predictive maintenance and production planning for multi-state systems
Hassan Dehghan Shoorkand, Mustapha Nourelfath, Adnène Hajji
Journal of Manufacturing Systems (2024) Vol. 74, pp. 397-410
Open Access | Times Cited: 5
Reinforcement learning based maintenance scheduling of flexible multi-machine manufacturing systems with varying interactive degradation
Jiangxi Chen, Xiaojun Zhou
Reliability Engineering & System Safety (2025), pp. 111018-111018
Closed Access
A hierarchical deep reinforcement learning model with expert prior knowledge for intelligent penetration testing
Qianyu Li, Min Zhang, Yi Shen, et al.
Computers & Security (2023) Vol. 132, pp. 103358-103358
Closed Access | Times Cited: 14
Joint maintenance and spare part ordering from multiple suppliers for multicomponent systems using a deep reinforcement learning algorithm
Meimei Zheng, Zhiyun Su, Dong Wang, et al.
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109628-109628
Closed Access | Times Cited: 14
A deep reinforcement learning approach for repair-based maintenance of multi-unit systems using proportional hazards model
Seyedvahid Najafi, Chi-Guhn Lee
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109179-109179
Closed Access | Times Cited: 13
Deep reinforcement learning for maintenance optimization of a scrap-based steel production line
Waldomiro Alves Ferreira Neto, Cristiano Alexandre Virgínio Cavalcante, Phuc Do
Reliability Engineering & System Safety (2024) Vol. 249, pp. 110199-110199
Open Access | Times Cited: 4
Reinforcement Learning in Reliability and Maintenance Optimization: A Tutorial
Qin Zhang, Yu Liu, Yisha Xiang, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110401-110401
Closed Access | Times Cited: 4
A State-Specific Joint Size, Maintenance, and Inventory Policy for a k-out-of-n Load-Sharing System Subject to Self-Announcing Failures
Shenyu Zhao, Yian Wei, Yao Cheng, et al.
Reliability Engineering & System Safety (2025), pp. 110855-110855
Closed Access
A recursive method for the health assessment of systems using the proportional hazards model
Rui Zheng, Seyedvahid Najafi, Yingzhi Zhang
Reliability Engineering & System Safety (2022) Vol. 221, pp. 108379-108379
Closed Access | Times Cited: 19
Maintenance Policies for Two-Unit Balanced Systems Subject to Degradation
Xiujie Zhao, Ziyu Wang
IEEE Transactions on Reliability (2022) Vol. 71, Iss. 2, pp. 1116-1126
Closed Access | Times Cited: 19
Hierarchical reinforcement learning for transportation infrastructure maintenance planning
Zachary Hamida, James A. Goulet
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109214-109214
Closed Access | Times Cited: 11
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