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OpenAlex Citation Counts

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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:

A systematic literature review of machine learning methods applied to predictive maintenance
Thyago Peres Carvalho, Fabrízzio Soares, Roberto Oliveira Vita, et al.
Computers & Industrial Engineering (2019) Vol. 137, pp. 106024-106024
Closed Access | Times Cited: 972

Showing 26-50 of 972 citing articles:

Applications of machine learning methods in port operations – A systematic literature review
Siyavash Filom, Amir Mohammad Amiri, Saiedeh Razavi
Transportation Research Part E Logistics and Transportation Review (2022) Vol. 161, pp. 102722-102722
Closed Access | Times Cited: 80
Exploring the remote work challenges in the era of COVID-19 pandemic: review and application model
P. Arunprasad, Chitra Dey, Fedwa Jebli, et al.
Benchmarking An International Journal (2022) Vol. 29, Iss. 10, pp. 3333-3355
Closed Access | Times Cited: 73
Autonomous robot-driven deliveries: A review of recent developments and future directions
Sharan Srinivas, Surya Ramachandiran, Suchithra Rajendran
Transportation Research Part E Logistics and Transportation Review (2022) Vol. 165, pp. 102834-102834
Closed Access | Times Cited: 71
From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry
Marek Molęda, Bożena Małysiak-Mrozek, Weiping Ding, et al.
Sensors (2023) Vol. 23, Iss. 13, pp. 5970-5970
Open Access | Times Cited: 69
Artificial Intelligence for Predictive Maintenance Applications: Key Components, Trustworthiness, and Future Trends
Ayşegül Uçar, Mehmet Karaköse, Necim Kırımça
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 898-898
Open Access | Times Cited: 55
An Artificial Intelligence Approach for Improving Maintenance to Supervise Machine Failures and Support Their Repair
Izabela Rojek, Małgorzata Jasiulewicz–Kaczmarek, Mariusz Piechowski, et al.
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 4971-4971
Open Access | Times Cited: 54
Artificial intelligence in supply chain and operations management: a multiple case study research
Violetta Giada Cannas, Maria Pia Ciano, Mattia Saltalamacchia, et al.
International Journal of Production Research (2023) Vol. 62, Iss. 9, pp. 3333-3360
Open Access | Times Cited: 53
Improved Fault Classification for Predictive Maintenance in Industrial IoT Based on AutoML: A Case Study of Ball-Bearing Faults
Russul H. Hadi, Haider Najy Hady, Ahmed Mudheher Hasan, et al.
Processes (2023) Vol. 11, Iss. 5, pp. 1507-1507
Open Access | Times Cited: 51
Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead
Saima Akhtar, Sulman Shahzad, Asad Zaheer, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4060-4060
Open Access | Times Cited: 49
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Mehdi Saman Azari, Francesco Flammini, Stefania Santini, et al.
IEEE Access (2023) Vol. 11, pp. 12887-12910
Open Access | Times Cited: 42
Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects
M.Y. Arafat, M. J. Hossain, Md Morshed Alam
Renewable and Sustainable Energy Reviews (2023) Vol. 190, pp. 114088-114088
Closed Access | Times Cited: 42
Empirical exploration of predictive maintenance in concrete manufacturing: Harnessing machine learning for enhanced equipment reliability in construction project management
Odey Alshboul, Rabia Emhamed Al Mamlook, Ali Shehadeh, et al.
Computers & Industrial Engineering (2024) Vol. 190, pp. 110046-110046
Closed Access | Times Cited: 30
Dynamic predictive maintenance strategy for system remaining useful life prediction via deep learning ensemble method
Lubing Wang, Zhengbo Zhu, Xufeng Zhao
Reliability Engineering & System Safety (2024) Vol. 245, pp. 110012-110012
Closed Access | Times Cited: 18
Optimizing energy efficiency in data center cooling towers through predictive maintenance and project management
Wisdom Ebirim, Favour Oluwadamilare Usman, Kehinde Andrew Olu-lawal, et al.
World Journal of Advanced Research and Reviews (2024) Vol. 21, Iss. 2, pp. 1782-1790
Open Access | Times Cited: 18
Predictive maintenance in Industry 4.0: A systematic multi-sector mapping
Panagiotis Mallioris, Eirini Aivazidou, Dimitrios Bechtsis
CIRP journal of manufacturing science and technology (2024) Vol. 50, pp. 80-103
Open Access | Times Cited: 16
Proposal for a Sustainable Model for Integrating Robotic Process Automation and Machine Learning in Failure Prediction and Operational Efficiency in Predictive Maintenance
Leonel Patrício, Leonilde Varela, Zilda de Castro Silveira
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 854-854
Open Access | Times Cited: 2
End-to-end lifecycle machine learning framework for predictive maintenance of critical equipment
Jérémie Marchand, Jannik Laval, Aïcha Sekhari, et al.
Enterprise Information Systems (2025)
Closed Access | Times Cited: 1
Revolutionizing Food Quality With Machine Vision and Machine Learning Techniques
MOHAMMED AL RASHED, Shaimaa Fakhry, Radwa Satour
IGI Global eBooks (2025), pp. 71-124
Closed Access | Times Cited: 1
Real-World Anomaly Detection by Using Digital Twin Systems and Weakly Supervised Learning
Andrea Castellani, Sebastian Schmitt, Stefano Squartini
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 7, pp. 4733-4742
Open Access | Times Cited: 114
State of AI-Based Monitoring in Smart Manufacturing and Introduction to Focused Section
Han Ding, Robert X. Gao, Alf Isaksson, et al.
IEEE/ASME Transactions on Mechatronics (2020) Vol. 25, Iss. 5, pp. 2143-2154
Open Access | Times Cited: 110
Reinforcement learning for facilitating human-robot-interaction in manufacturing
Harley Oliff, Ying Liu, Maneesh Kumar, et al.
Journal of Manufacturing Systems (2020) Vol. 56, pp. 326-340
Open Access | Times Cited: 100
Data science applications for predictive maintenance and materials science in context to Industry 4.0
S. M. Sajid, Abid Haleem, Shashi Bahl, et al.
Materials Today Proceedings (2021) Vol. 45, pp. 4898-4905
Closed Access | Times Cited: 97
A novel decision support system for managing predictive maintenance strategies based on machine learning approaches
Simone Arena, E. Florian, Ilenia Zennaro, et al.
Safety Science (2021) Vol. 146, pp. 105529-105529
Closed Access | Times Cited: 95
A Deep Learning Model for Predictive Maintenance in Cyber-Physical Production Systems Using LSTM Autoencoders
Xanthi Bampoula, Georgios Siaterlis, Nikolaos Nikolakis, et al.
Sensors (2021) Vol. 21, Iss. 3, pp. 972-972
Open Access | Times Cited: 93
Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press
Balduíno César Mateus, Mateus Mendes, José Torres Farinha, et al.
Energies (2021) Vol. 14, Iss. 21, pp. 6958-6958
Open Access | Times Cited: 91

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