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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:

Optimizing Predictive Maintenance With Machine Learning for Reliability Improvement
Yali Ren
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering (2021) Vol. 7, Iss. 3
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

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 In-Depth Study of Vibration Sensors for Condition Monitoring
Ietezaz Ul Hassan, Krishna Panduru, J. L. Walsh
Sensors (2024) Vol. 24, Iss. 3, pp. 740-740
Open Access | Times Cited: 21
AI-Driven Intelligent Data Analytics and Predictive Analysis in Industry 4.0: Transforming Knowledge, Innovation, and Efficiency
Zhijuan Zong, Yu Guan
Journal of the Knowledge Economy (2024)
Closed Access | Times Cited: 18
PREDICTIVE ANALYTICS IN THE MAINTENANCE AND RELIABILITY OF SATELLITE TELECOMMUNICATIONS INFRASTRUCTURE: A CONCEPTUAL REVIEW OF STRATEGIES AND TECHNOLOGICAL ADVANCEMENTS
Nneka Adaobi Ochuba, Favour Oluwadamilare Usman, Enyinaya Stefano Okafor, et al.
Engineering Science & Technology Journal (2024) Vol. 5, Iss. 3, pp. 704-715
Open Access | Times Cited: 16
Reinforcement learning for predictive maintenance: a systematic technical review
Rajesh Siraskar, Satish Kumar, Shruti Patil, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 11, pp. 12885-12947
Closed Access | Times Cited: 28
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
Low-Temperature NO2 Gas-Sensing System Based on Metal–Organic Framework-Derived In2O3 Structures and Advanced Machine Learning Techniques
Jesse Nii Okai Amu-Darko, Shahid Hussain, Enock Adjei Agyekum, et al.
Inorganic Chemistry (2024) Vol. 63, Iss. 35, pp. 16429-16441
Closed Access | Times Cited: 6
Reshaping Industrial Maintenance with Machine Learning: Fouling Control Using Optimized Gaussian Process Regression
Francesco Negri, Andrea Galeazzi, Francesco Gallo, et al.
Industrial & Engineering Chemistry Research (2025)
Open Access
Predictive Maintenance in Industrial Systems Using Machine Learning
Rishikant Kumar, Manmohan Mishra, Suryali Suman, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 1778-1785
Open Access | Times Cited: 4
Impact analysis of field maintenance practices on reliability metrics
Ahiamadu Jonathan Okirie, Ebigenibo Genuine Saturday, Mathew Izuchukwu Gift, et al.
Maintenance Reliability and Condition Monitoring (2025)
Open Access
Artificial Neural Network Predictions of Heat Transfer of Flat Plate Collector With Hybrid Nanofluids
L. Syam Sundar, Solomon Mesfin, Veeredhi Vasudeva Rao
Advances in chemical and materials engineering book series (2025), pp. 405-432
Closed Access
Advances in Numerical Modeling for Heat Transfer and Thermal Management: A Review of Computational Approaches and Environmental Impacts
Łukasz Łach, Dmytro Svyetlichnyy
Energies (2025) Vol. 18, Iss. 5, pp. 1302-1302
Open Access
Innovative Adaptation of Predictive Maintenance Familiarization Content to Address Contemporary Requirements in Transportation Sector
Georgios Ntanis, Aggelos Aggelakakis, Maria Boile, et al.
Lecture notes in intelligent transportation and infrastructure (2025), pp. 185-204
Closed Access
Predictive Maintenance Algorithms, Artificial Intelligence Digital Twin Technologies, and Internet of Robotic Things in Big Data-Driven Industry 4.0 Manufacturing Systems
Marek Nagy, Marcel Figura, Katarína Valašková, et al.
Mathematics (2025) Vol. 13, Iss. 6, pp. 981-981
Open Access
Machine Learning-Based Maintenance Need Prediction for a Power Station Case Study
Nicolla Fundira, Evangelista Tasiiwa Nyakujipa
Advances in computational intelligence and robotics book series (2025), pp. 133-168
Closed Access
Energy-efficient production scheduling through machine on/off control during preventive maintenance
Guiliang Gong, Raymond Chiong, Qianwang Deng, et al.
Engineering Applications of Artificial Intelligence (2021) Vol. 104, pp. 104359-104359
Closed Access | Times Cited: 29
Predicting the performance of an industrial furnace using Gaussian process and linear regression: A comparison
Andrea Galeazzi, Francesco de Fusco, Kristiano Prifti, et al.
Computers & Chemical Engineering (2023) Vol. 181, pp. 108513-108513
Open Access | Times Cited: 12
Automated Identification of Pavement Structural Distress Using State-of-the-Art Object Detection Models and Nondestructive Testing
Xiaogang Guo, Ning Wang
Journal of Computing in Civil Engineering (2024) Vol. 38, Iss. 4
Closed Access | Times Cited: 3
A Proactive Approach to Fault Tolerance Using Predictive Machine Learning Models in Distributed Systems
Mohammad Haroon, Zeeshan Ali Siddiqui, Mohammad Husain, et al.
International Journal of experimental research and review (2024) Vol. 44, pp. 208-220
Open Access | Times Cited: 3
A Systematic Mapping Study on Machine Learning Techniques Applied for Condition Monitoring and Predictive Maintenance in the Manufacturing Sector
Thuy Linh Jenny Phan, Ingolf Gehrhardt, H. A. David, et al.
Logistics (2022) Vol. 6, Iss. 2, pp. 35-35
Open Access | Times Cited: 12
A Novel Energy Performance-Based Diagnostic Model for Centrifugal Compressor using Hybrid ML Model
Mukhtiar Ali Shar, Masdi Muhammad, Ainul Akmar Mokhtar, et al.
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 11, pp. 14835-14853
Closed Access | Times Cited: 2
Elevating Smart Manufacturing with a Unified Predictive Maintenance Platform: The Synergy Between Data Warehousing, Apache Spark, and Machine Learning
Naijing Su, Shifeng Huang, Chuan‐Jun Su
Sensors (2024) Vol. 24, Iss. 13, pp. 4237-4237
Open Access | Times Cited: 2
Deep Learning Stranded Neural Network Model for the Detection of Sensory Triggered Events
Sotirios Kontogiannis, Theodosios Gkamas, Christos Pikridas
Algorithms (2023) Vol. 16, Iss. 4, pp. 202-202
Open Access | Times Cited: 6
Refinery 4.0, a Review of the Main Challenges of the Industry 4.0 Paradigm in Oil & Gas Downstream
Igor G. Olaizola, Marco Quartulli, Elias Unzueta, et al.
Sensors (2022) Vol. 22, Iss. 23, pp. 9164-9164
Open Access | Times Cited: 10
Martian Energy System Design Considerations
L. Wang, Robert S. Balog
(2024), pp. 1-6
Closed Access | Times Cited: 1
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