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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:

Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition
B. D. Deebak, Fadi Al‐Turjman
International Journal of Intelligent Systems (2021) Vol. 37, Iss. 12, pp. 10289-10316
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

Predictive maintenance using digital twins: A systematic literature review
Raymon van Dinter, Bedir Teki̇nerdoğan, Cagatay Catal
Information and Software Technology (2022) Vol. 151, pp. 107008-107008
Open Access | Times Cited: 223
A systematic review of digital twin about physical entities, virtual models, twin data, and applications
Xin Liu, Du Jiang, Bo Tao, et al.
Advanced Engineering Informatics (2023) Vol. 55, pp. 101876-101876
Closed Access | Times Cited: 164
Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises
Shen Yan, Haidong Shao, Yiming Xiao, et al.
Robotics and Computer-Integrated Manufacturing (2022) Vol. 79, pp. 102441-102441
Open Access | Times Cited: 139
A review of digital twin-driven machining: From digitization to intellectualization
Shimin Liu, Jinsong Bao, Pai Zheng
Journal of Manufacturing Systems (2023) Vol. 67, pp. 361-378
Closed Access | Times Cited: 75
A survey of transfer learning for machinery diagnostics and prognostics
Siya Yao, Qi Kang, MengChu Zhou, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 2871-2922
Closed Access | Times Cited: 74
Reference architecture for digital twin-based predictive maintenance systems
Raymon van Dinter, Bedir Teki̇nerdoğan, Cagatay Catal
Computers & Industrial Engineering (2023) Vol. 177, pp. 109099-109099
Open Access | Times Cited: 42
Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Review
Yujiao Hu, Qingmin Jia, Yuan Yao, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 11, pp. 19143-19167
Closed Access | Times Cited: 21
Enhancing four-axis machining center accuracy through interactive fusion of spatiotemporal graph convolutional networks and an error-controlled digital twin system
Lin Zhang, Chi Ma, Jialan Liu
Journal of Manufacturing Processes (2024) Vol. 112, pp. 14-31
Closed Access | Times Cited: 19
Physics-informed machine learning: A comprehensive review on applications in anomaly detection and condition monitoring
Yuandi Wu, Brett Sicard, S. Andrew Gadsden
Expert Systems with Applications (2024) Vol. 255, pp. 124678-124678
Open Access | Times Cited: 15
Digital twin technology in modern machining: A comprehensive review of research on machining errors
Xiangfu Fu, Hyo-Sook Song, Shuo Li, et al.
Journal of Manufacturing Systems (2025) Vol. 79, pp. 134-161
Open Access | Times Cited: 1
TAB-SAPP: A Trust-Aware Blockchain-Based Seamless Authentication for Massive IoT-Enabled Industrial Applications
B. D. Deebak, Fida Hussain Memon, Kapal Dev, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 1, pp. 243-250
Closed Access | Times Cited: 51
Digital Twin for Integration of Design-Manufacturing-Maintenance: An Overview
Fu Yang, Gang Zhu, Ming‐Liang Zhu, et al.
Chinese Journal of Mechanical Engineering (2022) Vol. 35, Iss. 1
Open Access | Times Cited: 51
A comprehensive survey on authentication and secure key management in internet of things: Challenges, countermeasures, and future directions
Patruni Muralidhara Rao, B. D. Deebak
Ad Hoc Networks (2023) Vol. 146, pp. 103159-103159
Closed Access | Times Cited: 38
A review of digital twin technology for electromechanical products: Evolution focus throughout key lifecycle phases
Zhexin Cui, Xiaolang Yang, Jiguang Yue, et al.
Journal of Manufacturing Systems (2023) Vol. 70, pp. 264-287
Closed Access | Times Cited: 23
Tool wear condition monitoring across machining processes based on feature transfer by deep adversarial domain confusion network
Zhiwen Huang, Jiajie Shao, Jianmin Zhu, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 3, pp. 1079-1105
Closed Access | Times Cited: 22
An Efficient Fault Diagnosis Framework for Digital Twins Using Optimized Machine Learning Models in Smart Industrial Control Systems
Samar M. Zayed, Gamal Attiya, Ayman El‐Sayed, et al.
International Journal of Computational Intelligence Systems (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 21
Research progress in machining technology of aerospace thin-walled components
Zhongqun Li, Zhaopeng Zeng, Yang Yu, et al.
Journal of Manufacturing Processes (2024) Vol. 119, pp. 463-482
Closed Access | Times Cited: 12
Methodology and application of digital twin-driven diesel engine fault diagnosis and virtual fault model acquisition
Yaqing Bo, Han Wu, Weifan Che, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107853-107853
Closed Access | Times Cited: 10
An online monitoring method of milling cutter wear condition driven by digital twin
Xintian Zi, Shangshang Gao, Yang Xie
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Adaptive weighted generative adversarial network with attention mechanism: A transfer data augmentation method for tool wear prediction
Jianliang He, Yadong Xu, Yi Pan, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111288-111288
Closed Access | Times Cited: 10
Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application
Shuguo Hu, Changhe Li, Benkai Li, et al.
Intelligent and sustainable manufacturing (2024) Vol. 1, Iss. 1, pp. 10007-10007
Open Access | Times Cited: 10
Review of advances in tool condition monitoring techniques in the milling process
T. Mohanraj, E S Kirubakaran, Dinesh Kumar Madheswaran, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092002-092002
Closed Access | Times Cited: 10
State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies
Sizhe Ma, Katherine A. Flanigan, Mario Bergés
Advanced Engineering Informatics (2024) Vol. 62, pp. 102800-102800
Open Access | Times Cited: 8
Digital twin-driven prognostics and health management for industrial assets
Bin Xiao, Jingshu Zhong, Xiangyu Bao, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
A bio-inspired LIDA cognitive-based Digital Twin architecture for unmanned maintenance of machine tools
Jianhao Lv, Xinyu Li, Yicheng Sun, et al.
Robotics and Computer-Integrated Manufacturing (2022) Vol. 80, pp. 102489-102489
Closed Access | Times Cited: 30
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