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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 data-driven method based on deep belief networks for backlash error prediction in machining centers
Zhe Li, Yi Wang, Kesheng Wang
Journal of Intelligent Manufacturing (2017) Vol. 31, Iss. 7, pp. 1693-1705
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Intelligent Fault Diagnosis by Fusing Domain Adversarial Training and Maximum Mean Discrepancy via Ensemble Learning
Yibin Li, Yan Song, Lei Jia, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 4, pp. 2833-2841
Closed Access | Times Cited: 295
From data to big data in production research: the past and future trends
Yong‐Hong Kuo, Andrew Kusiak
International Journal of Production Research (2018) Vol. 57, Iss. 15-16, pp. 4828-4853
Open Access | Times Cited: 179
A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment
Zhe Li, Jingyue Li, Yi Wang, et al.
The International Journal of Advanced Manufacturing Technology (2019) Vol. 103, Iss. 1-4, pp. 499-510
Closed Access | Times Cited: 149
In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks
Dongsen Ye, Jerry Ying Hsi Fuh, Yingjie Zhang, et al.
ISA Transactions (2018) Vol. 81, pp. 96-104
Closed Access | Times Cited: 138
Intelligent ball screw fault diagnosis using a deep domain adaptation methodology
Moslem Azamfar, Xiang Li, Jay Lee
Mechanism and Machine Theory (2020) Vol. 151, pp. 103932-103932
Closed Access | Times Cited: 80
Data-informed inverse design by product usage information: a review, framework and outlook
Liang Hou, Jianxin Jiao
Journal of Intelligent Manufacturing (2019) Vol. 31, Iss. 3, pp. 529-552
Closed Access | Times Cited: 77
A survey of deep learning-driven architecture for predictive maintenance
Zhe Li, Qian He, Jingyue Li
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108285-108285
Open Access | Times Cited: 8
Toward Intelligent Machine Tool
Jihong Chen, Pengcheng Hu, Huicheng Zhou, et al.
Engineering (2019) Vol. 5, Iss. 4, pp. 679-690
Open Access | Times Cited: 68
Recurrent feature-incorporated convolutional neural network for virtual metrology of the chemical mechanical planarization process
Ki Bum Lee, Chang Ouk Kim
Journal of Intelligent Manufacturing (2018) Vol. 31, Iss. 1, pp. 73-86
Closed Access | Times Cited: 54
A big data analytics based machining optimisation approach
Wei Ji, Shubin Yin, Lihui Wang
Journal of Intelligent Manufacturing (2018) Vol. 30, Iss. 3, pp. 1483-1495
Open Access | Times Cited: 52
Recent Advances on Machine Learning Applications in Machining Processes
Francesco Aggogeri, Nicola Pellegrini, Franco Luis Tagliani
Applied Sciences (2021) Vol. 11, Iss. 18, pp. 8764-8764
Open Access | Times Cited: 39
Condition Monitoring of Machine Tool Feed Drives: A Review
Quade Butler, Youssef Ziada, David A. Stephenson, et al.
Journal of Manufacturing Science and Engineering (2022) Vol. 144, Iss. 10
Open Access | Times Cited: 27
A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing
Liping Zhao, Bohao Li, Yiyong Yao
Advances in Manufacturing (2023) Vol. 11, Iss. 2, pp. 280-294
Closed Access | Times Cited: 13
Enhanced representation of the nonlinear dynamic characteristics of ball screw feed drive system through developing a three-state model
Min Wan, Dai Jia, Hui Tian, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112371-112371
Closed Access
Enhancing machine tool predictive maintenance: A dual-model approach integrating improved deep autoencoders and graph attention network
Changchun Liu, Dunbing Tang, Haihua Zhu, et al.
Computers & Industrial Engineering (2025), pp. 111048-111048
Closed Access
Framework and case study of cognitive maintenance in Industry 4.0
Bao-rui Li, Yi Wang, Dai Guo-hong, et al.
Frontiers of Information Technology & Electronic Engineering (2019) Vol. 20, Iss. 11, pp. 1493-1504
Closed Access | Times Cited: 37
Exploring the Relationship Between Data Science and Circular Economy: An Enhanced CRISP-DM Process Model
Eivind Kristoffersen, Oluseun Omotola Aremu, Fenna Blomsma, et al.
Lecture notes in computer science (2019), pp. 177-189
Open Access | Times Cited: 32
A Data-driven Digital Twin of CNC Machining Processes for Predicting Surface Roughness
V.S. Vishnu, Kiran George Varghese, B. Gurumoorthy
Procedia CIRP (2021) Vol. 104, pp. 1065-1070
Open Access | Times Cited: 25
A Taxonomy and Archetypes of Business Analytics in Smart Manufacturing
Jonas Wanner, Christopher Wissuchek, Giacomo Welsch, et al.
ACM SIGMIS Database the DATABASE for Advances in Information Systems (2023) Vol. 54, Iss. 1, pp. 11-45
Open Access | Times Cited: 9
Understanding unforeseen production downtimes in manufacturing processes using log data-driven causal reasoning
Christopher Hagedorn, Johannes Huegle, Rainer Schlößer
Journal of Intelligent Manufacturing (2022) Vol. 33, Iss. 7, pp. 2027-2043
Open Access | Times Cited: 14
Fault classification in the process industry using polygon generation and deep learning
Mohamed Elhefnawy, Ahmed Ragab, Mohamed-Salah Ouali
Journal of Intelligent Manufacturing (2021) Vol. 33, Iss. 5, pp. 1531-1544
Closed Access | Times Cited: 19
Product failure detection for production lines using a data-driven model
Ziqiu Kang, Cagatay Catal, Bedir Teki̇nerdoğan
Expert Systems with Applications (2022) Vol. 202, pp. 117398-117398
Closed Access | Times Cited: 12
Automated climate prediction using pelican optimization based hybrid deep belief network for Smart Agriculture
A. Punitha, V. Geetha
Measurement Sensors (2023) Vol. 27, pp. 100714-100714
Open Access | Times Cited: 7
An effective approach for causal variables analysis in diesel engine production by using mutual information and network deconvolution
Wei Qin, Zha Dongye, Jie Zhang
Journal of Intelligent Manufacturing (2018) Vol. 31, Iss. 7, pp. 1661-1671
Closed Access | Times Cited: 21
A gear machining error prediction method based on adaptive Gaussian mixture regression considering stochastic disturbance
Dayuan Wu, Ping Yan, You Guo, et al.
Journal of Intelligent Manufacturing (2021) Vol. 33, Iss. 8, pp. 2321-2339
Closed Access | Times Cited: 16
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