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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:

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

Showing 10 citing articles:

State-of-art, challenges, and outlook on deep hole boring: chatter suppression, tool wear monitoring, and error measurement
Jiefu Sun, Chao Sun, Zheping Yan, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access | Times Cited: 1
Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system
Song Liu, Liang Shi, Wei Xu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Tool wear prediction based on XGBoost feature selection combined with PSO-BP network
Lin Zhang, Yankun Fan, Jinling Tan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
In-situ tool wear condition monitoring during the end milling process based on dynamic mode and abnormal evaluation
Min Chen, Jianwei Mao, Yu Fu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Recent Progress of Chatter Detection and Tool Wear Online Monitoring in Machining Process: A Review and Future Prospects
Feng-ze Qin, Huajun Cao, Guibao Tao, et al.
International Journal of Precision Engineering and Manufacturing-Green Technology (2024) Vol. 12, Iss. 2, pp. 719-748
Closed Access | Times Cited: 2
Smart manufacturing platform based on input-output empirical relationships for process monitoring
Giuseppina Ambrogio, Luigino Filice, Francesco Gagliardi
International Journal of Material Forming (2024) Vol. 17, Iss. 5
Open Access | Times Cited: 1
Tool wear prediction based on kernel principal component analysis and least square support vector machine
Kangping Gao, Xinxin Xu, Shengjie Jiao
Measurement Science and Technology (2024) Vol. 35, Iss. 10, pp. 106129-106129
Closed Access | Times Cited: 1
Integration of Big Data and Machine Learning Solutions as Preventive Maintenance Strategies to Improve Manufacturing Productivity
Bryan Keane, Zhi Min Lim, Ahmed Rafat Elkilany, et al.
Lecture notes in electrical engineering (2024), pp. 11-18
Closed Access
Methodology and Experimental Verification for Predicting the Remaining Useful Life of Milling Cutters Based on Hybrid CNN-LSTM-Attention-PSA
Meilu Zhu, Ji Zhang, Lingfan Bu, et al.
Machines (2024) Vol. 12, Iss. 11, pp. 752-752
Open Access
Cutting force prediction of longitudinal-torsional ultrasonic assisted milling based on synergistic prediction ensemble learning model: A case study on CFRP
Tianming Yan, Lida Zhu, Wentian Shi, et al.
Composites Part A Applied Science and Manufacturing (2024), pp. 108702-108702
Closed Access
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