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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:

Intelligent monitoring of milling tool wear based on milling force coefficients by prediction of instantaneous milling forces
Defeng Peng, Hongkun Li
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 111033-111033
Closed Access | Times Cited: 12

Showing 12 citing articles:

Improving milling tool wear prediction through a hybrid NCA-SMA-GRU deep learning model
Zhongyuan Che, Chong Peng, T. Warren Liao, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124556-124556
Closed Access | Times Cited: 7
Digital-twin-driven intelligent tracking error compensation of ultra-precision machining
Zhicheng Xu, Baolong Zhang, Dongfang Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 219, pp. 111630-111630
Closed Access | Times Cited: 5
Melt pool control-assisted additive manufacturing of thin-walled parts
Youyu Su, Gang Xu, Xiang Xu, et al.
International Journal of Mechanical Sciences (2024) Vol. 280, pp. 109519-109519
Closed Access | Times Cited: 4
Online tool wear prediction based on cutting force coefficients identification using neural network
Guicheng Wang, Min Wang, Peng Gao, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access
Cutting force estimation based on machine current data-driven mathematical model
Defeng Peng, Hongkun Li, Yuhang Jiang, et al.
Measurement (2025), pp. 117408-117408
Closed Access
Mechanism-informed friction-dynamics coupling GRU neural network for real-time cutting force prediction
Yinghao Cheng, Yingguang Li, Qiyang Zhuang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 221, pp. 111749-111749
Closed Access | Times Cited: 3
Dynamic milling force model considering vibration and tool flank wear width for monitoring tool states in machining of Ti-6AI-4V
Junjin Ma, Yujie Zhang, Jiao Feng, et al.
Journal of Manufacturing Processes (2024) Vol. 124, pp. 1519-1540
Closed Access | Times Cited: 1
Effects of tool orientation and surface curvature on tool wear in ball end milling of 17-4PH stainless steel
Wenbin Ji, H. Shang, Bofan Li, et al.
Research Square (Research Square) (2024)
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
Sustainable Machining: A Case Study on Face Milling of AISI 1045 Steel Using a Multi-Objective Optimization Approach
M. Venkata Roshan, C.S. Sumesh, S. Sakthi Balaji, et al.
International Journal on Interactive Design and Manufacturing (IJIDeM) (2024)
Closed Access
Effects of tool orientation and surface curvature on tool wear in ball end milling of 17-4PH stainless steel
Wenbin Ji, H. Shang, Bofan Li, et al.
The International Journal of Advanced Manufacturing Technology (2024)
Closed Access
Mining method for cutting force coefficient with the impact of tool vibration and machine tool system
Xi Chen, Qi Wang, Wengang Chen, et al.
Advances in Mechanical Engineering (2024) Vol. 16, Iss. 12
Open Access
Prediction of Milling Force During Supercritical Co2 Minimum Quantity Lubrication Milling Process of Niti Smart Alloy
Mingyang Li, Jiaqi Wang, Qingguang Li, et al.
(2024)
Closed Access
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