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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:

Prediction and classification of tool wear and its state in sustainable machining of Bohler steel with different machine learning models
Mehmet Erdi Korkmaz, Munish Kumar Gupta, Mustafa Kuntoğlu, et al.
Measurement (2023) Vol. 223, pp. 113825-113825
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Tool wear and its mechanism in turning aluminum alloys with image processing and machine learning methods
Mehmet Erdi Korkmaz, Munish Kumar Gupta, Enes Çeli̇k, et al.
Tribology International (2023) Vol. 191, pp. 109207-109207
Closed Access | Times Cited: 22
A new intelligent approach of surface roughness measurement in sustainable machining of AM-316L stainless steel with deep learning models
Nimel Sworna Ross, Peter Madindwa Mashinini, C. Sherin Shibi, et al.
Measurement (2024) Vol. 230, pp. 114515-114515
Closed Access | Times Cited: 12
Effect of ball nose flank wear on surface integrity in high-speed hard milling of AISI 4340 steel using MQL
Hamed Hassanpour, Amir Rasti, Javad Hashemi Khosrowshahi, et al.
Heliyon (2024), pp. e37337-e37337
Open Access | Times Cited: 5
Prospective research on the tribological behavior of graphdiyne nanofluid and its machine learning performance prediction
Jiaqi He, Chenglong Wang, Huajie Tang, et al.
Applied Surface Science (2025), pp. 162954-162954
Closed Access
Surface quality prediction in abrasive flow machining using ANN model on small data sets
Haiquan Wang, Yiao Guo, Xuanping Wang, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access
Enhanced permeation mechanism and tribological assessment of ultrasonic vibration nanolubricants grinding CFRP
Teng Gao, Jixin Liu, Xiaofeng Sun, et al.
Tribology International (2025) Vol. 204, pp. 110494-110494
Closed Access
Multi-Modal Explainable Artificial Intelligence for neural network-based tool wear detection in machining
Saleh Valizadeh Sotubadi, Shyam Sasi Pallissery, Nguyễn Xuân Vinh
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110141-110141
Closed Access
Advanced Machine Learning Approaches for Predicting Machining Performance in Orthogonal Cutting Process
Syed Asad Shabbir Bukhari, Salman Pervaiz
Lubricants (2025) Vol. 13, Iss. 2, pp. 83-83
Open Access
A Hybrid Algorithm-Based Comparative Analysis of a Newly Designed Tool Holder During the Machining of Hastelloy-B3 with MQL
T. Murali, S. Devendiran, K. Venkatesan
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 3
Application of multi-scale information semi-supervised learning network in vibrating screen operational state recognition
Yuxin Wu, Yang Song, W Wang, et al.
Measurement (2024) Vol. 238, pp. 115264-115264
Closed Access | Times Cited: 3
Bibliometric analysis and research trends in minimum quantity lubrication for reducing cutting forces
Chen Ji, Rui Sheng, Hao Wu, et al.
The International Journal of Advanced Manufacturing Technology (2024)
Closed Access | Times Cited: 3
A State of the Art on Sustainable Metal Working Fluids in Machining Applications
Hakan Yurtkuran, Mustafa Günay, Ritu Rai
Journal of Molecular and Engineering Materials (2024) Vol. 12, Iss. 03
Closed Access | Times Cited: 3
Machine learning models and machinability analysis for comparison of various cooling and lubricating mediums during milling of Hardox 400 steel
Abdullah Aslan
Tribology International (2024) Vol. 198, pp. 109860-109860
Closed Access | Times Cited: 3
Influence of Al2O3/MoS2 hybrid nanofluid MQL on surface roughness, cutting force, tool wear and tool life in hard turning
Tran Bao Ngoc, Trần Minh Đức, Ngô Minh Tuấn, et al.
Forces in Mechanics (2024) Vol. 16, pp. 100285-100285
Open Access | Times Cited: 3
Islanding Detection and Power Quality Diagnosis of Wind Power Integrated Microgrid with Reduced Feature Trained Novel Optimized Random Decision Forest
Sairam Mishra, Ranjan Kumar Mallick, Debadatta Amaresh Gadanayak, et al.
International Journal of Energy Research (2024) Vol. 2024, pp. 1-20
Open Access | Times Cited: 2
Multistep Forecasting Method for Offshore Wind Turbine Power Based on Multi-Timescale Input and Improved Transformer
Anping Wan, Zhipeng Gong, Chao Wei, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 6, pp. 925-925
Open Access | Times Cited: 2
Prediction and formation mechanism of serrated chips in cutting of SA508-3 steel under enhanced cooling and lubrication environments
Qinqiang Wang, Yong Zhao, Chao Zhang, et al.
Tribology International (2024) Vol. 200, pp. 110053-110053
Closed Access | Times Cited: 2
Optimizing end milling parameters for custom 450 stainless steel using ant lion optimization and TOPSIS analysis
C. Devi, Siva Kumar Mahalingam, Róbert Čep, et al.
Frontiers in Mechanical Engineering (2024) Vol. 10
Open Access | Times Cited: 1
A Comparative Study of Two Tree-Based Models for Predicting Flyrock Velocity at Open Pit Bench Mining
Ezatullah Rawnaq, Bassir Esmatyar, Akihiro Hamanaka, et al.
Open Journal of Applied Sciences (2024) Vol. 14, Iss. 02, pp. 267-287
Open Access | Times Cited: 1
Predicting Mechanical Properties of Polymer Materials Using Rate-Dependent Material Models: Finite Element Analysis of Bespoke Upper Limb Orthoses
Syed Hammad Mian, Usama Umer, Khaja Moiduddin, et al.
Polymers (2024) Vol. 16, Iss. 9, pp. 1220-1220
Open Access | Times Cited: 1
Serum klotho associated with thyroid hormone in adults: A population-based cross-sectional research
Xia Zhang, Xuekui Liu, Li Lin, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0301484-e0301484
Open Access | Times Cited: 1
Study of an ISSA-XGBoost model for milling tool wear prediction under variable working conditions
S. -L. Chen, Zengbin Yin, Lei Zheng, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 133, Iss. 5-6, pp. 2761-2774
Closed Access | Times Cited: 1
Predicting tool life and sound pressure levels in dry turning using machine learning models
Alex Fernandes de Souza, Filipe Alves Neto Verri, Paulo Henrique da Silva Campos, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 135, Iss. 7-8, pp. 3777-3793
Closed Access | Times Cited: 1
Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms
Leta Daba Gemechu, Dame Alemayehu Efa, Robsan Abebe
Heliyon (2024) Vol. 10, Iss. 24, pp. e40969-e40969
Closed Access | Times Cited: 1
Knowledge-based intelligent ensemble monitoring method of grit wear in ultrasonic assisted grinding
Lida Zhu, Shaoqing Qin, Yanpeng Hao, et al.
Advanced Engineering Informatics (2024) Vol. 64, pp. 103043-103043
Closed Access | Times Cited: 1
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