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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:

Detection of accelerated tool wear in turning
Sebastian Bombiński, Joanna Kossakowska, Krzysztof Jemielniak
Mechanical Systems and Signal Processing (2021) Vol. 162, pp. 108021-108021
Open Access | Times Cited: 24

Showing 24 citing articles:

Systematic review on tool breakage monitoring techniques in machining operations
Xuebing Li, Xianli Liu, Caixu Yue, et al.
International Journal of Machine Tools and Manufacture (2022) Vol. 176, pp. 103882-103882
Closed Access | Times Cited: 128
Surface roughness and tool wear monitoring in turning processes through vibration analysis using PSD and GRMS
Roumaissa Bouchama, Mohamed Lamine Bouhalais, Abdelhakim Cherfia
The International Journal of Advanced Manufacturing Technology (2024) Vol. 130, Iss. 7-8, pp. 3537-3552
Closed Access | Times Cited: 7
Leveraging artificial intelligence for real-time indirect tool condition monitoring: From theoretical and technological progress to industrial applications
Delin Liu, Zhanqiang Liu, Bing Wang, et al.
International Journal of Machine Tools and Manufacture (2024) Vol. 202, pp. 104209-104209
Closed Access | Times Cited: 5
Deep-learning-driven intelligent tool wear identification of high-precision machining with multi-scale CNN-BiLSTM-GCN
Zhicheng Xu, Baolong Zhang, Louis Luo Fan, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103234-103234
Closed Access
Tool wear prediction in turning using workpiece surface profile images and deep learning neural networks
Meng Lip Lim, Mohd Naqib Derani, Mani Maran Ratnam, et al.
The International Journal of Advanced Manufacturing Technology (2022) Vol. 120, Iss. 11-12, pp. 8045-8062
Closed Access | Times Cited: 14
Needs, Requirements and a Concept of a Tool Condition Monitoring System for the Aerospace Industry
Sebastian Bombiński, Joanna Kossakowska, Mirosław Nejman, et al.
Sensors (2021) Vol. 21, Iss. 15, pp. 5086-5086
Open Access | Times Cited: 18
Development of a Platform for Learning Cybersecurity Using Capturing the Flag Competitions
Iván Ortiz-Garcés, Rommel Gutierrez, David Guerra, et al.
Electronics (2023) Vol. 12, Iss. 7, pp. 1753-1753
Open Access | Times Cited: 7
Quality, efficiency and sustainability improvement in machining processes using Artificial Intelligence
Lourdes Martinez Molina, Roberto Teti, Eva María Rubio
Procedia CIRP (2023) Vol. 118, pp. 501-506
Open Access | Times Cited: 7
Vibration energy-based indicators for multi-target condition monitoring in milling operations
Lele Bai, Jun Zhang, Erhan Budak, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 284-300
Closed Access | Times Cited: 2
A novel procedure to predict cumulative tool wear in turning based on experimental analysis.
Andrea Abeni, Aldo Attanasio, J.C. Outeiro, et al.
Wear (2024) Vol. 560-561, pp. 205607-205607
Closed Access | Times Cited: 2
Investigation of Gaussian mixture clustering model for online diagnosis of tip-wear in nanomachining
Fei Cheng, Shichen Zhai, Jingyan Dong
Journal of Manufacturing Processes (2022) Vol. 77, pp. 114-124
Closed Access | Times Cited: 11
Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
Usama Umer, Syed Hammad Mian, Muneer Khan Mohammed, et al.
Materials (2022) Vol. 15, Iss. 12, pp. 4059-4059
Open Access | Times Cited: 10
Unsupervised Detection of Tool Breakage: A Novel Approach Based on Time and Sensor Domain Data Analysis
Yufei Gui, Zi–Qiang Lang, Zepeng Liu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-13
Closed Access | Times Cited: 5
Methodology for Tool Wear Detection in CNC Machines Based on Fusion Flux Current of Motor and Image Workpieces
Geovanni Díaz-Saldaña, Roque A. Osornio‐Rios, Israel Zamudio-Ramírez, et al.
Machines (2023) Vol. 11, Iss. 4, pp. 480-480
Open Access | Times Cited: 4
Influence of the Material Mechanical Properties on Cutting Surface Quality during Turning
Il-Seok Kang, Tae‐Ho Lee
Processes (2024) Vol. 12, Iss. 6, pp. 1171-1171
Open Access | Times Cited: 1
Study of the influence of cutting parameters on tool wear and the state of the machined surface
Benattia Bloul, Hélène Chanal, Merzouk Meziane
Advances in Mechanical Engineering (2024) Vol. 16, Iss. 9
Open Access | Times Cited: 1
Effect of Changing Belt Tension on Machining Surface of CNC Lathe Spindle
Il-Seok Kang, Tae‐Ho Lee
Processes (2023) Vol. 11, Iss. 4, pp. 1079-1079
Open Access | Times Cited: 3
Measurement of the Machined Surface Diameter by a Laser Triangulation Sensor and Optimalization of Turning Conditions Based on the Diameter Deviation and Tool Wear by GRA and ANOVA
Jozef Jurko, Martin Miškiv-Pavlík, Vratislav Hladký, et al.
Applied Sciences (2022) Vol. 12, Iss. 10, pp. 5266-5266
Open Access | Times Cited: 4
Analysis of the Suitability of Signal Features for Individual Sensor Types in the Diagnosis of Gradual Tool Wear in Turning
Joanna Kossakowska, Sebastian Bombiński, Krzysztof Ejsmont
Energies (2021) Vol. 14, Iss. 20, pp. 6489-6489
Open Access | Times Cited: 5
Experimental Investigation of Tool Lifespan Evolution During Turning Operation Based on the New Spectral Indicator OLmod
Mohamed Khemissi Babouri, Nouredine Ouelaa, Mohamed Cherif Djamaa, et al.
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 4, pp. 5455-5473
Closed Access | Times Cited: 1
Advances in Research on Tool Wear Online Monitoring Method
Xitong Wu, Guohe Li, Zhihua Shao, et al.
Recent Patents on Engineering (2023) Vol. 18, Iss. 6
Closed Access
Online Tip Damage Diagnosis of Atomic Force Microscope Based on Statistical Pattern Recognition
Min Cai, Fei Cheng, Zizhan Jiang
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 3, pp. 4131-4147
Closed Access
Experimental investigation of tool wear evolution during turning operation based on analysis of vibration and cutting forces signals
Mohamed Khemissi Babouri, Nouredine Ouelaa, Mohamed Cherif Djamaa, et al.
Research Square (Research Square) (2022)
Open Access
Modeling of Sound Generation Mechanism During the Turning Process
Reza Nourizadeh, Mohammad Zareinejad, Seyed Mehdi Rezaei, et al.
Modares Mechanical Engineering (2022) Vol. 22, Iss. 8, pp. 529-539
Open Access
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