Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Torque based defect detection and weld quality modelling in friction stir welding process
Bipul Das, Sukhomay Pal, Swarup Bag
Journal of Manufacturing Processes (2017) Vol. 27, pp. 8-17
Closed Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Machine learning and data mining in manufacturing
Alican Doğan, Derya Birant
Expert Systems with Applications (2020) Vol. 166, pp. 114060-114060
Closed Access | Times Cited: 509
Current Trends and Applications of Machine Learning in Tribology—A Review
Max Marian, Stephan Tremmel
Lubricants (2021) Vol. 9, Iss. 9, pp. 86-86
Open Access | Times Cited: 144
Applications of machine learning in friction stir welding: Prediction of joint properties, real-time control and tool failure diagnosis
Ammar H. Elsheikh
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105961-105961
Closed Access | Times Cited: 135
Weldability of thermoplastic materials for friction stir welding- A state of art review and future applications
Ranvijay Kumar, Rupinder Singh, Inderpreet Singh Ahuja, et al.
Composites Part B Engineering (2017) Vol. 137, pp. 1-15
Closed Access | Times Cited: 134
An automatic welding defect location algorithm based on deep learning
Lei Yang, Huaixin Wang, Benyan Huo, et al.
NDT & E International (2021) Vol. 120, pp. 102435-102435
Closed Access | Times Cited: 95
Artificial Intelligence Applications for Friction Stir Welding: A Review
Berkay Eren, Mehmet Ali Güvenç, Selçuk Mıstıkoğlu
Metals and Materials International (2020) Vol. 27, Iss. 2, pp. 193-219
Closed Access | Times Cited: 80
Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions
Yu Ming Zhang, Yu‐Ping Yang, Wei Zhang, et al.
Journal of Manufacturing Science and Engineering (2020) Vol. 142, Iss. 11
Closed Access | Times Cited: 72
Tribo-informatics approaches in tribology research: A review
Nian Yin, Zhiguo Xing, Ke He, et al.
Friction (2022) Vol. 11, Iss. 1, pp. 1-22
Open Access | Times Cited: 57
Predicting EHL film thickness parameters by machine learning approaches
Max Marian, Jonas Mursak, Marcel Bartz, et al.
Friction (2022) Vol. 11, Iss. 6, pp. 992-1013
Open Access | Times Cited: 40
Towards Friction Stir Remanufacturing of High-Strength Aluminum Components
Xiangchen Meng, Yuming Xie, Xiaotian Ma, et al.
Acta Metallurgica Sinica (English Letters) (2022) Vol. 36, Iss. 1, pp. 91-102
Open Access | Times Cited: 37
A review of recent advances and applications of machine learning in tribology
Abhishek T. Sose, Soumil Y. Joshi, Lakshmi Kumar Kunche, et al.
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 6, pp. 4408-4443
Closed Access | Times Cited: 29
Machine learning-supported manufacturing: a review and directions for future research
Baris Ördek, Yuri Borgianni, Éric Coatanéa
Production & Manufacturing Research (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 13
Monitoring of friction stir welding based on vision system coupled with Machine learning algorithm
S. Sudhagar, M. Sakthivel, P. Ganeshkumar
Measurement (2019) Vol. 144, pp. 135-143
Closed Access | Times Cited: 67
Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review
Uma Maheshwera Reddy Paturi, Suryapavan Cheruku
Materials Today Proceedings (2020) Vol. 38, pp. 2392-2401
Open Access | Times Cited: 59
A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions
Utkarsh Chadha, Senthil Kumaran Selvaraj, Neha Gunreddy, et al.
Material Design & Processing Communications (2022) Vol. 2022, pp. 1-28
Open Access | Times Cited: 36
Defect detection method for high-resolution weld based on wandering Gaussian and multi-feature enhancement fusion
Liangliang Li, Jia Ren, Peng Wang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 199, pp. 110484-110484
Closed Access | Times Cited: 17
A review on phenomenological model subtleties for defect assessment in friction stir welding
Debtanay Das, Swarup Bag, Sukhomay Pal, et al.
Journal of Manufacturing Processes (2024) Vol. 120, pp. 641-679
Closed Access | Times Cited: 7
Machine learning based hierarchy of causative variables for tool failure in friction stir welding
Yong Du, Tuhin Mukherjee, Prasenjit Mitra, et al.
Acta Materialia (2020) Vol. 192, pp. 67-77
Closed Access | Times Cited: 46
A Rapid Learning Model based on Selected Frequency Range Spectral Subtraction for the Data-Driven Fault Diagnosis of Manufacturing Systems
Seungyon Cho, Hea-Ryeon Seo, Geonhwi Lee, et al.
International Journal of Precision Engineering and Manufacturing-Smart Technology (2023) Vol. 1, Iss. 1, pp. 49-62
Closed Access | Times Cited: 13
Optimization of Plasma Welding Sequence and Performance Verification for a Fork Shaft: A Comparison of Same-Direction and Reverse-Direction Welding
Jianguang Yang, Peng Cao, J.S. Yao, et al.
Materials (2025) Vol. 18, Iss. 2, pp. 288-288
Open Access
A review of artificial intelligence techniques for optimizing friction stir welding processes and predicting mechanical properties
Roosvel Soto-Díaz, Mauricio Vásquez‐Carbonell, José Escorcia‐Gutierrez
Engineering Science and Technology an International Journal (2025) Vol. 62, pp. 101949-101949
Closed Access
Prediction of Mechanical Properties and Defect Detection in a TIG Cladded SS 316L by Machine Learning Techniques
Shanmuga Vadivu K R, Vilvanatha Prabu A, K. Sathickbasha
Journal of Alloys and Metallurgical Systems (2025), pp. 100167-100167
Open Access
Machine Learning Algorithms for Manufacturing Quality Assurance: A Systematic Review of Performance Metrics and Applications
Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, et al.
Array (2025), pp. 100393-100393
Open Access
State of the Art Review on Process, System, and Operations Control in Modern Manufacturing
Dragan Djurdjanović, Laine Mears, Farbod Akhavan Niaki, et al.
Journal of Manufacturing Science and Engineering (2017) Vol. 140, Iss. 6
Closed Access | Times Cited: 45
Detection of tunnel defects in friction stir welded aluminum alloy joints based on the in-situ force signal
Wei Guan, Dongxiao Li, Lei Cui, et al.
Journal of Manufacturing Processes (2021) Vol. 71, pp. 1-11
Closed Access | Times Cited: 31
Page 1 - Next Page

Scroll to top