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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:

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: 61

Showing 1-25 of 61 citing articles:

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control
Sachin Kumar, T. Gopi, N. Harikeerthana, et al.
Journal of Intelligent Manufacturing (2022) Vol. 34, Iss. 1, pp. 21-55
Open Access | Times Cited: 151
Comparison of k-nearest Neighbor & Artificial Neural Network prediction in the mechanical properties of aluminum alloys
M. Arunadevi, M. Suvarchala Rani, R. Sibinraj, et al.
Materials Today Proceedings (2023)
Closed Access | Times Cited: 52
Automatic fruit picking technology: a comprehensive review of research advances
Jun Zhang, Ningbo Kang, Qianjin Qu, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
Open Access | Times Cited: 27
A novel decision support system for managing predictive maintenance strategies based on machine learning approaches
Simone Arena, E. Florian, Ilenia Zennaro, et al.
Safety Science (2021) Vol. 146, pp. 105529-105529
Closed Access | Times Cited: 98
A comprehensive review: Machine learning and its application in integrated power system
Aanand Kumbhar, Pravin G. Dhawale, Shobha Kumbhar, et al.
Energy Reports (2021) Vol. 7, pp. 5467-5474
Open Access | Times Cited: 75
Tool wear monitoring of TC4 titanium alloy milling process based on multi-channel signal and time-dependent properties by using deep learning
Boling Yan, Lida Zhu, Yichao Dun
Journal of Manufacturing Systems (2021) Vol. 61, pp. 495-508
Closed Access | Times Cited: 65
Applications of Machine Learning in Process Monitoring and Controls of L-PBF Additive Manufacturing: A Review
Dalia Mahmoud, Marcin Magolon, Jan Boer, et al.
Applied Sciences (2021) Vol. 11, Iss. 24, pp. 11910-11910
Open Access | Times Cited: 60
Determination of ductile fracture properties of 16MND5 steels under varying constraint levels using machine learning methods
Xingyue Sun, Zheng Liu, Xin Wang, et al.
International Journal of Mechanical Sciences (2022) Vol. 224, pp. 107331-107331
Closed Access | Times Cited: 40
Security in modern manufacturing systems: integrating blockchain in artificial intelligence-assisted manufacturing
Dhruv Patel, Chandan K. Sahu, Rahul Rai
International Journal of Production Research (2023) Vol. 62, Iss. 3, pp. 1041-1071
Closed Access | Times Cited: 26
A conceptual framework for machine learning algorithm selection for predictive maintenance
Simone Arena, Eleonora Florian, Fabio Sgarbossa, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108340-108340
Open Access | Times Cited: 14
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
Advancing energy efficiency: Machine learning based forecasting models for integrated power systems in food processing company
Seray MİRASÇI, Sara Uygur, Aslı Aksoy
International Journal of Electrical Power & Energy Systems (2025) Vol. 165, pp. 110445-110445
Open Access | Times Cited: 1
Advanced big-data/machine-learning techniques for optimization and performance enhancement of the heat pipe technology – A review and prospective study
Zhangyuan Wang, Xudong Zhao, Zhonghe Han, et al.
Applied Energy (2021) Vol. 294, pp. 116969-116969
Open Access | Times Cited: 42
Density Prediction in Powder Bed Fusion Additive Manufacturing: Machine Learning-Based Techniques
Meet Gor, Aashutosh Dobriyal, Vishal Ashok Wankhede, et al.
Applied Sciences (2022) Vol. 12, Iss. 14, pp. 7271-7271
Open Access | Times Cited: 37
Recognition of penetration state in GTAW based on vision transformer using weld pool image
Zhenmin Wang, Haoyu Chen, Qiming Zhong, et al.
The International Journal of Advanced Manufacturing Technology (2022) Vol. 119, Iss. 7-8, pp. 5439-5452
Closed Access | Times Cited: 29
Estimation of machinability performance in wire-EDM on titanium alloy using neural networks
Uma Maheshwera Reddy Paturi, Suryapavan Cheruku, Sriteja Salike, et al.
Materials and Manufacturing Processes (2022) Vol. 37, Iss. 9, pp. 1073-1084
Closed Access | Times Cited: 26
Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology
Uma Maheshwera Reddy Paturi, N.S. Reddy, Suryapavan Cheruku, et al.
Surface and Coatings Technology (2021) Vol. 422, pp. 127559-127559
Closed Access | Times Cited: 31
Deep learning-based optimization for motion planning of dual-arm assembly robots
Kuo‐Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, et al.
Computers & Industrial Engineering (2021) Vol. 160, pp. 107603-107603
Closed Access | Times Cited: 30
A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures
Tae Wook Heo, Saad A. Khairallah, Rongpei Shi, et al.
Journal of Physics Materials (2021) Vol. 4, Iss. 3, pp. 034012-034012
Open Access | Times Cited: 28
Role of Machine Learning in Additive Manufacturing of Titanium Alloys—A Review
Uma Maheshwera Reddy Paturi, Sai Teja Palakurthy, Suryapavan Cheruku, et al.
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 8, pp. 5053-5069
Closed Access | Times Cited: 13
Post Weld Heat Treatment Optimization of Dissimilar Friction Stir Welded AA2024-T3 and AA7075-T651 Using Machine Learning and Metaheuristics
Pinmanee Insua, Wasawat Nakkiew, Warisa Wisittipanich
Materials (2023) Vol. 16, Iss. 5, pp. 2081-2081
Open Access | Times Cited: 11
Predictions of in-situ melt pool geometric signatures via machine learning techniques for laser metal deposition
Jiayu Ye, Alireza Bab‐Hadiashar, Reza Hoseinnezhad, et al.
International Journal of Computer Integrated Manufacturing (2022) Vol. 36, Iss. 9, pp. 1345-1361
Open Access | Times Cited: 17
Performance Monitoring of Wind Turbines Gearbox Utilising Artificial Neural Networks — Steps toward Successful Implementation of Predictive Maintenance Strategy
Basheer Shaheen, István Németh
Processes (2023) Vol. 11, Iss. 1, pp. 269-269
Open Access | Times Cited: 10
Adaptive process parameters decision-making in robotic grinding based on meta-reinforcement learning
Jie Pan, Fan Chen, Dan Han, et al.
Journal of Manufacturing Processes (2025) Vol. 137, pp. 376-396
Closed Access
An Auto Hierarchical Clustering Algorithm to Distinguish Geometries Suitable for Additive and Traditional Manufacturing Technologies: Comparing Humans and Unsupervised Learning
Baris Ördek, Éric Coatanéa, Yuri Borgianni
Results in Engineering (2025), pp. 104418-104418
Open Access
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