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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:

A Digital Twin-Based Distributed Manufacturing Execution System for Industry 4.0 with AI-Powered On-The-Fly Replanning Capabilities
Jiří Vyskočil, Petr Douda, Petr Novák, et al.
Sustainability (2023) Vol. 15, Iss. 7, pp. 6251-6251
Open Access | Times Cited: 15

Showing 15 citing articles:

Big data, machine learning, and digital twin assisted additive manufacturing: A review
Liuchao Jin, Xiaoya Zhai, Kang Wang, et al.
Materials & Design (2024) Vol. 244, pp. 113086-113086
Open Access | Times Cited: 43
Conversion of lignocellulosic biomass waste into mycoprotein: current status and future directions for sustainable protein production
Zheng Yang Ng, Phei Er Kee, Rosazlin Abdullah, et al.
Biomass Conversion and Biorefinery (2024)
Closed Access | Times Cited: 5
Smart quality control of Industry 4.0 by artificial intelligence-powered robot vision, a review
Mohsen Soori, Roza Dastres, Fooad Karimi Ghaleh Jough, et al.
Elsevier eBooks (2025), pp. 255-285
Closed Access
Verification and validation of digital twins: a systematic literature review for manufacturing applications
Julia Bitencourt, Ana Wooley, Gregory Harris
International Journal of Production Research (2024), pp. 1-29
Closed Access | Times Cited: 3
Driving sustainability - The role of digital twin in enhancing battery performance for electric vehicles
P.K. Rajesh, T. Soundarya, K.V. Jithin
Journal of Power Sources (2024) Vol. 604, pp. 234464-234464
Closed Access | Times Cited: 2
An Immersive Digital Twin Applied to a Manufacturing Execution System for the Monitoring and Control of Industry 4.0 Processes
Gustavo Caiza, Ricardo Sanz
Applied Sciences (2024) Vol. 14, Iss. 10, pp. 4125-4125
Open Access | Times Cited: 2
Immersive Digital Twin under ISO 23247 Applied to Flexible Manufacturing Processes
Gustavo Caiza, Ricardo Sanz
Applied Sciences (2024) Vol. 14, Iss. 10, pp. 4204-4204
Open Access | Times Cited: 2
Analyzing The Purpose And Technologies Of Digital Twins In Distributed Manufacturing: A Systematic Literature Review
Monika Risling, Michael Oberle, Thomas Bauernhansl
Procedia Computer Science (2024) Vol. 232, pp. 368-376
Open Access | Times Cited: 1
Strategic Planning of Reconfigurable Industrial Systems and Value Chains: A life cycle conceptual model
Alessia Napoleone
Procedia CIRP (2024) Vol. 122, pp. 1071-1076
Open Access | Times Cited: 1
Smart Factory Digital Twin for Performance Measurement, Optimization, and Prediction
Suhas D. Joshi
(2024), pp. 115-143
Closed Access
Hybrid Model Based Autonomous System for Controlling Double Side Grinding Process
Hong‐Seok Park, Ngoc-Hien Tran
International Journal of Precision Engineering and Manufacturing-Smart Technology (2024) Vol. 2, Iss. 2, pp. 191-208
Closed Access
Research on the correlation between the degree of digitization of manufacturing process links and economic benefits
Heyong Wang, Long Gu, Ming Hong
Business Process Management Journal (2024)
Closed Access
Mercado do Gêmeo Digital: aplicação da matriz SWOT para análise mercadológica e tendências do setor
Andressa Clara Barbosa de Araújo, Daniel Marques Santana Oliveira, Emilli Cássia Souza Lopes, et al.
Revista de Gestão e Secretariado (Management and Administrative Professional Review) (2024) Vol. 15, Iss. 9, pp. e4160-e4160
Open Access
A Novel Approach of Resource Allocation for Distributed Digital Twin Shop-Floor
Haijun Zhang, Qiong Yan, Yan Qin, et al.
Information (2023) Vol. 14, Iss. 8, pp. 458-458
Open Access | Times Cited: 1
Unsupervised and Supervised Machine Learning Methods for Cutting Tool Path Clustering and RUL Estimation in Manufacturing
Fabio C. Zegarra, Juan Vargas-Machuca, Avid Román-Gonzalez, et al.
Journal of Machine Engineering (2023)
Open Access | Times Cited: 1
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