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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:

Multistage Quality Control Using Machine Learning in the Automotive Industry
Ricardo Silva Peres, José Barata, Paulo Leitão, et al.
IEEE Access (2019) Vol. 7, pp. 79908-79916
Open Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review
Ting Zheng, Marco Ardolino, Andrea Bacchetti, et al.
International Journal of Production Research (2020) Vol. 59, Iss. 6, pp. 1922-1954
Closed Access | Times Cited: 530
Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
Ricardo Silva Peres, Xiaodong Jia, Jay Lee, et al.
IEEE Access (2020) Vol. 8, pp. 220121-220139
Open Access | Times Cited: 426
Machine Learning for industrial applications: A comprehensive literature review
Massimo Bertolini, Davide Mezzogori, Mattia Neroni, et al.
Expert Systems with Applications (2021) Vol. 175, pp. 114820-114820
Closed Access | Times Cited: 348
Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook
Jorge Arinez, Qing Chang, Robert X. Gao, et al.
Journal of Manufacturing Science and Engineering (2020) Vol. 142, Iss. 11
Open Access | Times Cited: 343
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: 132
Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review
Jun-Hyeong Lee, Donggeun Park, Mingyu Lee, et al.
Materials Horizons (2023) Vol. 10, Iss. 12, pp. 5436-5456
Closed Access | Times Cited: 39
Smart Machine Vision System to Improve Decision-Making on the Assembly Line
Carlos Américo de Souza Silva, Edson Pacheco Paladini
Machines (2025) Vol. 13, Iss. 2, pp. 98-98
Open Access | Times Cited: 1
Towards Zero Defect Manufacturing paradigm: A review of the state-of-the-art methods and open challenges
Bianca Caiazzo, Mario Di Nardo, Teresa Murino, et al.
Computers in Industry (2021) Vol. 134, pp. 103548-103548
Closed Access | Times Cited: 64
Artificial intelligence to predict West Nile virus outbreaks with eco-climatic drivers
Zia Farooq, Joacim Rocklöv, Jonas Wallin, et al.
The Lancet Regional Health - Europe (2022) Vol. 17, pp. 100370-100370
Open Access | Times Cited: 63
A network security situation assessment method based on adversarial deep learning
Hongyu Yang, Renyun Zeng, Guangquan Xu, et al.
Applied Soft Computing (2021) Vol. 102, pp. 107096-107096
Closed Access | Times Cited: 59
In artificial intelligence (AI) we trust: A qualitative investigation of AI technology acceptance
Abhinav Hasija, Terry L. Esper
Journal of Business Logistics (2022) Vol. 43, Iss. 3, pp. 388-412
Closed Access | Times Cited: 58
Optical metrology for digital manufacturing: a review
Sofia Catalucci, Adam Thompson, Samanta Piano, et al.
The International Journal of Advanced Manufacturing Technology (2022) Vol. 120, Iss. 7-8, pp. 4271-4290
Open Access | Times Cited: 50
European projections of West Nile virus transmission under climate change scenarios
Zia Farooq, Henrik Sjödin, Jan C. Semenza, et al.
One Health (2023) Vol. 16, pp. 100509-100509
Open Access | Times Cited: 33
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
Metaverse in advanced manufacturing: Background, applications, limitations, open issues & future directions
Gabriel Chukwunonso Amaizu, Judith Nkechinyere Njoku, Jae‐Min Lee, et al.
ICT Express (2024) Vol. 10, Iss. 2, pp. 233-255
Open Access | Times Cited: 9
Role and Applications of Artificial Intelligence and Machine Learning in Manufacturing Engineering: A Review
Sara Bunian, Meshari A. Al-Ebrahim, Amro A. Nour
Engineered Science (2024)
Open Access | Times Cited: 7
Energy-Aware Multi-Objective Job Shop Scheduling Optimization with Metaheuristics in Manufacturing Industries: A Critical Survey, Results, and Perspectives
Jesús Para, Javier Del Ser, Antonio J. Nebro
Applied Sciences (2022) Vol. 12, Iss. 3, pp. 1491-1491
Open Access | Times Cited: 29
Real-World Applications of Data Analytics, Big Data, and Machine Learning
Prince Shiva Chaudhary, M. Khurana, Mukund Ayalasomayajula
Studies in big data (2024), pp. 237-263
Closed Access | Times Cited: 5
Data analytics for quality management in Industry 4.0 from a MSME perspective
Görkem Sarıyer, Sachin Kumar Mangla, Yiğit Kazançoğlu, et al.
Annals of Operations Research (2021)
Closed Access | Times Cited: 37
Applying Bayesian Optimization for Machine Learning Models in Predicting the Surface Roughness in Single-Point Diamond Turning Polycarbonate
Van-Hai Nguyen, Tien-Thinh Le, Hoanh-Son Truong, et al.
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-16
Open Access | Times Cited: 35
Application of machine learning and rough set theory in lean maintenance decision support system development
Katarzyna Antosz, Małgorzata Jasiulewicz–Kaczmarek, Łukasz Paśko, et al.
Eksploatacja i Niezawodnosc - Maintenance and Reliability (2021) Vol. 23, Iss. 4, pp. 695-708
Open Access | Times Cited: 35
A Primer on the Factories of the Future
Noble Anumbe, Clint Saidy, Ramy Harik
Sensors (2022) Vol. 22, Iss. 15, pp. 5834-5834
Open Access | Times Cited: 23
A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing
Liping Zhao, Bohao Li, Yiyong Yao
Advances in Manufacturing (2023) Vol. 11, Iss. 2, pp. 280-294
Closed Access | Times Cited: 13
An AHP parsimonious based approach to handle manufacturing errors in production processes
Gerarda Fattoruso, Maria Barbati, Alessio Ishizaka
Production Planning & Control (2024) Vol. 35, Iss. 16, pp. 2370-2399
Closed Access | Times Cited: 4
Automating quality control through an expert system
Giorgio Scarton, Marco Formentini, Pietro Romano
Electronic Markets (2025) Vol. 35, Iss. 1
Open Access
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