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:

On the use of machine learning methods to predict component reliability from data-driven industrial case studies
Emanuel Federico Alsina, Manuel Chica, Krzysztof Trawiński, et al.
The International Journal of Advanced Manufacturing Technology (2017) Vol. 94, Iss. 5-8, pp. 2419-2433
Closed Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
Andreas Theissler, Judith Pérez-Velázquez, Marcel Kettelgerdes, et al.
Reliability Engineering & System Safety (2021) Vol. 215, pp. 107864-107864
Open Access | Times Cited: 296
Advances in Computational Intelligence of Polymer Composite Materials: Machine Learning Assisted Modeling, Analysis and Design
Aanchna Sharma, T. Mukhopadhyay, Sanjay Mavinkere Rangappa, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 5, pp. 3341-3385
Open Access | Times Cited: 136
Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future
Matthias Klumpp, Marc Hesenius, Ole Meyer, et al.
The International Journal of Advanced Manufacturing Technology (2019) Vol. 105, Iss. 9, pp. 3691-3709
Open Access | Times Cited: 95
A Systematic Mapping of the Advancing Use of Machine Learning Techniques for Predictive Maintenance in the Manufacturing Sector
Milena Nacchia, Fabio Fruggiero, Alfredo Lambiase, et al.
Applied Sciences (2021) Vol. 11, Iss. 6, pp. 2546-2546
Open Access | Times Cited: 65
Impact of dataset size and convolutional neural network architecture on transfer learning for carbonate rock classification
Harriet L. Dawson, Olivier Dubrule, Cédric M. John
Computers & Geosciences (2022) Vol. 171, pp. 105284-105284
Open Access | Times Cited: 64
Reliability assessment of manufacturing systems: A comprehensive overview, challenges and opportunities
Jonas Friederich, Sanja Lazarova‐Molnar
Journal of Manufacturing Systems (2023) Vol. 72, pp. 38-58
Open Access | Times Cited: 24
Intelligent System for the Predictive Analysis of an Industrial Wastewater Treatment Process
Luis Arismendy, Carlos Cárdenas, Diego Gómez, et al.
Sustainability (2020) Vol. 12, Iss. 16, pp. 6348-6348
Open Access | Times Cited: 60
Machine learning in industrialization: a bibliometric analysis
Guillermo Alexander Loayza-Delgado, Xiomara Luciana Tejada-Montalvo, María Fernanda Carnero Quispe, et al.
DYNA (2025) Vol. 92, Iss. 235, pp. 28-37
Open Access
A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing
Hamzeh Soltanali, Abbas Rohani, Mohammad Hossein Abbaspour‐Fard, et al.
Applied Soft Computing (2020) Vol. 98, pp. 106738-106738
Closed Access | Times Cited: 44
Influence of Abrasive Wear on Reliability and Maintainability of Components in Quarry Technological Equipment: A Case Study
Vlad Alexandru Florea, Mihaela Toderaş, Daniel Tihanov-Tănăsache
Applied Sciences (2025) Vol. 15, Iss. 7, pp. 3603-3603
Open Access
A Machine Learning Evaluation of Maintenance Records for Common Failure Modes in PV Inverters
Thushara Gunda, Sean F. Hackett, Laura Kraus, et al.
IEEE Access (2020) Vol. 8, pp. 211610-211620
Open Access | Times Cited: 31
Unsupervised Fault Detection and Prediction of Remaining Useful Life for Online Prognostic Health Management of Mechanical Systems
Francesca Calabrese, Alberto Regattieri, Lucia Botti, et al.
Applied Sciences (2020) Vol. 10, Iss. 12, pp. 4120-4120
Open Access | Times Cited: 30
A novel bidirectional DiPLS based LSTM algorithm and its application in industrial process time series prediction
Yongjian Wang, De Bao, S. Joe Qin
Chemometrics and Intelligent Laboratory Systems (2023) Vol. 240, pp. 104878-104878
Closed Access | Times Cited: 10
Adoptable approaches to predictive maintenance in mining industry: An overview
Oluwatobi Dayo-Olupona, Bekir Genc, Turgay Çelik, et al.
Resources Policy (2023) Vol. 86, pp. 104291-104291
Open Access | Times Cited: 9
Machine learning for monitoring and classification in inverters from solar photovoltaic energy plants
Fabíola Pereira, Carlos Silva
Solar Compass (2023) Vol. 9, pp. 100066-100066
Open Access | Times Cited: 9
Shop floor simulation optimization using machine learning to improve parallel metaheuristics
Wilson Trigueiro de Sousa, José Arnaldo Barra Montevechi, Rafael de Carvalho Miranda, et al.
Expert Systems with Applications (2020) Vol. 150, pp. 113272-113272
Closed Access | Times Cited: 25
Improved prediction for failure time of multilayer ceramic capacitors (MLCCs): A physics-based machine learning approach
Pedram Yousefian, Alireza Sepehrinezhad, Adri C. T. van Duin, et al.
APL Machine Learning (2023) Vol. 1, Iss. 3
Open Access | Times Cited: 8
On the Use of Predictive Models for Improving the Quality of Industrial Maintenance: An Analytical Literature Review of Maintenance Strategies
Oana Merkt
Annals of Computer Science and Information Systems (2019) Vol. 18, pp. 693-704
Open Access | Times Cited: 25
Data-driven smart production line and its common factors
Yongping Zhang, Ying Cheng, Xi Vincent Wang, et al.
The International Journal of Advanced Manufacturing Technology (2019) Vol. 103, Iss. 1-4, pp. 1211-1223
Closed Access | Times Cited: 23
A Data-Driven Motor Optimization Method Based on Support Vector Regression—Multi-Objective, Multivariate, and with a Limited Sample Size
Guanghao Li, Ruicheng Li, Haobo Hou, et al.
Electronics (2024) Vol. 13, Iss. 12, pp. 2231-2231
Open Access | Times Cited: 2
Catalyzing industrial evolution: A dynamic maintenance framework for maintenance 4.0 optimization
Mario Di Nardo, Teresa Murino, Assunta Cammardella, et al.
Computers & Industrial Engineering (2024) Vol. 196, pp. 110469-110469
Closed Access | Times Cited: 2
Advances in Computational Intelligence of Polymer Composite Materials: Machine Learning Assisted Modeling, Analysis and Design
Aanchna Sharma, T. Mukhopadhyay, Sanjay Mavinkere Rangappa, et al.
Research Square (Research Square) (2021)
Open Access | Times Cited: 16
Regression-based finite element machines for reliability modeling of downhole safety valves
Danilo Colombo, Gílson Brito Alves Lima, Danillo Roberto Pereira, et al.
Reliability Engineering & System Safety (2020) Vol. 198, pp. 106894-106894
Closed Access | Times Cited: 17
An improved risk and reliability framework-based maintenance planning for food processing systems
Hamzeh Soltanali, Mehdi Khojastehpour, José Torres Farinha
Quality Technology & Quantitative Management (2022) Vol. 20, Iss. 2, pp. 256-278
Closed Access | Times Cited: 9
A dynamic optimisation approach for a single machine scheduling problem with machine conditions and maintenance decisions
Wenhui Yang, Lu Chen, Stéphane Dauzère‐Pérès
International Journal of Production Research (2021) Vol. 60, Iss. 10, pp. 3047-3062
Open Access | Times Cited: 12
Page 1 - Next Page

Scroll to top