Machines | Highly Cited Papers in 2024
1. “Vibration Research on Centrifugal Loop Dryer Machines Used in Plastic Recycling Processes”
by Anna Borucka, Maksym Delembovskyi, Michał Stosiak, Mykola Karpenko, Paulius Skačkauskas and Pavel Ževžikov
Machines 2024, 12(1), 29; https://doi.org/10.3390/machines12010029
Available online: http://www.mdpi.com/2075-1702/12/1/29
2. “A Survey on Path Planning for Autonomous Ground Vehicles in Unstructured Environments”
by Dongxuan Xie, Jixin Wang, Kanghua Zhang, Nan Wang and Xiang Li
Machines 2024, 12(1), 31; https://doi.org/10.3390/machines12010031
Available online: http://www.mdpi.com/2075-1702/12/1/31
3. “Review of Prediction of Stress Corrosion Cracking in Gas Pipelines Using Machine Learning”
by Intizar Hussain, Ishrat Jamil, Muhammad Hussain, Muzaffar Chaudhry, Shazia Kausar and Tieling Zhang
Machines 2024, 12(1), 42; https://doi.org/10.3390/machines12010042
Available online: http://www.mdpi.com/2075-1702/12/1/42
4. “Simultaneous Estimation of Vehicle Sideslip and Roll Angles Using an Event-Triggered-Based IoT Architecture”
by Beatriz López Boada, Fernando Viadero-Monasterio, Javier García, Manuel Jiménez-Salas, María Jesús López Boada and Miguel Meléndez-Useros
Machines 2024, 12(1), 53; https://doi.org/10.3390/machines12010053
Available online: http://www.mdpi.com/2075-1702/12/1/53
5. “DC Series Arc Fault Diagnosis Scheme Based on Hybrid Time and Frequency Features Using Artificial Learning Models”
by Hoang-Long Dang, Sangshin Kwak and Seungdeog Choi
Machines 2024, 12(2), 102; https://doi.org/10.3390/machines12020102
Available online: http://www.mdpi.com/2075-1702/12/2/102
6. “Emotional Intelligence for the Decision-Making Process of Trajectories in Collaborative Robotics”
by Costanzo Manes, Enrico Mattei, Michele Gabrio Antonelli, Nicola Stampone and Pierluigi Beomonte Zobel
Machines 2024, 12(2), 113; https://doi.org/10.3390/machines12020113
Available online: http://www.mdpi.com/2075-1702/12/2/113
7. “Localization and Mapping for Self-Driving Vehicles: A Survey”
by Ali Yahyaouy, Anas Charroud, Eyo U. Eyo, Karim El Moutaouakil, Uche Onyekpe and Vasile Palade
Machines 2024, 12(2), 118; https://doi.org/10.3390/machines12020118
Available online: http://www.mdpi.com/2075-1702/12/2/118
8. “The Role of Ergonomic and Human Factors in Sustainable Manufacturing: A Review”
by Bassam Hasanain
Machines 2024, 12(3), 159; https://doi.org/10.3390/machines12030159
Available online: http://www.mdpi.com/2075-1702/12/3/159
9. “On Torque Vectoring Control: Review and Comparison of State-of-the-Art Approaches”
by Edoardo Sabbioni, Michele Asperti and Michele Vignati
Machines 2024, 12(3), 160; https://doi.org/10.3390/machines12030160
Available online: http://www.mdpi.com/2075-1702/12/3/160
10. “Machine Vision-Based Surface Defect Detection Study for Ceramic 3D Printing”
by Haili Li, Jing Zhou, Lin Lu and Ying Cheng
Machines 2024, 12(3), 166; https://doi.org/10.3390/machines12030166
Available online: http://www.mdpi.com/2075-1702/12/3/166
11. “Heterogeneous Multi-Robot Collaboration for Coverage Path Planning in Partially Known Dynamic Environments”
by Diego B. Haddad, Fabio A. A. Andrade, Gabriel G. R. de Castro, José Lima, Leonardo de M. Honório, Milena F. Pinto and Tatiana M. B. Santos
Machines 2024, 12(3), 200; https://doi.org/10.3390/machines12030200
Available online: http://www.mdpi.com/2075-1702/12/3/200
12. “Deep Learning-Enhanced Small-Sample Bearing Fault Analysis Using Q-Transform and HOG Image Features in a GRU-XAI Framework”
by Anshuman Purohit, Himanshu Borade, Hitesh Agrawal, Nandan Padia, Vinay Vakharia and Vipul Dave
Machines 2024, 12(6), 373; https://doi.org/10.3390/machines12060373
Available online: http://www.mdpi.com/2075-1702/12/6/373
13. “A Review of Time-Series Forecasting Algorithms for Industrial Manufacturing Systems”
by Afshin Rahimi and Syeda Sitara Wishal Fatima
Machines 2024, 12(6), 380; https://doi.org/10.3390/machines12060380
Available online: http://www.mdpi.com/2075-1702/12/6/380
14. “Optimization of the Factory Layout and Production Flow Using Production-Simulation-Based Reinforcement Learning”
by DongHyun Lee, Horim Kim, Hyekyung Choi, Hyunsik Yoon, Jagyu Han, Minsu Kwon, Sang Do Noh, Sanghoon Ji and Seokhwan Yu
Machines 2024, 12(6), 390; https://doi.org/10.3390/machines12060390
Available online: http://www.mdpi.com/2075-1702/12/6/390
15. “Design of Soft Robots: A Review of Methods and Future Opportunities for Research”
by Behzad Hasanshahi, Ki-Young Song, Lin Cao and Wenjun Zhang
Machines 2024, 12(8), 527; https://doi.org/10.3390/machines12080527
Available online: http://www.mdpi.com/2075-1702/12/8/527
16. “Equipment and Operations Automation in Mining: A Review”
by Joseph Sottile, Michael Long, Peter Kolapo, Steven Schafrik and Zach Agioutantis
Machines 2024, 12(10), 713; https://doi.org/10.3390/machines12100713
Available online: http://www.mdpi.com/2075-1702/12/10/713
17. “Digital Twin for Flexible Manufacturing Systems and Optimization Through Simulation: A Case Study”
by Adriana Florescu
Machines 2024, 12(11), 785; https://doi.org/10.3390/machines12110785
Available online: http://www.mdpi.com/2075-1702/12/11/785
18. “Self-Starting Improvement and Performance Enhancement in Darrieus VAWTs Using Auxiliary Blades and Deflectors”
by Erfan Enayati, Farzad Ghafoorian, Hui Wan and Seyed Reza Mirmotahari
Machines 2024, 12(11), 806; https://doi.org/10.3390/machines12110806
Available online: http://www.mdpi.com/2075-1702/12/11/806
19. “A Review of Physics-Based, Data-Driven, and Hybrid Models for Tool Wear Monitoring”
by Defeng Gao, Haoyuan Zhang, Shanglei Jiang, Wenxiang Bai and Yuwen Sun
Machines 2024, 12(12), 833; https://doi.org/10.3390/machines12120833
Available online: http://www.mdpi.com/2075-1702/12/12/833
20. “Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model”
by Jun Guo, Kaixu Han and Wenhao Wang
Machines 2024, 12(12), 927; https://doi.org/10.3390/machines12120927
Available online: http://www.mdpi.com/2075-1702/12/12/927