Fangyu Peng

3.5k total citations
147 papers, 2.6k citations indexed

About

Fangyu Peng is a scholar working on Mechanical Engineering, Biomedical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Fangyu Peng has authored 147 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 118 papers in Mechanical Engineering, 67 papers in Biomedical Engineering and 42 papers in Industrial and Manufacturing Engineering. Recurrent topics in Fangyu Peng's work include Advanced machining processes and optimization (105 papers), Advanced Surface Polishing Techniques (64 papers) and Advanced Machining and Optimization Techniques (39 papers). Fangyu Peng is often cited by papers focused on Advanced machining processes and optimization (105 papers), Advanced Surface Polishing Techniques (64 papers) and Advanced Machining and Optimization Techniques (39 papers). Fangyu Peng collaborates with scholars based in China, United Kingdom and United States. Fangyu Peng's co-authors include Rong Yan, Xiaowei Tang, Hongqi Liu, Lin Zhou, Xinyong Mao, Zerun Zhu, Bo Luo, Chen Chen, Bin Li and Jiawei Wu and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Industrial Electronics and Journal of Sound and Vibration.

In The Last Decade

Fangyu Peng

136 papers receiving 2.5k citations

Peers

Fangyu Peng

IME

EEE

CSE

Kunpeng Zhu China

Marek Balazinski Canada

Liping Wang China

Ye Ding China

F. Ismail Canada

Ibrahim Tansel United States

Krzysztof Jemielniak Poland

Lütfi Taner Tunç Türkiye

Benoît Furet France

M.S. Shunmugam India

Kunpeng Zhu China

Fangyu Peng

2.7k ×1.3

677 ×0.6

1.1k ×1.5

IME

1.0k ×1.4

EEE

430 ×0.8

CSE

Citations per year, relative to Fangyu Peng Fangyu Peng (= 1×) peers Kunpeng Zhu

Countries citing papers authored by Fangyu Peng

Since Specialization

Citations

This map shows the geographic impact of Fangyu Peng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fangyu Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangyu Peng more than expected).

Fields of papers citing papers by Fangyu Peng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fangyu Peng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fangyu Peng. The network helps show where Fangyu Peng may publish in the future.

Co-authorship network of co-authors of Fangyu Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Fangyu Peng. A scholar is included among the top collaborators of Fangyu Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fangyu Peng. Fangyu Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Zhang, Teng, et al.. (2025). UGP-KD: An unsupervised generalized prediction framework for robot machining quality under historical task knowledge distillation for new tasks. Computers in Industry. 168. 104269–104269. 3 indexed citations

Peng, Fangyu, et al.. (2025). An uncertainty quantification and accuracy enhancement method for deep regression prediction scenarios. Mechanical Systems and Signal Processing. 227. 112394–112394. 6 indexed citations

Zhang, Hang, et al.. (2025). Laser-assisted machining of SiCp/Al composites: Preheating history driven microstructure evolution and its role in material removal. Journal of Materials Processing Technology. 344. 119024–119024. 2 indexed citations

Peng, Fangyu, et al.. (2025). Spatial–temporal feature fusion for intelligent foreknowledge of robotic machining errors. Robotics and Computer-Integrated Manufacturing. 94. 102972–102972. 3 indexed citations

Peng, Fangyu, et al.. (2025). PI2-BDMPs in Combination With Contact Force Model: A Robotic Polishing Skill Learning and Generalization Approach. IEEE/ASME Transactions on Mechatronics. 30(2). 978–988.

Tang, Xiaowei, et al.. (2025). Three-dimensional cellular magnetorheological elastomer absorber for suppressing time-varying chatter in robotic milling. Procedia CIRP. 133. 155–160.

Zhang, Teng, et al.. (2024). An online prediction and compensation method for robot position errors embedded with error-motion correlation. Measurement. 234. 114866–114866. 14 indexed citations

Zhang, Hua, et al.. (2024). United optimization strategy of ultrasonic vibration assisted process and multiple parameters for machining deformation reduction. Journal of Manufacturing Processes. 131. 1942–1958. 5 indexed citations

Peng, Fangyu, Hao Sun, Rong Yan, et al.. (2024). A self-adaptive agent for flexible posture planning in robotic milling system. Journal of Manufacturing Systems. 75. 228–245. 5 indexed citations

10.

Zhang, Teng, et al.. (2024). A sparse knowledge embedded configuration optimization method for robotic machining system toward improving machining quality. Robotics and Computer-Integrated Manufacturing. 90. 102818–102818. 6 indexed citations

11.

Peng, Fangyu, et al.. (2024). Study on the parameters optimization of 3D printing continuous carbon fiber-reinforced composites based on CNN and NSGA-II. Composites Part A Applied Science and Manufacturing. 190. 108657–108657. 4 indexed citations

12.

Peng, Fangyu, et al.. (2024). Event-triggered Hybrid Force Feedback Architecture With Tank-based Stabilization Method for Complicated Bilateral Teleoperation Tasks. International Journal of Control Automation and Systems. 22(7). 2193–2206. 1 indexed citations

13.

Yang, Minghui, et al.. (2023). Multiscale modeling of cutting processes for TiBw/TA15 composites based on the interface model parameters identification method by microcolumn compression. Journal of Materials Processing Technology. 317. 118008–118008. 3 indexed citations

14.

Tang, Xiaowei, et al.. (2023). Investigation of the low-frequency chatter in robotic milling. International Journal of Machine Tools and Manufacture. 190. 104048–104048. 37 indexed citations

15.

Peng, Fangyu, et al.. (2023). Review on Removal Mechanism and Process Modeling in Machining of Metal Matrix Composites. Journal of Mechanical Engineering. 59(19). 460–460. 3 indexed citations

16.

Peng, Fangyu, et al.. (2023). Robotic Milling Chatter Types Detection Based on Adaptive VariationalMode Decomposition and Difference of Power Spectral Entropy. Journal of Mechanical Engineering. 59(9). 90–90. 4 indexed citations

17.

Sun, Hao, et al.. (2023). Feature fusion and distillation embedded sparse Bayesian learning model for in-situ foreknowledge of robotic machining errors. Journal of Manufacturing Systems. 71. 546–564. 9 indexed citations

18.

Peng, Fangyu, et al.. (2012). Anisotropic force ellipsoid based multi-axis motion optimization of machine tools. Chinese Journal of Mechanical Engineering. 25(5). 960–967. 8 indexed citations

19.

Peng, Fangyu, Li Li, Xubing Chen, & Bin Li. (2006). Corner Constraint Conditions Based on Machining Dynamics in High Speed and High Precision Continuous Micro-Line Interpolation. Journal of Computer-Aided Design & Computer Graphics. 18(12). 1812–1816. 2 indexed citations

20.

Peng, Fangyu. (2002). Reconstruction of Rough Huge Lamina Surface Based on Energy Minimization.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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