Caixu Yue

2.0k total citations · 1 hit paper
94 papers, 1.4k citations indexed

About

Caixu Yue is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Caixu Yue has authored 94 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Mechanical Engineering, 45 papers in Biomedical Engineering and 36 papers in Electrical and Electronic Engineering. Recurrent topics in Caixu Yue's work include Advanced machining processes and optimization (78 papers), Advanced Surface Polishing Techniques (44 papers) and Advanced Machining and Optimization Techniques (35 papers). Caixu Yue is often cited by papers focused on Advanced machining processes and optimization (78 papers), Advanced Surface Polishing Techniques (44 papers) and Advanced Machining and Optimization Techniques (35 papers). Caixu Yue collaborates with scholars based in China, United States and Sweden. Caixu Yue's co-authors include Steven Y. Liang, Xianli Liu, Lihui Wang, Xianli Liu, Haining Gao, Xuebing Li, Bowen Zhang, Shaoyang Liu, Rongyi Li and Zhitao Chen and has published in prestigious journals such as Journal of Materials Processing Technology, Mechanical Systems and Signal Processing and Wear.

In The Last Decade

Caixu Yue

88 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Systematic review on tool breakage monitoring techniques in machining operations

2022 141 citations Xuebing Li, Xianli Liu et al. profile →

Peers

Caixu Yue

ME

EEE

IME

BE

CSE

Kejia Zhuang China

Marco Sortino Italy

Giovanni Totis Italy

Vigneashwara Pandiyan Switzerland

Jürgen Leopold Germany

Uroš Župerl Slovenia

Sijie Yan China

Şerafettin Engin Canada

Xiaowei Tang China

Yongqing Wang China

Kejia Zhuang China

Caixu Yue

968 ×0.8

ME

414 ×0.8

EEE

267 ×0.5

IME

557 ×1.2

BE

103 ×0.8

CSE

Citations per year, relative to Caixu Yue Caixu Yue (= 1×) peers Kejia Zhuang

Countries citing papers authored by Caixu Yue

Since Specialization

Citations

This map shows the geographic impact of Caixu Yue'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 Caixu Yue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Caixu Yue more than expected).

Fields of papers citing papers by Caixu Yue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Caixu Yue. 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 Caixu Yue. The network helps show where Caixu Yue may publish in the future.

Co-authorship network of co-authors of Caixu Yue

This figure shows the co-authorship network connecting the top 25 collaborators of Caixu Yue. A scholar is included among the top collaborators of Caixu Yue 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 Caixu Yue. Caixu Yue is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Li, Rongyi, Xianli Liu, Caixu Yue, et al.. (2025). Swin-fusion: An adaptive multi-source information fusion framework for enhanced tool wear monitoring. Journal of Manufacturing Systems. 79. 435–454. 10 indexed citations

2.

Li, Mingxing, Caixu Yue, Xianli Liu, & Jinming Zhou. (2025). Research on properties of Re-doped WC-Co alloys. International Journal of Refractory Metals and Hard Materials. 133. 107373–107373.

3.

Rong, Weibin, et al.. (2025). Robust Localization Algorithm for Micromanipulation Targets Under Complex Interference Conditions. IEEE Transactions on Automation Science and Engineering. 22. 23959–23969.

4.

Sun, Shao‐Cong, et al.. (2025). An efficient calculation method of milling force. The International Journal of Advanced Manufacturing Technology. 137(3-4). 1339–1362. 1 indexed citations

5.

Li, Xuebing, Jing Ni, Caixu Yue, et al.. (2025). Chatter-free milling of aerospace thin-walled parts. Journal of Materials Processing Technology. 341. 118903–118903. 3 indexed citations

6.

Zhang, Bowen, et al.. (2024). Meta-learning-based approach for tool condition monitoring in multi-condition small sample scenarios. Mechanical Systems and Signal Processing. 216. 111444–111444. 18 indexed citations

7.

Yue, Caixu, et al.. (2024). Research on online deformation monitoring of thin-walled parts driven by digital twin. 3. 100023–100023. 5 indexed citations

8.

Wang, Hongyang, et al.. (2024). An accurate mathematical model for ball end mills with chisel edge. The International Journal of Advanced Manufacturing Technology. 131(12). 5729–5743. 2 indexed citations

9.

Li, Xuebing, et al.. (2024). Data-model linkage prediction of tool remaining useful life based on deep feature fusion and Wiener process. Journal of Manufacturing Systems. 73. 19–38. 41 indexed citations

10.

Ma, Wei, Xianli Liu, Caixu Yue, Lihui Wang, & Steven Y. Liang. (2023). Multi-scale one-dimensional convolution tool wear monitoring based on multi-model fusion learning skills. Journal of Manufacturing Systems. 70. 69–98. 26 indexed citations

11.

Lu, Junhui, et al.. (2023). Analytical modeling of milling residual stress under different tool wear conditions. The International Journal of Advanced Manufacturing Technology. 127(9-10). 4253–4269. 4 indexed citations

12.

Liu, Xianli, et al.. (2023). Research on design and milling performance of unequal gradient helix and variable pitch end mill. Journal of Manufacturing Processes. 106. 347–362. 4 indexed citations

13.

Liu, Xianli, et al.. (2023). Design, Manufacturing, Management and Control Technology of Cutting Tools for Intelligent Manufacturing Process. Journal of Mechanical Engineering. 59(19). 429–429. 1 indexed citations

14.

Yue, Caixu, et al.. (2023). Tool wear identification and prediction method based on stack sparse self-coding network. Journal of Manufacturing Systems. 68. 72–84. 76 indexed citations

15.

Lin, Zhi, et al.. (2023). Development and application of parametric design system for solid end mills based on Open CASCADE. The International Journal of Advanced Manufacturing Technology. 127(9-10). 4659–4676. 2 indexed citations

16.

Chen, Zhitao, et al.. (2023). An analytical machining deformation model of H-section multi-frame beam integral components. Journal of Materials Processing Technology. 314. 117907–117907. 9 indexed citations

17.

Yue, Caixu, et al.. (2022). Research on Surface Roughness of Supersonic Vibration Auxiliary Side Milling for Titanium Alloy. Chinese Journal of Mechanical Engineering. 35(1). 5 indexed citations

18.

Yue, Caixu, et al.. (2017). 3D FEM Simulation of Milling Force in Corner Machining Process. Chinese Journal of Mechanical Engineering. 30(2). 286–293. 10 indexed citations

19.

Yue, Caixu, et al.. (2014). Hardening effect on machined surface for precise hard cutting process with consideration of tool wear. Chinese Journal of Mechanical Engineering. 27(6). 1249–1256. 6 indexed citations

20.

Yue, Caixu. (2013). Machining Technology of Hardened Steel Molds of Automobile Large Covering. Harbin Ligong Daxue xuebao. 3 indexed citations

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.

Explore authors with similar magnitude of impact