11 citations as recorded by crossref.

1. Grain-scale material removal mechanisms of crystalline material micro-cutting H. Ji et al. https://doi.org/10.1016/j.ijmecsci.2022.107671
2. Enhancement of forming tool performance through combined macro-geometric optimization and regional micro-scale passivation X. Chen et al. https://doi.org/10.1016/j.jmrt.2026.09.094
3. The study of cutting force, temperature, and geometric error in cutting a large screw X. Ma & Q. Guo https://doi.org/10.1177/16878132231177994
4. A two-step machine learning approach for dynamic model selection: A case study on a micro milling process Y. Cruz et al. https://doi.org/10.1016/j.compind.2022.103764
5. Study on deformation and compensation for micromilled thin walls with high aspect ratios Y. Li et al. https://doi.org/10.1007/s00170-021-07833-6
6. Study on the Micro-cutting Mechanism of FeCoCrNiAl0.6 High-Entropy Alloy Based on Pre-Cutting P. Zhang et al. https://doi.org/10.1007/s11665-025-12729-7
7. Study on deformation and compensation for micromilling of thin walls Y. Li et al. https://doi.org/10.1007/s00170-022-08798-w
8. An improved energy consumption model for micro-cutting: exploring the specificities of cutting energy, chip morphology and surface integrity in micro-cutting Y. Yao et al. https://doi.org/10.1016/j.jmapro.2025.10.105
9. An edge identification method for gap in-line measurement based on fillet assumption Q. Zhao et al. https://doi.org/10.1177/00202940221117272
10. Investigations on piezo actuator-based non-resonant type workpiece vibratory system for vibration-assisted micro-milling P. Prabhu & M. Rao https://doi.org/10.1007/s00170-024-14298-w
11. Intelligent chatter detection in micro-milling integrating self-attention-CNN feature fusion and optimized ensemble SVM T. Zhu et al. https://doi.org/10.1016/j.rineng.2026.111001