On understanding milling characteristics of TC4 alloy during graphene nanofluid minimum quantity lubrication with bionic micro-texture tool
TC4 alloy has excellent comprehensive properties and is widely applied in the aircraft, medical device, and chemical equipment. However, the cutting area cooling and lubrication state is very poor by reason of the high mechanical strength, poor heat dissipation, and low elastic modulus of TC4 alloy in the milling process, which is prone to generate large milling force, high milling temperature, serious tool wear, and poor surface quality. For improving the cutting area cooling and lubrication state, a new eco-friendly, efficient, and sustainable milling process by combining the graphene nanofluid minimum quantity lubrication with the bionic micro-texture tool was proposed. In order to reveal the multi-effect synergistic improving mechanism of this new process, the milling experiments were conducted in the six working conditions. Meanwhile, the milling characteristics were evaluated with regard to the milling force, milling temperature, surface integrity, and tool wear. The results indicated that combining the graphene nanofluid minimum quantity lubrication with bionic micro-texture tool can reduce the milling force peak values (x, y, z) by 39.23 %, 35.75 %, and 40.23 % respectively, the average peak value of the milling temperature by 43.83 %, the surface roughness by 56.91 %, and the surface micro-hardness by 19.17 %, while prolong the tool life by 112 % compared to the Dry-CT working condition. This is mainly because the combination can significantly improve the cutting zone lubrication and cooling state, and achieve the best milling characteristics. In summary, these findings can provide some theoretical support to promote the application of this new milling process in industrial production.
Authors
- Qingguang Li (ORCID: https://orcid.org/0009-0008-5973-6764)
- Ming Li (ORCID: https://orcid.org/0000-0002-0094-0129)
- Lianjie Ma
- Yunguang Zhou (ORCID: https://orcid.org/0000-0001-5142-8187)
- Zixuan Wang (ORCID: https://orcid.org/0000-0002-6823-5573)
- Tianbiao Yu (ORCID: https://orcid.org/0000-0003-0893-1515)
- Shengzhi Xu
- Jiaqi Wang (ORCID: https://orcid.org/0000-0003-2300-8227)
- Xianchao Pan
Institutions
- Shijiazhuang University (CN)
- PLA Army Engineering University (CN)
- Northeastern University (CN)
Publication Details
- Journal
- Journal of Materials Research and Technology
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1016/j.jmrt.2025.04.091
- Citations
- 6
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 4.28