A grinding process-microstructure-surface property correlation model for grinding burn mitigation in TPMM35 powder metallurgy high-speed steel
Powder metallurgy high-speed steel (PMHSS) exhibits excellent red hardness, wear resistance, high toughness, and homogeneous microstructure, making it extensively employed in manufacturing high-performance cutting tools and precision molds. Grinding serves as the primary machining method for PMHSS, its inherent high hardness and low thermal conductivity frequently lead to grinding burn. This phenomenon induces quality deterioration, and ultimately compromises the service performance of machined components. Focusing on TPMM35 PMHSS, this study systematically investigates microstructural evolution under varying burn severities, evaluates post-burn surface properties, and establishes a grinding process-microstructure-surface property correlation model to achieve precise burn control and surface integrity enhancement. Results indicate that with increasing grinding temperature, the surface progressively exhibited four distinct burn discoloration states: matrix color, yellow, brown, and purple. Oxygen contents of 2.68%, 4.76%, and 9.26% were measured on yellow, brown, and purple burns surfaces, respectively. Progressive burn severity generates gradient microstructural layers: a 20-43 nm nanocrystalline (NC) layer, an superfine lath grains (SLG) layer, and a deformation influence (DI) layer. As the burn severity intensifies, the depth of the NC layer progressively increases. Within the SLG layer, grain refinement and elevated dislocation density are observed. Specimens with brown burns exhibit the most pronounced grain refinement characteristics, demonstrating an average grain size of 0.56 μm, and hardness of 11.7 GPa, representing a 5.4% hardness increase compared to specimens with no obvious burns. When purple burns occur, the surface grain coarsens by 30% and the hardness is reduced by 14.4% compared to specimens without obvious burns.
Authors
- Zhiqiang Liang (ORCID: https://orcid.org/0000-0002-6126-7126)
- Kenan Zhang (ORCID: https://orcid.org/0000-0003-1343-6068)
- Weiwei Ming (ORCID: https://orcid.org/0000-0002-5588-1154)
- Chenguang Wang
- Ronghua Yan
- Yaya Zhou
- Qinglong An (ORCID: https://orcid.org/0000-0001-5023-7258)
- Jiaqiang Dang (ORCID: https://orcid.org/0000-0002-7446-8234)
- Jinming Zhou (ORCID: https://orcid.org/0000-0002-7335-2045)
- Ming Chen (ORCID: https://orcid.org/0000-0001-8904-7259)
- Lanyu Shi
Institutions
- Beijing Institute of Technology (CN)
- Shanghai Jiao Tong University (CN)
- Tiangong University (CN)
Publication Details
- Journal
- Journal of Materials Research and Technology
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1016/j.jmrt.2025.08.176
- Citations
- 2
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- National Natural Science Foundation of China
- National Science and Technology Planning Project