Study on surface integrity of IN718 cladding layer milled by micro texture tool
Jiasheng Wu, Linsen Shu, Siyu Mao, Rongrong Song, Yu Liu, Jun ZhouPurpose
The IN718 cladding layer is prone to poor machined surface quality issues during processing due to its multi-phase heterogeneous microstructure, high hardness and high strength. This study aims to investigate high-quality machining methods for this material.
Design/methodology/approach
This study designed and fabricated micro-textured tools. These tools, along with conventional tools, were used to mill the IN718 cladding layer under various cutting parameters. The effects of both tool types on the surface and subsurface quality of the workpiece were compared and analyzed.
Findings
Experimental results indicate that, compared to conventional tools, the micro-textured tools reduced the surface roughness (Ra) value by 23% and effectively minimized surface micro-defects. In addition, the tensile residual stress on the workpiece surface was reduced by 25.3%, while the compressive stress level in the subsurface layer increased by 34.5%. The surface hardness decreased by 13.2%, and the subsurface hardness decreased by 5%. In summary, micro-textured tools can effectively suppress machining-induced damage and significantly enhance the surface integrity of the IN718 cladding layer.
Originality/value
This study represents original work. All experimental design, data collection, analysis and interpretation were independently completed by the undersigned authors. The design and fabrication of the micro-textured tools described in this paper, as well as their application method in milling IN718 cladding layers, are innovative. This work systematically reveals the synergistic improvement mechanism of micro-textures on multiple surface integrity indicators (roughness, residual stress, hardness gradient). The research has not been published previously and is not under simultaneous consideration for publication elsewhere. All contributing authors are aware of and consent to this submission. There are no conflicts of interest to declare. The data are authentic and verifiable, and all cited literature has been properly acknowledged.