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Investigation on Cutting Performance of Micro-Textured Cutting Tools

Authors: Li; Pan; Jiao; Hu;

Investigation on Cutting Performance of Micro-Textured Cutting Tools

Abstract

This paper explores the influence of micro textures on cutting performance of polycrystalline cubic boron nitride (PCBN) tools from two aspects, that is, tool wear and machined surface roughness. By designing micro-hole textures with different forms and scales on the rake face of tools when PCBN tools turn hardened steel GCr15, and combining finite element analysis (FEA) technology and cutting experiments, the cutting performance of micro-textured tools is simulated and analyzed. This paper analyses the influence of micro textures on tool wear and machined surface roughness by analyzing cutting force, Mises stress and maximum shear stress of tool surface. Results of finite element analysis (FEA) and cutting experiments show that the reasonable micro-hole textures can significantly alleviate tool wear and improve machined surface quality when compared with the non-textured tools. Besides, the size of micro-hole textures on the rake face play an important role in reducing the cutting force and tool wear. This is mainly because micro-hole textures can reduce cutting force and improve tool surface stress. Finally, by designing reasonable micro-hole textures on the rake face, the problems of bad roughness of machined workpiece and severe tool wear of PCBN tools in cutting GCr15 material are solved. Consequently, the paper shows that micro-hole textures have a positive effect on improving the cutting performance of tool.

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Keywords

cutting performance, Article, micro hole, tool wear, Cutting force, Surface roughness, cutting force, surface roughness, TJ1-1570, Cutting performance, Micro hole, Mechanical engineering and machinery, Tool wear

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
Green
gold