Haidong YANG, Libao ZHANG, Haodong LI, Junsheng ZHANG, Huohong TANG, Shunhua CHEN. Influence of tool corner radius on chip geometrical characteristics of machining Zr-based bulk metallic glass[J]. Journal of Advanced Manufacturing Science and Technology . DOI: 10.51393/j.jamst.2025012
Citation: Haidong YANG, Libao ZHANG, Haodong LI, Junsheng ZHANG, Huohong TANG, Shunhua CHEN. Influence of tool corner radius on chip geometrical characteristics of machining Zr-based bulk metallic glass[J]. Journal of Advanced Manufacturing Science and Technology . DOI: 10.51393/j.jamst.2025012

Influence of tool corner radius on chip geometrical characteristics of machining Zr-based bulk metallic glass

  • The effect of tool corner radius on the chip geometrical characteristics of low-speed cutting Zr57Cu20Al10Ni8Ti5 bulk metallic glass (at%, noted as Zr57 BMG) were studied. Additionally, traditional industrial pure zirconium (Zr702), titanium alloy (TC4), and 45 steel were selected as comparative materials. Continuous ribbon-shaped chips were formed during the turning of Zr57 BMG. The observable burrs were the result of chip tearing and dropping off layer by layer along multiple scratches. Serrated chips with numerous secondary shear bands (SSBs) were generated during the machining of Zr57 BMG. As the corner radius increased from 0.4 to 1.6 mm, the serration pitch P decreased from 29.68 to 6.2 μm, showing an increase in serrated frequency. Besides, the formation of BMG chips is associated with multiple shear behaviors. The stability of the serrated chip formation was quantitatively analyzed using three-parameter Weibull statistical analysis. Generally, the Weibull modulus of the inclination angles for serrated chips increased with the increase of corner radius, indicating that the chip formation process was more stable, which was conducive to superior machined surface quality. The machined surface roughness Ra decreased from 0.5 to 0.23 μm, which was consistent with the Weibull results. This work is of significant importance for understanding the state of the machining process from the perspective of chip characteristics.
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