Prediction of machined surface roughness during the high-speed machining of Zr-based bulk metallic glasses

Abstract

A theoretical model of surface roughness prediction for high-speed machining Zr-based bulk metallic glasses was established. The roughness components of the prediction model, including plastic side flow, material recovery, cutting vibration and kinematics were discussed. The cutting forces and machined surface morphology were studied to characterize the cutting vibration and plastic side flow, respectively. Specially, the cutting vibration during machining was characterized with radial force amplitude. The surface morphology of the Zr-based bulk metallic glass (BMG) was mainly characterized with plastic flow traces, molten droplets, dimples, adhensions and ploughing marks. The presence of material recovery would effectively improve the surface quality and, on the contrary, the presence of plastic side flow would deteriorate it. Finally, the surface roughness prediction model was validated with turning experiments under varying tool geometric parameters, and the calculated surface roughness showed good agreement with the measured results. The present results are beneficial to revealing the underlying mechanisms for machined surface roughness, and can provide basis for optimizing cutting parameters and surface quality for industry.