Abstract
In the process of micro-removal machining SiCp/Al, the real-time prediction of cutting force is of great significance to ensure the surface quality of the workpiece and safe production. Based on the two major sources of cutting forces: the elastic-plastic deformation resistance of the machined material and the friction between the tool and the material, this paper established an ultrasonic vibration-assisted scratching force model by considering four aspects: chip formation force, SiC particle breaking force, tool and Al matrix friction force and rolling friction force. The model was experimentally validated by a self-built ultrasonic scratching device, and the effects of scratching speed, SiC particle volume fraction, and ultrasonic amplitude on the scratching force were investigated. The results showed that the scratching force is minimum when the scratching speed is 400 mm/min for both ordinary scratching (OS) and ultrasonic vibration-assisted scratching (UVAS). As the volume fraction of SiC particles increases, the scratching force gradually increases. Under the same experimental conditions, the force of UVAS is much smaller than OS. The maximum error between the experimental value and the predicted value of the model is 33% and gradually decreases with the increase of scratching speed and SiC volume fraction. The overall trend of the two is consistent, which proves the feasibility of the scratching force model. This study can provide some theoretical guidance for the force control when machining SiCp/Al. The ultrasonic vibration-assisted scratching force model was established by considering the chip formation force, SiC particle breaking force, tool matrix friction force, rolling friction force and ultrasonic vibration applied. And the model was verified by experiments. • A new machining process of ultrasonic vibration-assisted scratching was proposed. • An ultrasonic vibration-assisted scratching force model was established. • The experimental values were in good agreement with the model predicted value, which verified the feasibility of the established model.
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