Grinding force modeling considering the combined effect of abrasive grit diverse characteristics and intermittent cutting in ultrasonic vibration-assisted grinding of nickel-based superalloy

• Combined effect of grit diverse characteristics and intermittent cutting is revealed • Probability superposition method is effective for grinding force prediction in UVAG • Undeformed chip thickness and exposure height of grits follow a linear relationship • UVAG performs better at higher grinding depths and larger ultrasonic amplitudes • The grinding force model yields an average prediction error of 7.5% Inconel 718 nickel-based superalloy is a representative hard-to-cut material with excellent comprehensive thermomechanical properties, and it has marked promising prospect in the field of aerospace engineering. Ultrasonic vibration-assisted grinding is an advanced machining technology for improving the efficiency and surface quality. However, the diverse characteristics of abrasive grits on the grinding wheel surface and the application of ultrasonic vibration increase the complexity of the material removal mechanism. In the study, an analytical grinding force model was developed considering the varying exposure heights of abrasive grits and the intermittent cutting behaviour. The influence of multiple grinding path intersections and the interaction effect between undeformed chip thickness and quantity of effective abrasive grits were revealed. The results indicate that ultrasonic vibration helps maintain the grinding temperature stably below 100 °C and increases the maximum material removal rate by 20%. The maximum undeformed chip thickness has a negative linear relationship with the boundary exposure height of effective abrasive grits, and the parameters of this relationship are mainly associated with grinding wheel characteristics. Ultrasonic vibration exhibits better performance at higher grinding depths and larger ultrasonic amplitudes, owing to the increased workpiece infeed distance during cutting interval of abrasive grits and the extended grinding arc length. The model yields an average prediction error of 7.5% and a maximum prediction error of 14.9%. The grinding force can be reduced by a maximum of 30% at an ultrasonic amplitude of 8 μm.