Grinding force and power modeling based on chip thickness analysis

Abstract

The ability to predict grinding force and power is important to many aspects of grinding process optimization, monitoring, and control. This paper presents the predictive modeling of grinding force and power based on the probabilistic distribution of undeformed chip thickness as a function of the kinematic conditions, material properties, wheel microstructure, and dynamic effects. The chip thickness is the main random variable and it is expected to assume a Rayleigh probability density function. The model takes into account the microstructure of the grinding wheel given by the grain geometry and the static grain density in terms of the radial depth into the wheel. The dynamic cutting edge density was calculated incorporating the effects of kinematic and dynamic phenomena such as the kinematic hidden grains and the local grain deflection. The elastic deformation of the grinding contact length was also considered. The model was used to predict the total tangential and normal forces in surface grinding and the total grinding power in cylindrical grinding. In both cases experimental measurement data in the context of chip thickness probability density, tangential force, normal force, and power have been presented and compared to model calculations.