A grinding force predictive model and experimental validation for the laser-assisted grinding (LAG) process of zirconia ceramic

Abstract

Laser-assisted grinding (LAG), as a potential machining method, is expected to achieve high-efficiency machining without any surface damage or sub-surface damage. However, grinding force tends to exert serious impact on the surface damage during LAG process. In this paper, a grinding force predictive model for the LAG process was established, which has taken the combined effects of temperature-dependent mechanical properties of the material, statuses of grit-material micro interaction, and stochastic shapes and random distributions of abrasive grits into consideration. This model also reveals the mechanism for the reduction of grinding force during LAG. In the meantime, the simulative grinding force distributions of workpiece surface with different laser powers were obtained. LAG experiments of zirconia ceramic were carried out to validate this model. It is found that the modelled forces are in good agreement with the measured forces and the error rates can be confined within 12 %. In addition, the effect of grinding parameters on grinding force has been investigated. It is demonstrated that the grinding force can be reduced by a certain percentage ranging from 29.4%–60.1% using the optimal machining parameters. Within a certain threshold, higher laser power can improve the surface integrity and decrease the depth of damage. This work is expected to provide significant guidance for promoting the development of the laser-assisted machining technologies.