Predictive Force Modeling in MQL (Minimum Quantity Lubrication) Grinding

Using grinding fluid is the most common strategy to generate cooling and lubrication during the grinding process. However, economic and environmental drawbacks have been noticed for conventional flood cooling. MQL, which is to apply minimum amount of lubricant directly into the contact zone, is an alternative to deal with those concerns. In order to advance the MQL technique into practical manufacturing situations, understanding of the process and evaluation of the performance is necessary. This paper presents the predictive modeling of MQL grinding force through considerations of boundary lubrication condition, single grit interaction, wheel topography, material properties, and dynamic effects. The friction coefficient was first calculated based on boundary lubrication theory. Subsequently, the single grit interaction is studied considering both chip formation and ploughing mechanisms. Then the undeformed chip thickness distribution and dynamic grit density has been calculated for extrapolating the single grit interaction to the whole wheel. Finally, the predicted tangential and normal forces were presented and compared to surface grinding experiment data.