Yamin Shao

Predictive Modeling of Surface Roughness in Grinding of Ceramics

The surface roughness represents the quality of ground surface since irregularities on the surface may form nucleation for cracks or corrosion and thus degrade the mechanical properties of the component. The surface generation mechanism in grinding of ceramic materials could behave as a mixture of plastic flow and brittle fracture, while the extent of the mixture hinges upon certain process parameters and material properties. The resulting surface profile can be distinctively different from these two mechanisms. In this article, a physics-based model is proposed to predict the surface roughness in grinding of ceramic materials considering the combined effect of brittle and ductile material removal. The random distribution of cutting edges is first described by a Rayleigh probability function. Afterwards, surface profile generated by brittle mode grinding is characterized via indentation mechanics approach. Last, the surface roughness is modeled through a probabilistic analysis of ductile and brittle generated surface profile. The model expresses the surface finish as a function of the wheel microstructure, the process conditions, and the material properties. The predictions are compared with experimental results from grinding of silicon carbide and silicon nitride workpieces (SiC and Si3N4, respectively) using a diamond wheel.

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.Copyright

Phase Transition at High Heating Rate and Strain Rate During Maraging Steel C250 Grinding

In this study, maraging steel kinetics of both diffusion-controlled and diffusionless phase transitions under thermo-mechanical conditions was predicted using a physics-based model via the investigation of heating rate, stain rate, and contact zone temperature during grinding. It was assumed that high heating rate and high strain rate will affect phase transition. The theory of phase transition nucleation was combined with analysis of heating rate, stain rate, and contact zone temperature to predict phase transition during the grinding. The effects of heating rate and strain rate on phase transition were verified through maraging steel grinding experiments, X-ray diffractometry, and regression analyses. The results of post-grinding phase volume fractions of martensite and ferrite were compared with the results predicted from the neural network model, and models without consideration of heating rate or strain rate. Validation tests proved that the proposed physics-based model successfully predicted the occurrence and extent of phase transition associated with heating rate and strain rate. This physics-based model can be used to reduce phase transition during grinding of maraging steel, or to cause a predefined phase transition by controlling the thermo-mechanical loading.

Prediction of Residual Stress in Multi-Step Orthogonal Cutting

The effect of residual stresses on the fatigue behavior as well as the dimensional stability of high precision part is very important. Machining operation consists generally multi-step operations from roughing to finishing. It is therefore critical to predict residual stresses under such configuration. In this paper, an analytical algorithm is proposed to predict the final residual stresses induced by a multi-step machining operation capturing the change of stress state of the workpiece as well as material hardening behavior during the multi-step orthogonal cutting. The model predictions were compared to other work’s finite element method (FEM) predictions.Copyright