Mathematical modeling and experimental verification of surface roughness in micro-end-milling

Surface roughness is crucial for evaluating the surface quality of machined parts. In this study, a mathematical model for accurately predicting surface roughness is proposed by surface generated based on the trajectory of cutting edge, which comprehensively considered the geometry of tool and cutting parameters. The novelty of this research is consideration of the material's elastic recovery into the surface profile generated in the presence of the tool run-out effect. The calculation of surface roughness has considered the combination of the minimum uncut chip thickness (MUCT), tool run-out, and the material's elastic recovery. Furthermore, tool run-out has been identified by a non-contact method using three displacement sensors. To assess the accuracy of the proposed surface roughness model, a set of experiments for full slot micro-end-milling are carried out and surface roughness is measured and compared to that predicted. The results indicated that the surface roughness predicted is well in agreement with that experimental measured. Some conclusions can be drawn that elastic recovery can more obviously affect the surface roughness predicted with smaller feed per tooth; the errors between measured and predicted are getting smaller with the feed per tooth increasing.