Grey Prediction on Sheared Edge Quality in Precision Blanking Process for Micro IT Parts

Sheared edge quality of micro IT parts is an important standard to evaluate product quality. In this paper, a prediction model of sheared edge quality based on grey prediction is studied. By mapping the stroke and the burr width to be the time increment and the eigenvalue of grey system, the grey prediction model was established. The dynamic regularity of burr in actual production was attained from the precision blanking experiment and the prediction of burr width was performed. The results show that the model can predict burr width accurately and needs less sampling data. Thus, it is fit for the requirement of manufacturing.