A novel wafer edge quality inspection method based on analyzing curved-edge diffraction patterns is introduced in this paper. The diffraction patters, being collected through two approaches: (1) single point scanning method and (2) areal imaging method, are affected by edge topography, edge geometry and defects. After applying statistical feature extraction methods and wavelet transform to the collected fringe data, corresponding features of various defect modes were further extracted. In summary, both proposed methods enabled characterization and identification of various wafer edge defect modes and shed light on automatically wafer edge defects detection and categorization.
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