Contour based process characterization and modeling for HVM

In this paper, we present the flow and results of contour-based process characterization, modeling and control used for semiconductor manufacturing. First, high-quality contours are extracted from large field of view (FOV) SEM images based on the improved Canny edge detection algorithm. Prior to the contour analysis steps, SEM image distortion correction is performed by using the low-order linear model. When there are repeating cells within one FOV, the N-sigma roughness band of the unit cell is calculated to show the stochastic process variation fingerprint. For SEM images collected from a focus-exposure matrix wafer, the contourbased process window analysis is performed to generate the depth-of-focus map for the full image, enabling precise detection of process window limiting locations. Finally, 3D compact resist models are calibrated by using both inner and outer contours from the same SEM images, which proves to be effective for the prediction of resist top loss related hotspots.