Automated image analysis for evaluation of wafer backside chipping

Abstract

When a silicon wafer is cut into separate dies, their front and back sides might have chipping resulting in die cracks and yield loss. To prevent defect formation, silicon wafers should undergo optical inspection for evaluation of wafer chipping, its size, and its shape. This work proposes an automated method of image processing that includes die edge detection, die street search, and determination of chipping size and shape. Die edge search was done using an Otsu’s thresholding method. This technique was chosen out as the optimal of the five ones. The choice was based on the segmentation precision evaluation of two types of images: with sharp and blurred edges. Die street search was done using a developed algorithm capable of processing images with angular displacement. Chipping shape and size were calculated through die edge displacement from the die street. Based on the numerical evaluation of chipping size and shape, a chipping danger metric that may be used for detection of defective dies has been proposed.