Die level defects detection in semiconductor units

Abstract

The assembly test process has many steps where defects can be created at any time during different stages. Detecting defects at early stages is very crucial and saves a lot of cost and time by isolating the defective parts from further processing. Detecting defects on the die area of the semiconductor units is a challenging procedure due to the fact that die's defects exhibits large variations in intensity and shape. The existing manual and automated inspection approaches still produce high rate of under-rejection and over-rejection which impacts the yield and adds significant cost to the inspected unit. A robust die level defect detection procedure is presented in this paper in order to come up with a solution that is cheaper, easier to sustain, and that would automatically inspect each unit for defects providing for efficient baseline characterization and rapid excursion detection. The proposed method gives a higher detection rate of die level defects with under-rejecting and overrejection rates within the acceptable criteria.

Similarity based ART 1 model for automatic die defect detection and classification

“…For example, analyzing the defect distribution [1]- [3] and monitoring in the manufacturing fabrication [4]- [6] are proposed. Assad et al [7] proposed a defect detection method on the die level. Wang et al [8] proposed an automatic optical inspection method by using the Gaussian EM algorithm and spherical-shell algorithm to classify the defects.…”