Deep neural network (DNN)-based potential defect detection and classification method for through silicon via (TSV) in 2.5D & 3D packaging

Abstract

In this paper, we propose a deep neural network (DNN)-based potential defect detection and classification method for through silicon via (TSV) in 2.5D & 3D packaging. In order to overcome the limitations of the existing analysis method, this paper applied the signal integrity analysis method to search for potential defects that cause quality problems, and additionally applied a deep neural network (DNN) to confirm that it is a faster and more accurate method than the existing analysis method. To verify the proposed method, the level and location of potential defects were applied by type to the structure to which the through silicon via was applied, and the results obtained through the signal integrity analysis method and the deep neural network were compared. In addition, the effectiveness of the proposed method was confirmed by applying the proposed method to high bandwidth memory (HBM), which is a representative package with through silicon via.