X-ray inspection of TSV defects with self-organizing map network and Otsu algorithm. (December 2016)

• Record Type: Journal Article
• Authors: Shen, Junjie; Chen, Pengfei; Su, Lei; Shi, Tielin; Tang, Zirong; Liao, Guanglan
• Is Part Of: Microelectronics and reliability. Volume 67(2016)
• Page Start: 129
• Page End: 134
• Publication Date: 2016-12
• Subjects: TSV -- Defects inspection -- X-ray -- Self-organizing map network -- Otsu algorithm; Electronic apparatus and appliances -- Reliability -- Periodicals; Miniature electronic equipment -- Periodicals; Appareils électroniques -- Fiabilité -- Périodiques; Équipement électronique miniaturisé -- Périodiques; Electronic apparatus and appliances -- Reliability; Miniature electronic equipment; Periodicals; 621.3815
• DOI: 10.1016/j.microrel.2016.10.011
• Languages: English
• ISSNs: 0026-2714

Abstract

Abstract: Through-silicon via (TSV) is one of the most critical elements in 3D integration, where defects such as unfilled bottom and holes are very common. Thus, defect detection is of great importance to improve products quality. In this work, a non-destructive TSV defect detection method using X-ray imaging is introduced. Seven features representative of TSVs are extracted from the images, and then inputted into a self-organizing map (SOM) network for classification and testing. The results demonstrate that the normal TSVs and defective TSVs can be distinguished obviously by SOM network. The voids inside the TSVs are further located qualitatively using the Otsu algorithm and verified by the SEM images. These prove the feasibility of X-ray inspection of TSV defects with SOM network and Otsu algorithm. Highlights: The SOM network can accurately distinguish normal TSVs from defective TSVs. The Otsu method is useful for locating TSV voids qualitatively. It is feasible for X-ray inspection of TSV defects with SOM and Otsu.