Automated Detection and Localization of Counterfeit Chip Defects by Texture Analysis in Infrared (IR) Domain

Abstract

Today's globalized supply chain for electronics design, fabrication, and distribution has resulted in a proliferation of counterfeit chips. Recycled and remarked chips are the most common counterfeit types in the market, and prior work has shown that physical inspection is the best approach to detect them. However, it can be time-consuming, expensive, and destructive while relying on the use of subject matter experts. This paper proposes a low-cost, automated detection technique that examines surface variations within and between chips to identify defective chips. Further, it can estimate the location of the defects for additional analysis. The proposed method only requires a cheap IR camera-based setup to capture images of the chip package surface and is completely unsupervised and non-destructive. Experimental results on 25 chips in our lab demonstrate 100% detection accuracy.