Automated Physical Inspection for Counterfeit Electronics Detection and Avoidance

Counterfeit electronics in the supply chain are a longstanding issue with nontrivial impacts on government, industry, and society as a whole: (i) security and reliability risks for critical systems and infrastructures that incorporate them; (ii) substantial economic losses for IP owners; (iii) source of revenue for terrorist groups and organized crime; (iv) reduce the incentive to develop new products and ideas, thereby impacting worldwide innovation, economic growth, and employment. The counterfeit chip market has an estimated worldwide value of $75B, and such chips are then integrated into electronic devices reportedly worth more than $169. The ongoing chip shortage due to the COVID-19 pandemic exacerbates the situation by creating huge gaps in the supply chain.

FINS is currently engaged  in research that focuses on using AI, image processing, and computer vision to address the challenges associated with non-invasive physical inspection for counterfeit integrated circuit (IC) and printed circuit board (PCB) detection. Namely, by automating identification of the defects associated with counterfeits, we can reduce the time, costs, and need for subject matter experts. This technology is envisioned for use by non-technical, minimally trained operators such as border agents at U.S. Ports of Entry.