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Devon Richman
Abstract: Traditional lab testing for counterfeit microelectronics has long been accepted as the method of choice; however, it was not until 2016 when SAE AS6171 and its slash sheets were published that a standard focused solely on testing for the detection of suspect counterfeit parts. Counterfeit electronic parts and counterfeit testing have existed for decades, but no systematic assessment has previously been reported on the effectiveness of conventional, and more recently standards-based testing. In 2019, CALCE began a DMEA-sponsored project to investigate techniques for detection and authentication of counterfeit microelectronic parts. This study, which concluded in December 2020, included a comparative evaluation of side channel methods, machine vision technologies, and conventional laboratory testing based on the SAE AS6171 standard. In partnership with SMT Corporation, CALCE led a blind study using eleven different microelectronic parts, for which both authentic and counterfeit parts (including clones) were provided to the test organizations participating in the study.
Five different part numbers, including remarked/recycled (conventional) and cloned counterfeit devices, were included in the standards-based portion of the study. Participating labs provided CALCE with reports for each part number, including defect sheets outlining which defects, from the 69 outlined in AS6171, were observed using a given test method. Analysis of the results shows numerous factors that impact the effectiveness of various testing methods and why having a standard in place is critical to accurate counterfeit detection. Results showed substantial differences in the defects reported by different labs. The study has provided essential information and demonstrates that standards-based methods are effective in finding remarked/recycled and cloned counterfeits, so long as the standard is followed. External visual inspection was particularly effective across all parts tested.
Side channel and machine vision methods were assessed for their suitability for part authentication, wherein part signatures could be logged into a database when their chain of custody to the original component manufacturer was still established. Each lab was provided a different set of part numbers. Most of the provided part numbers were clones. The side channel methods and machine vision methods were also assessed for their technology readiness for real-world implementation. Side channel methods displayed the ability to accurately separate and cluster authentic and counterfeit devices. Machine vision methods were able to accurately identify parts which had been registered. Both methods show promise for use in counterfeit detection and prevention, although further development is needed.
Bio: Mr. Devon Richman is a third-year Ph.D. student at the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland College Park. He received his Bachelor's degree in Mechanical Engineering from the University of Maryland. He is an active member of the SAE G-19A Test Laboratory Standards Development Committee as well as a technical expert for the ANSI National Accreditation Board for SAE AS6171. Mr. Richman’s primary research interests are the detection of counterfeit microelectronics and failure analysis of electronics. He has worked on the analysis of current standards-based methods as well as newly developing detection systems. He has performed failure analysis for industry leaders including General Electric.
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