Abstract: Shortages in electronic components are a known fact in the industry. Currently, the IC market is suffering from a shortage caused by the COVID-19 pandemic and the increase in demand. Shortages are forcing electronic manufacturers to depart from their trusted sources who cannot supply components in practical times and purchase components in the free market. This purchasing shift is increasing the risk of counterfeit, out-of-date, mixed lots, badly handled, recycled, and defective components from the standard 0.5-2% when purchasing from trusted sources to 5-10% of purchasing in the free market. This risk is conventionally mitigated by performing lab tests on components purchased in the free market according to SAE AS6081. However, sampling a small fraction of the components may not be enough. This is because lab testing does not address out-of-date, mixed lots, badly handled, or defective components which may be randomly scattered within a package. Inspecting the entire reel population is essential for meeting reliability expectations, but lab inspection services cannot scale efficiently to support this requirement. The digital transformation of the electronic component inspection process removes the dependence on human judgment and demanding labor. We present a patented software solution that visually inspects and detects suspect and fraudulent components. Using artificial intelligence, big data, and integration with SMT pick and place vision systems and sensors, the software achieves 100% component inspection coverage and accuracy exceeding 99.5%. Detection of the suspect and fraudulent components is reported to enterprise management systems. Siemens has partnered with Cybord to enhance Siemens electronic manufacturing traceability and digital twin solutions with an unprecedented level of surgical traceability. Providing full traceability about the source of each and every component, it enriches existing Siemens manufacturing material traceability data and Opcenter material management. The solution support industry with solution from Supply chain to product end of life.

Bio: Dr. Eyal Weiss received his B.Sc. cum laude in Mechanical Engineering from the Technion-Israel Institute of Technology, Haifa in 1995, his M.Sc. in Plasma Physics from the Technion–Israel Institute of Technology, Haifa in 2001, and his Ph.D. in Electronic and Computer Engineering from Ben-Gurion University of the Negev, Beer-Sheba in 2014. He worked for 6 years as a researcher on pulsed plasma at Soreq Research Center (SNRC). He then worked for 5 years in the fiber-optics high-tech industry as a technology department manager. He returned to Soreq SNRC, and for 12 years served as manager and leading scientist of the R&D Systems Department. In 2018, he founded and became CTO of Cybord, developing electronic component authentication technologies. He specializes in multidisciplinary technology development and has received major awards and accolades in the fields of machine learning, plasma physics, optical assemblies, laser technology, and electromagnetics, including twice the prestigious Israel Defence Prize. Dr. Weiss is an expert in technology development.

Bio: Tovi Yadin is an Innovation Solutions Manager at Siemens Digital Industries Software. Tovi is passionate about leveraging advanced technologies such as AI and ML to optimize and automate manufacturing processes. She brings extensive expertise in electronic manufacturing processes and a strong business and technical background to her current role, where she focuses on smart manufacturing and Industry 4.0, promoting Siemens' data-driven manufacturing initiative.