Stopping the Infiltration of Counterfeit Hardware through AI

We are very fortunate to have Dr. Eyal Weiss for today’s episode. He is the CTO and founder of Cybord, an AI tool for detecting counterfeit hardware and electrical components.

This is a very exciting conversation. We will talk about a better, practical applications of AI in the electronics industry, outside of design.

Watch through the end and make sure to check all the additional links and resources below.

Watch the episode here.

Show Highlights:

• Introduction to Dr. Eyal Weiss, CTO and founder of Cybord an AI tool for detecting counterfeit hardware and components
• Dr. Eyal Weiss's company is using AI-based component inspection services to detect counterfeits and ensure component quality.
• The system utilizes images of individual components taken during the placement process, leveraging big data and deep learning technology.
• The software integrates seamlessly with existing pick-and-place machines' internal vision systems, making it a plug-and-play solution.
• AI plays a crucial role in understanding and processing the vast diversity of component types, enabling accurate identification and fingerprinting of individual components.
• Most component failures are due to component-level issues, not board-level failures, making it crucial to focus on component quality.
• The traditional industry approach treats components as bulks, similar to handling grains, without addressing them individually.
• AI and big data technology now enable the ability to address components as individuals, allowing for better traceability and targeted recalls.
• Dr. Eyal Weiss's company uses AI and image analysis to examine individual components, providing detailed information about quality, authenticity, and potential defects.
• By analyzing individual components using AI-based inspection, manufacturers can conduct more targeted and efficient recalls based on specific fingerprint information.
• AI-driven analysis can also identify mismatches in traceability information, preventing wrong recalls and improving recall precision by targeting smaller groups of components.
• The AI system uses image recognition and natural language processing to interpret component markings and extract relevant data for traceability.
• The individual component level traceability is recommended in the latest IPC standard (IPC-1782B) and can provide the highest level of traceability with minimal additional cost.
• The AI system's feedback allows OEMs and CMs to improve their processes and make informed decisions on recalls, ensuring a win-win situation for both parties.
• Dr. Weiss wishes everyone success and a lifetime of no recalls ;)

Links and Resources:

• Read related articles:

  • The Path Forward for Embedded AI

  • Bringing AI to Market the Easy Way

• Connect with Dr. Eyal Weiss on LinkedIn

• Visit Cybord website

• Learn more about the IPC-1782

• Visit Octopart.com, the Electronic Parts Search Engine