19.02.2023

Faulty Components Analysis

Faulty Components Analysis: Cybord Visual AI Platform inspects electronic products during the assembly process. This reduces the risk of malfunction, and increasing safety and reliability. The platform aggregates and analyzes images and data from all components at various production stages. The process ensures authenticity, product quality, and traceability.

The video clip provides an example of the AirAsia Flight QZ8501 crash in 2014, where the primary cause of the accident was a malfunction in the aircraft’s rudder travel limiter unit (RTLU), a result of a cracked solder joint.

Cybord Visual AI Platform provides valuable insights and enables real-time decision-making by identifying potential issues early in the production process and addressing these issues before the product reaches the market. The Cybord Visual AI Platform can improve safety and efficiency in the electronics industry.

Faulty Components Analysis

Cybord was founded by Dr. Eyal Weiss, following a crisis in a defense mega project, due to counterfeit electronic components. It took his team months to trace the problem down to a 3 cents faulty capacitor.

Following this incident and by perceiving the understanding of the vast phenomenon of defective and counterfeit components, Cybord has taken on a mission to get counterfeit and defective components off production lines.

The Cybord Deep Visual-AI platform aggregates and analyzes images and data from 100% of the electronic components. It combines existing production data and unique new visual data collection, and ensures product quality, authenticity, and traceability, for OEMs and EMSs.

Read Next: Early Detection of Corrosion-Induced Failures in Electronic Components

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An Earthquake Exposed More Than a Supply Chain Risk. It Exposed a Visibility Problem.

The recent Kumamoto earthquake is a reminder that regional disruptions can quickly ripple through the global electronics supply chain—just as the Fukushima disaster did in 2011. Most OEMs have supplier diversification policies and approved alternative vendors. The real question is whether those alternatives are actually being used in production. In one OEM analysis, the Approved Vendor List (AVL) showed a highly diversified sourcing strategy, yet production data revealed that nearly 30% of components were sourced from a single supplier, creating a hidden concentration risk. Supply chain disruptions don't create hidden dependencies—they expose them. Visual AI enables manufacturers to continuously measure supplier concentration from the products they actually build, turning diversification from a policy into a measurable reality.

Who Verifies the Chip That Verifies Everything Else?

Intel and Fortinet are jointly developing Fortinet's next generation security processor, SP6, in part to build a more resilient, diversified supply chain. A security chip is still a chip. Once SP6 leaves the fab, it has to survive the same assembly process as every other component, the process where substitution and counterfeiting actually happen. Standard checks, documentation, batch traceability, sampling, confirm what should be true. Only Visual AI, verifying every component's markings, lot and date code, and country of origin as it's placed, confirms what is true. Cybord has already flagged over 30 major non-AVL substitution events in the first six months of the year. None were counterfeits. All were wrong parts that reached the line undetected by standard inspection. For telecom and datacom OEMs, the question isn't whether SP6 performs. It's whether you can prove the SP6 on the board is the genuine part, at the silicon level, every time.

The Tectonic Shift in Electronic Supply Chain Assurance

DFARS Case 2022-D011 marks a shift from documentation to proof, requiring defense suppliers to verify hardware provenance rather than rely solely on paper records. The new rule secures where PCBs come from, but not what gets assembled onto them, leaving component-level risks such as counterfeits, substitutions, and unauthorized parts largely unaddressed. Traditional inspection tools verify manufacturing quality—not component authenticity. Visual AI adds evidence by analyzing the physical characteristics of every installed component to confirm it matches approved hardware. As provenance requirements continue to expand, manufacturers that can provide image-based proof of authentic, approved hardware will gain both a compliance and competitive advantage

Europe’s CHIPS Act 2.0: The Assembly Gap Nobody Is Talking About

Europe’s CHIPS Act 2.0 targets fabs, but final assembly still happens offshore. Here’s why component-level transparency must be part of the strategy.