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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