Use case of

Cybord

tag
Electronic Manufacturing [EM]
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High level customers
Extensive pilot for Nvidia (Mellanox) done with cooperation of FLEX at FELX facilities. Ongoing pilot at Elbit systems Ongoing pilot at Siemens labs berlin
Digital assets
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What Challenges are you solving in this industry

  • Improving Process Productivity/Yield - Asset/Process performance management [APY]

  • Improving Quality (inspection process control) [QI]

  • Supply-chain efficiency and visibility [SCE]

Description of solution

Cybord’s software solution validates electronic components’ conformance during product assembly and arms OEMs and EMSs with a new resolution of traceability.
Based on AI and big data, Cybord’s technology inspects every electronic component prior to placement on the PCB.
An AI technology prevents nonconforming (counterfeit, defective, expired) and cyber-tampered material from getting assembled.
Alongside this inspection, Cybord creates placement traceability (as-made certificate) that combines material inspection, documentation, and visual imagery to establish material provenance with simple board/component tracking.
Manufacturers enjoy a dashboard view of all assembled components, assembled boards, and traceability data from multiple production sites and contract manufacturers.

What is the value you bring to your customers?

It is estimated that supply chain contamination rates vary between 0.5% and 20%, depending on the industry. Over 85% of hardware failure is due to nonconforming material. In this context, Cybord offers customers the following advantages:

– Prevention of internal and external failure, lower hardware return rates, and fewer repairs (at least 30% of returned goods are attributed to hardware failure).
– Smart manufacturing i4.0 for OEMs – first of its kind, real-time visibility and actionable alerts into assembled electronic components and the supply chain materials across sites and suppliers.
– Smart manufacturing i4.0 for EMS – real-time failure prevention reduces internal failure costs caused by nonconforming material and enriches AI quality data with collected data.
– Hardware cyber-security clearance.
– Ensuring high reliability – maintaining brand reputation and lowering liability risks.
– A reduction in product returns due to electronic failure to 0.1% results in a profit improvement of between 0.5% and 5%.
-Poor material prevention yields a 50% reduction in rework costs.
-Eliminating hardware-based cyberattacks that cost millions of dollars per year

Time to implementation

1-2 month