FAQ

Cybord provides an AI-driven software solution that’s seamlessly integrated into pick-and-place and AOI machines and visually analyzes every component placed on the PCB. With Cybord you can easily enforce AVL, get accurate visually verified traceability, and meet regulation like IPC-A-610 (AS9100, ISO26262… based on industry)

We inspect both the bottom-side and top-side of every component. The platform detects issues like body defects, tampering, authenticity, contaminations, bent leads, and setup failures. Additionally, we collect information such as country of origin, lot code, date code, MPNs and more. All this is stored in a data repository and accessed via our console.

No. Many customers prefer to have this data “injected” into their existing MES or BI systems by API.

To allow real-time processing Cybord requires an edge computer to be installed. A single edge computer can support multiple SMT lines.

The data is processed on the local edge computer. The analyzed data is stored in AWS.

Of course. The data is encrypted meeting all the required security standards.

The solution is designed for real-time calculations. The data can be made accessible >> RTI, the data is available in ms cos the machine react in real time to the analyzed results… All the rest – trace..rep… is accessible within 1 minute

We’re one of Fuji America’s preferred technology partners, delivering AI solutions to SMT customers. In essence it means that our solution is available to all Fuji customers as an add-on to their P&P Machines.

No. Our solution can be easily integrated into any P&P or AOI machine. In fact our customers use a variety of brands including ASMPT, Yamaha, Koh Young, Vitrox and others.

Absolutely! Cybord thrives in multi-vendor environments. Our high-scalability system powered by AI and big data gets better at identifying components the more variety it sees. This means Cybord can effectively manage component inspection from all your approved vendors on the AVL.

P&P machines are primarily designed for placement accuracy. They excel at verifying a component’s presence and orientation to ensure it’s positioned correctly on the board. However, P&P machines typically don’t inspect for component quality, authenticity, or defects.

Cybord’s traceability system is designed to handle inconsistencies in component text. Our AI engine is trained on a vast library of component markings and can recognize patterns even when the text font, size, or position varies slightly. Cybord’s algorithms can also learn and adapt to new component variations over time, ensuring reliable identification.

For advanced ICs containing unique identification data, can Cybord’s platform be used to capture and extract this specific information?

Cybord is designed to operate seamlessly within your production line. The system doesn’t directly stop the line. Instead, it communicates potential issues to your MES or ERP system. This allows you to define the appropriate actions, such as flagging the component for review or halting production entirely. Furthermore, Cybord boasts an exceptionally low false positive rate of less than 0.01%, minimizing the risk of unnecessary slowdowns.

Production volume doesn’t limit the benefits of Cybord’s platform. It can efficiently handle high-speed lines, producing large quantities of similar parts or lower-volume lines with a greater mix of components.

Cybord traceability goes beyond traditional systems that simply log data points during production. It offers a layer of visual validation, verifying the physical components match the data record. This additional layer strengthens your existing traceability system by ensuring the accuracy of the information collected. Think of Cybord as a complement to your current system, not a replacement.

Some AOI machines can use OCR to read component markings. However, OCR typically decodes the text itself, not its meaning. Cybord goes a step further by leveraging AI to interpret the information extracted by OCR. This allows us to translate the component markings into valuable data that can be used for traceability validation.