Enhancing the runtime environment to maximize inspection functionality! Troubles with debugging and customization have been resolved, making the introduction of AI to the field significantly easier.
Roxy AI, which enables high-speed and high-precision inspections, has become even easier to use. Are you facing any of the following issues when trying to implement AI on-site? - Custom development is needed to connect AI inspection products and devices, resulting in unexpected costs... - When there is a malfunction, it is difficult to investigate whether the issue is with the AI or the device... - Only limited devices specified by the vendor can be connected... - Unable to create inspection devices as envisioned due to unmet needs... To address these challenges, Roxy AI has revamped the "runtime functionality" used in inspection devices. This not only allows for high-precision inspections but also makes on-site implementation simpler and enables more flexible inspections. ■ Strengthening the Runtime Environment - Debugging Function Added a console feature that allows you to define inspection sequences and debug them on the spot. Data flowing through the sequence can also be visualized, allowing for immediate correction of mistakes. - Custom Development Customization is possible for external device integration, camera input, rule-based inspections, and various outputs. By simply implementing straightforward rules in C#, you can accommodate your unique requirements. *For more details, please download the materials or contact us via our website.
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**Details of Version Upgrade** ■Strengthening of Runtime Environment - Debugging Function A console feature has been added that allows you to define inspection sequences and debug on the spot. You can also visualize the data flowing through the sequence, so any mistakes can be corrected immediately. - Custom Development Customization is possible for external device integration, camera input, rule-based inspection, and various outputs. By simply implementing it in C# according to simple rules, you can meet your unique requirements. ■Enhancements to Learning Environment - Added various image transformation functions such as trimming, alignment, resizing, and masking. This allows for greater adaptability to various situations than ever before. The order of transformations and various parameters applied in the learning environment can be easily restored in the runtime environment, preventing discrepancies in AI inspection results due to differences in parameters between learning and inspection phases. *For more details, please download the PDF or feel free to contact us.*
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【Usage Scenarios】 ■ Detect various types of defects (such as scratches and discoloration) ■ Detect foreign objects like metal fragments, cardboard, and hair mixed in with products ■ Detect products or materials left on conveyor belts or cleaning equipment ■ Other inspections that are generally checked visually by humans *For more details, please download the PDF or contact us.
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In small and medium-sized enterprises that support a large part of the manufacturing industry, it is difficult to secure engineers who are knowledgeable about AI. Additionally, in environments that are forced to produce small quantities of a wide variety of products, it is not realistic to outsource AI development each time. What is needed now is "AI that can be effectively utilized on-site." "Being able to effectively utilize it on-site" does not simply refer to the ability to easily create AI or to have a user-friendly interface. There are many AI inspection products that focus on finding highly accurate AI through repeated parameter tuning, but we adopt the approach of injecting the know-how of inspectors into AI to create high-quality AI. Roxy AI will cultivate high-quality AI by improving the quality of training data. To enhance the quality of training data, we incorporate unique features such as proprietary visualization technology and tactile feedback. Roxy is an AI inspection product that is closely aligned with the on-site needs, contributing to the improvement of productivity in the manufacturing industry.
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