Detection of abnormalities that color sorters could not identify, such as food crop decay, insect damage, pinholes, chips, scratches, and shape defects, is also possible!
Our "Appearance Inspection Solution TESRAY G Series" conducts inspections using AI during the brief moment when the inspection target falls through the air, allowing for the expulsion and sorting of defective items before they land. By enabling AI to learn the concept of the inspection target, we can detect abnormalities that traditional rule-based technologies could not identify. 【Examples of detectable abnormalities】 Cut vegetables: - Decay (items with colors similar to normal parts) - Insect damage - Shape defects, etc. Nuts abnormalities: - Shape abnormalities due to underdevelopment - Very small pinholes caused by insect damage - Insect residue (remnants or secretions from insect damage) Dried fruits and other dried items abnormalities: - Surface mold - Foreign matter contamination from similar plants, etc. - Localized deformation due to insect or mold effects 【Ability to aggregate detected defects】 - Detected abnormalities can be aggregated by type of defect. This allows for feedback of information to the supplier. 【Ability to adjust yield rates】 - Abnormalities can be categorized by level, allowing for decisions on whether to expel items based on level, thus enabling yield rate adjustments.
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basic information
The inspection is conducted by AI during the brief moment the target falls through the air, allowing for the expulsion and sorting of defective items before landing. The system can handle not only color defects but also distortions in shape, as well as foreign objects such as stones, soil, plants, and insects that are similar in color to the target. By utilizing AI technology, it is possible to distinguish not only the presence of abnormalities but also their types, enabling flexible adjustments such as shipping defective items as normal products for processing purposes. Furthermore, it allows for the establishment of expulsion criteria based on the degree of abnormalities, accommodating sensory evaluations that were previously only achievable by humans, thus optimizing yield.
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【Examples of Detectable Abnormalities】 Cut Vegetables - Decay (similar color to normal parts) - Insect damage - Shape defects, etc. Nuts Abnormalities - Shape abnormalities due to poor development - Very small pinholes caused by insect damage - Insect residue (effects of food remnants or secretions from insect damage) Dried Fruits and Other Dried Products Abnormalities - Surface mold - Contamination with similar foreign plants, etc. - Localized deformation due to the effects of insects or mold
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We combine advanced hardware that thoroughly understands the field with cutting-edge software to solve the challenges faced by businesses and society using the power of AI and robotics. "The fusion of hardware and software." There are still very few companies in the world that truly realize this ideal and create genuine synergies. We have both the necessary personnel and facilities in-house, and we constantly engage in discussions, exchanges, and knowledge sharing across specialties and job types. We will shape unprecedented solutions in a one-stop manner.
![[For Quality Managers] Understanding the Basis for Judgment. Appearance Inspection AI that can learn from small amounts of data.](https://image.mono.ipros.com/public/product/image/a91/2000993773/IPROS502970889695055929.jpg?w=280&h=280)
