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It is possible to conduct appearance inspections of all sheet-like products manufactured by the "roll-to-roll" production method. It detects only the abnormal areas without over-detecting normal areas that closely resemble abnormal ones, such as fiber twists that do not have issues with product quality or appearance. 【Features】 - Supports all industrial products and food produced by methods such as "roll-to-roll" and "sheet" (e.g., film products, woven fabrics, non-woven fabrics, thin steel plates, food such as noodles, etc.). - Capable of suppressing the over-detection of normal areas, which was not achievable with rule-based defect detectors. - In the production line, it can replace existing inspection devices or collaborate with upstream and downstream equipment without changing the specifications or production speed of the production equipment. - When an anomaly is detected, images of the abnormal areas are displayed in real-time on the monitor. The coordinates of the product can also be displayed, enabling the construction of evidence for defective products. - It can identify the types of detected anomalies and aggregate the number of detections. - Utilization of big data for quality improvement using aggregated data is possible. - Even if the types of anomalies increase after implementation or new products become subject to inspection, additional AI learning is possible, and it can also be expanded to other factories.
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Free membership registrationOur "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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Free membership registration[CUTR Overview] - Utilizing a patented cutting mechanism and AI that flexibly determines cutting methods, we perform high-speed cutting processes with excellent yield. We develop dedicated hardware for cutting processes tailored to the required processing capacity and weather resistance in manufacturing environments. The AI estimates the position and posture of irregular objects to decide on cutting methods, achieving yields equal to or greater than those of human operators. - By proposing solutions that include handling and disposal of removed parts, we realize the automation of the cutting process. Adjustments can be made based on weight for cutting divisions and removal rates for inedible parts, allowing for flexible changes to cutting methods in line with daily operations. Our system can also integrate with existing equipment and robotic arms, tailored to inspection targets, takt times, and upstream and downstream processes.
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Free membership registration**For the Inspection of Industrial Products with Three-Dimensional Shapes** Equipped with specially designed robots, cameras, and lighting specifically for the visual inspection of three-dimensional shaped products, it achieves a level of high-speed inspection that cannot be accomplished with general vertical multi-joint robots. **Features** - Automation of visual inspection is possible for various industrial products made from materials such as resin, metal, and fiber, and using manufacturing methods such as injection molding, pressing, plating, and painting. - The inspection robot with 6 axes (up to 12 axes) can accommodate three-dimensional shaped workpieces, including parts with height/thickness and recesses/R shapes. - Implements AI algorithms that meet the inspection quality standards of automotive parts manufacturers. - The unique robot teaching function developed in-house makes it easy to handle production items with a wide variety of small lots. - Supports customized development for smooth integration with existing production equipment in the factory and seamless connection with upstream and downstream processes.
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Free membership registration【Removal of foreign substances and sorting of defective products in large-scale inspections of small food items, etc.】 AI inspection is conducted in the brief moment that the inspection target falls through the air, allowing for the expulsion and sorting of defective items before they land. 【Features】 - Optimized for small inspection targets ranging from fingertip to palm size (e.g., cut vegetables, nuts, spices, medicinal herbs, dried goods, fish roe, etc.) - Capable of addressing color variations that are difficult to manage with conventional technology, including shape defects, foreign substances, and insect damage. - Allows for the establishment of sorting criteria based on the classification of abnormalities and their severity (e.g., shipping items with minor deformations while not shipping those with significant deformations), enabling optimization of yield according to customer requirements. - All core technologies are developed in-house, allowing for adjustments and customizations of the device's performance based on the necessary processing capacity.
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