This is an example of replacing visual inspection, which relied on skilled operators, with a scanner-based line camera and AI image analysis.
We would like to introduce a case study of the "FA Finder" adopted by the Osaka Tanimachi Ready-Made Clothing Cooperative (Osaka Sponger), which undertakes the inspection (fabric inspection) of products for weaving irregularities, defects, and dirt from fabric manufacturers. Traditionally, fabric inspection relied on the visual assessment of skilled workers, but this has been replaced by a scanner-based line camera and AI image analysis. Furthermore, the registration of inspection results into the core system, which was previously done manually, has been automated using the "FA Finder." 【Case Overview】 ■Challenges - Although inspection standards exist, the criteria for judgment vary by individual. - Marking of abnormal (defect/dirt) areas is done by individuals. ■Benefits - Liberation from the harsh task of long hours of visual inspection and resolution of the shortage of skilled workers. - The number of inspections per day has increased approximately threefold. *For more details, please download the PDF or feel free to contact us.
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Zuken Elmic is expanding its contract development based on its knowledge and achievements in communication protocols and low-latency video streaming. In the manufacturing sector, it is focusing on: - The platform 'FA Finder', which integrates video, AI, FA equipment, and visualization systems for FA to build systems for detecting product defects and equipment malfunctions, as well as traceability systems. - Industrial network implementation support services.
