GETECH's Automatic Defect Recognition and Classification System Selected for Guangdong Industrial Internet Application Benchmark List
On November 15, the Guangdong Industrial Internet Industry Alliance released the second batch of the 2018 Guangdong Industrial Internet Application Benchmark List. The automatic defect recognition and classification system, developed by GETECH based on machine vision and artificial intelligence, was included.
To implement the "Guangdong Provincial People's Government's Notice on Deepening the 'Internet + Advanced Manufacturing' Development of Industrial Internet Implementation Plan and Supporting Policy Measures," promote industrial internet application innovation, cultivate and establish industry benchmark cases, and drive the digital, networked, intelligent, and service-oriented transformation and upgrading of Guangdong's manufacturing industry through data-driven approaches, the Guangdong Industrial Internet Industry Alliance, in accordance with the "Guangdong Industrial Internet Application Benchmark Cultivation Work Plan," organized the second batch of 2018 Guangdong Industrial Internet Application Benchmark cultivation and matching work. From November 5 to 8, 2018, the alliance organized the Guangdong Industrial Internet Expert Committee to conduct on-site demonstrations and benchmark evaluations. Based on the expert evaluation results, the second batch of the 2018 Guangdong Industrial Internet Application Benchmark List was finalized.
The Guangdong Industrial Internet Expert Committee believes that the automatic defect recognition and classification system developed by GETECH, based on machine vision and artificial intelligence, is a typical application of AI image recognition that has been effectively implemented in combination with enterprise processes. Using machine vision for semi-finished products and quality images, artificial intelligence enables defect recognition and classification, addressing previous issues such as low efficiency in defect image judgment by factory personnel, excessive human interference, and high costs. This significantly reduces factory labor input, improves the accuracy of defect judgment and classification, and advances anomaly interception by 1-2 hours. Experts stated that this system has broad demand and application scenarios in appearance inspection and defect detection in fields such as LED lighting, ceramics, 3C electronics, and steel, making it worthy of widespread promotion.
