Five machines linked together to form a production line, where mobile phone components like chips and batteries pass through in just 4 seconds. During this brief period, over 20 cameras perform comprehensive inspections of their dimensions and precision, with a detection error rate within 2 microns. Recently, with the deployment of the industry's first batch of fully automatic dimensional and appearance inspection equipment developed independently, Suzhou Dinnar Automation Technology Co., Ltd., located in Suzhou Industrial Park, has achieved domestic substitution in the field of industrial vision inspection. "Our equipment not only 'Fire Eye Golden Gaze' can detect micron-level differences in components, but it can also assemble them precisely, minimizing errors," said Qin Yinghua, founder and chairman of Dinnar Automation Technology.

Established in 2010, Dinnar Automation is a leading local enterprise in the park, dedicated to empowering traditional manufacturing with advanced technologies like 3D vision, artificial intelligence, and robotic control. Currently, its products are widely used in industries such as consumer electronics, automotive manufacturing, photovoltaic semiconductors, and warehousing logistics. In recent years, Dinnar Automation has seized the opportunities of the Industrial Internet's development, focusing on ultra-high precision measurement technologies in 3D vision, deep learning for complex defect detection, object recognition, and intelligent robotic vision grabbing techniques, continuously deepening its research and production in intelligent manufacturing equipment. Its technologies and products have now won favor from leading global enterprises in the electronic information industry and others.

"The diameter of a single hair is about 70 microns. The error detected by our independently developed fully automatic dimensional and appearance inspection equipment is within 2 microns, which is only one thirty-fifth of a hair," Qin Yinghua stated. The equipment, equipped with

 3D vision technology and leveraging big data deep learning, is highly "intelligent." "Take the example of mobile phone cover glass and phone cases; in the past, when the precision of detection wasn't so high, it was common for users to have their hair caught by the phone during calls," explained Qin Yinghua. While qualified components will fall within the allowable margin of error, previous detection devices could only assess each component's compliance individually and could not match the two closest-sized parts. The new equipment effectively resolves this issue by finding the "soul mate" for each component, significantly reducing the rate of product defects.

Deeply rooted in the field of machine vision, Dinnar Automation invests 15% of its annual revenue into R&D. The company has branches in Shenzhen, Zhejiang, and Silicon Valley in the United States and is accelerating the establishment of its R&D headquarters in the park. Recently, the company completed a 100 million yuan Series B financing round jointly invested by Source Code Capital, Yuanhai Minghua, and Xiaomiao Capital. Moving forward, the company will continue to enhance the precision and speed of automated inspections, constantly upgrading its integrated software and hardware for fully automatic intelligent manufacturing equipment, accelerating the transformation of Suzhou's manufacturing industry towards "intelligent manufacturing." (Su Bao Rong Media reporter Dong Jie Text/Photos/Videos)