>
>
>
[Smart China Expo] China's machine vision industry promotes industrial intelligence, and the industrial field welcomes a new era

ADD:No. 1 East No. 598 Fengting

           Avenue, Industrial Park

E-mail:info@dinnar.cn  

HOTLINE

 

0512-66957689

DINNAR

 

DINNAR


Page Copyright Suzhou DINNAR Automation Technology Co., Ltd. Copyright © 2018 All Rights Reserved.   苏ICP备13055261号-1 

NEWS

Company
Industry

[Smart China Expo] China's machine vision industry promotes industrial intelligence, and the industrial field welcomes a new era

2018/08/24 14:00

The China Machine Vision Industry Alliance participated in the 2018 China International Intelligent Industry Expo, and 36 machine vision-related companies came to showcase machine vision related products, including hardware components and application software and other machine vision products.

 

On the 24th, Pan Jin, chairman of the China Machine Vision Alliance, accepted the live news. The Chongqing Times reporter interviewed four: It is gratifying that in recent years, China's intelligent manufacturing standards have been continuously improved, and the manufacturing level of some industries has reached and exceeded the same international industry.

 

 

Machine lens detection, distance only 15mm

 

In the S4 exhibition area, Mo Yaomeng, a sales engineer from Guangdong Aotepu Technology Co., Ltd., told the live news-Chongqing Times reporter: "The working distance of the camera lens we made can be shortened to 15mm. It is still clear in such a short working distance. Shooting detects the internals of small parts. For example, this nut detection allows us to clearly detect the number of internal turns and external nicks on the small nut parts on the PCB."

 

The reporter learned that at present, this testing program has been used in some factories, adding a new step for the development of industrial intelligence.

 

In addition, the previous automobile production line used the naked eye of the worker to check the rubber coating of the vehicle body, and there may be small flaws that cannot be seen by the naked eye, but the visual inspection technology is widely used to detect and identify various types of components in the automobile production. This can be avoided.

 

 

Status: The machine vision industry started late and progressed fast

 

The China Machine Vision Industry Alliance was established in 2011 and has more than 200 member companies, 80% of which are domestic technology leaders and the rest are foreign machine vision companies.

 

Pan Jin, chairman of the China Machine Vision Alliance, accepted the live news. The Chongqing Times reporter said in an interview: Although the Machine Vision Alliance was founded less than ten years ago, most of them are young companies, but the product quality and visual technology of these companies are similar to international standards.

 

"Domestic machine vision technology started late, but the development process is very fast. The domestic visual industry is developing very rapidly. In just ten years, it has caught up with international standards." According to the statistics of the alliance: the machine vision industry in 2015 Creating more than 3 billion in output value, the trend of industrial intelligence has prompted the machine vision industry to create more than 6 billion in production value in 2017. In just two years, the output value has doubled.

 

In addition to improving manufacturing capabilities, you can also complete big data collection.

 

Machine vision technology is mainly used in the industrial field. It is applied in the detection, identification and measurement of industrial production lines, such as measuring the size of parts, positioning and grabbing some parts, detecting whether there are impurities, defective products, classification and classification in the products.

 

Chairman Pan told the truth news - Chongqing Times reporter: "The machine vision technology also has a function to collect analytical data, collect relevant data on the production line through visual software, make a detailed analysis of the aggregated big data, and understand the production line often through big data analysis. The problematic part of the problem, so that the company can better identify and solve the production difficulties."