Find the breakthrough point: AI “into the factory” to achieve double liters of quantity and quality

S72402-NANANA-NA-225 With the vigorous development of technology such as machine vision and the Internet of Things, the manufacturing enterprises at the forefront of The Times are building smart factories based on the existing IT architecture and combining cutting-edge technology through expansion solutions.

At the Fifth Global Intelligent Industry Conference 2021, Professor Jia Jia, tenured professor of the Chinese University of Hong Kong, member of the International Association of Electrical and Electronics Engineers, and chairman/founder of Simo Technology, said that the core of intelligent manufacturing lies in “intelligence” : Intelligence is not simple automation, intelligence is to make the manufacturing has a “brain” and a variety of nervous systems that let the brain make decisions, S72402-NANANA-NA-225 only with a smart “brain” can maximize the role of automation “arms” – and AI is the core factor that makes the manufacturing of industrial machines and equipment that can think.

Intelligent sorting, intelligent fault prediction, AI surface defect detection and even intelligent quality control, timing prediction… These applications highlight the key role played by AI in different stages and fields of manufacturing, so it has become the most typical case of intelligent manufacturing in recent years.

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In the case of the aforementioned enterprise, Ningde Times, its demand for capacity and quality improvement based on the continuous growth of global market demand has prompted the demand for AI power battery defect detection solutions. Such a solution should not only meet the requirements of the headquarters layer by layer control, but also need to have a more efficient real-time defect detection capability, that is, to achieve more than 400FPS in a single process and achieve the goal of zero leakage detection in image processing speed.

Defect detection is a highly detailed and time-consuming project. The traditional artificial defect detection method is not only slow and poor accuracy, but the traditional digital image processing technology has poor generalization ability, which requires parameter adaptation according to each machine and is disconnected from the division of labor and headquarters, lack of overall deployment control ability, and processing capacity cannot match the continuous growth of market demand.

“When Ningde era and Intel communicate S72402-NANANA-NA-225 such confusion, they clearly put forward two needs, one is to capture the pictures of different production lines, with real-time image data analysis to achieve product defect detection during battery production, and the other is to help Intel to establish a unified AI platform, which can make defect detection more real-time and accurate.” Said Wu Zhijing, account manager of Intel’s industry solutions business group in China.

Before this, Ningde era has deployed multiple cameras on each battery production S72402-NANANA-NA-225 line in the battery product manufacturing factory, which can produce hundreds of pictures per second, and a factory has at least a dozen production lines, so a factory has thousands or even tens of thousands of pictures every second. Therefore, Ningde Times urgently needs to introduce a set of technical solutions to analyze and process the above-mentioned massive pictures in real time to determine whether there are product defects in the production process, so as to solve the industry problems in quality control.