With the proposal of the "dual carbon" goal and the continuous expansion of application fields such as new energy vehicles and energy storage, power batteries, as the upstream industry and core components of new energy vehicles, are benefiting from the release of policy dividends in the production and sales of new energy vehicles and are experiencing rapid development.
In order to meet the rapidly growing market demand, battery production enterprises continuously break through in manufacturing processes and technologies, seize the market by manufacturing more efficient products, and continuously open new production lines and factories to meet the demand for production capacity.
In the era of large-scale manufacturing of lithium-ion batteries, ensuring that quality inspection can catch up with production and ensuring the production quality of products is a prerequisite for the good development of power batteries. As a result, machine vision inspection has been widely used in multiple stages of power battery production due to its advantages such as efficiency and intelligence, providing protection for battery quality control.
Long production process for power batteries:
Industrial complexity and rapid iterative development
The production of lithium batteries is a complex system with a long production process, involving more than 50 processes, including: positive electrode, negative electrode, separator, electrolyte, current collector and binder, conductive agent, etc. The reactions involved include electrochemical reactions between positive and negative electrodes, lithium ion conduction and electron conduction, as well as heat diffusion.
With the accumulation of technical experience and the increasing demand from downstream major customers, lithium battery production is shifting from manufacturing to intelligent manufacturing, posing new requirements for the interactive correction ability, accuracy, speed, and stability consistency of equipment. The pursuit of energy conservation and emission reduction in the production process, as well as the ultimate pursuit of production efficiency, are also simultaneously reshaping the entire industry.
The power battery industry is experiencing rapid growth,
Visual inspection standardization ability becomes the key to breaking through
The defects such as bubbles, black spots, and scratches generated during the production process of lithium batteries, as well as the misalignment of pole ears, can affect battery quality and even cause explosions. This requires real-time visual inspection of the lithium battery production process to ensure consistency and stability of the production line.
Starting from the CATL era, battery manufacturers have increasingly attached importance to machine vision inspection, while also requiring visual inspection solution suppliers to have a deep industry accumulation and technical accumulation in the entire process of power batteries. They can have a deep understanding of inspection problems, achieve rapid response to customer needs, and implement deep level solutions.
In machine vision inspection projects, battery manufacturers have two main demands:
(1) Let quality inspection catch up with production and shorten the time for the landing of new lithium battery production capacity;
(2) Visual inspection should be able to deal with various complex defects, and the detection yield should be close to 100%.
To address the pain points in the lithium battery industry and bring more value to customers, how to shorten the preparation time of production lines and achieve the rapid landing of new power battery production lines; How to improve the yield of testing and meet the efficiency goals of enterprises has become an important topic for Huahan Weiye to consider.
Qin Si Precision‘s self-developed testing plan,
Realizing full process visual inspection coverage for lithium batteries
Faced with the testing needs of various new production lines in the lithium battery industry, Huahan Weiye relies on its self-developed deep learning algorithm to quickly understand and evaluate defects in multiple core sections of power batteries based on process information. Combined with the industry Know How formed by the landing and application of lithium battery industry projects, the full process testing needs of the lithium battery industry are precipitated into a normalized visual inspection solution.
Faced with the testing needs of various new production lines in the lithium battery industry, Huahan Weiye relies on its self-developed deep learning algorithm to quickly understand and evaluate defects in multiple core sections of power batteries based on process information. Combined with the industry Know How formed by the landing and application of lithium battery industry projects, the full process testing needs of the lithium battery industry are precipitated into a normalized visual inspection solution.