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Quality control of electric vehicle battery production requires deep learning solutions
Batteries, continuous quality checks throughout the production process
Deep learning-based sensor and network solutions needed
Electric vehicle batteries must have a high capacity per volume to achieve maximum efficiency in a limited space. In addition, they must withstand the shocks transmitted during driving and have stability and durability to withstand low and high temperatures.

On the 10th, Cognex proposed a deep learning-based machine vision solution that can be applied to manufacturing process automation to ensure the quality and extend the life of electric vehicle batteries.
Since even one faulty battery cell can have a negative impact on the performance of the entire battery pack, a lack of quality control can lead to the production of many defective products. Quality is an area that must be continuously checked throughout the entire battery production process. Manufacturers must use efficient automated solutions that can perform economical inspections while maintaining high quality.
Cognex's sensor, identification, and network solutions based on deep learning solutions enable the production of high-quality batteries. By introducing this solution, you can determine whether a product is defective in a short period of time, and you can also determine whether the final shipment is defective through process monitoring and full inspection.
The machine vision deep learning solutions for automating the electric vehicle battery manufacturing process announced by Cognex Korea include ▲In-Sight ViDi classification and defect detection tool for 'cap weld inspection' and 'battery cell injection seal weld inspection', ▲In-Sight D900 smart camera for 'cell surface inspection', ▲VisionPro ViDi image analysis software for 'pouch surface inspection', and ▲In-Sight ViDi defect detection and segmentation tool for 'side and top panel weld inspection'.




“Cognex provides integrated deep learning-based solutions for quality assurance across the entire process from the first process of electric vehicle battery cell production to final product shipment,” said Moon Eung-jin, CEO of Cognex Korea.
Deep learning-based sensor and network solutions needed
Electric vehicle batteries must have a high capacity per volume to achieve maximum efficiency in a limited space. In addition, they must withstand the shocks transmitted during driving and have stability and durability to withstand low and high temperatures.

▲ Cognex Insight D900 smart camera [Photo = Cognex]
On the 10th, Cognex proposed a deep learning-based machine vision solution that can be applied to manufacturing process automation to ensure the quality and extend the life of electric vehicle batteries.
Since even one faulty battery cell can have a negative impact on the performance of the entire battery pack, a lack of quality control can lead to the production of many defective products. Quality is an area that must be continuously checked throughout the entire battery production process. Manufacturers must use efficient automated solutions that can perform economical inspections while maintaining high quality.
Cognex's sensor, identification, and network solutions based on deep learning solutions enable the production of high-quality batteries. By introducing this solution, you can determine whether a product is defective in a short period of time, and you can also determine whether the final shipment is defective through process monitoring and full inspection.
The machine vision deep learning solutions for automating the electric vehicle battery manufacturing process announced by Cognex Korea include ▲In-Sight ViDi classification and defect detection tool for 'cap weld inspection' and 'battery cell injection seal weld inspection', ▲In-Sight D900 smart camera for 'cell surface inspection', ▲VisionPro ViDi image analysis software for 'pouch surface inspection', and ▲In-Sight ViDi defect detection and segmentation tool for 'side and top panel weld inspection'.

▲ Example of cap welding inspection during battery assembly [Image = Cognex]

▲ Example of injection seal inspection during battery assembly [Image = Cognex]
: 347px;" /> ▲ Example of cell surface inspection during battery assembly [Image = Cognex]

▲ Example of pouch surface inspection during battery assembly [Image = Cognex]

▲ Welding the side and top panels when assembling the battery
Inspection Example [Image = Cognex]
Inspection Example [Image = Cognex]
“Cognex provides integrated deep learning-based solutions for quality assurance across the entire process from the first process of electric vehicle battery cell production to final product shipment,” said Moon Eung-jin, CEO of Cognex Korea.
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