The “defect inspection system for golf balls,” provides customers with a complete set of AI-AOI system and equipment for detecting the surface defects of golf balls. The defect inspection system uses computer vision with deep learning. It is a high-speed and high-precision AOI system with automated feeding and unloading. The defect inspection system has solved the problem of manual visual inspection. It can also record the defect status and report back in real time.
It can help achieve a daily production capacity of more than 100,000 pieces, with the production yield rate of up to 98.5%.
(2) Steel coil serial number OCR
Integrating into the steel coil production process, this system assists the introduction of AI-OCR technology to achieve a recognition rate of 98.7% or above, effectively preventing the delivery of the wrong products.
(3) Factory safety image recognition
Using deep learning image recognition technology, this system employs AGV (Automatic Guided Vehicle) and cameras to conduct factory safety inspection, covering personal protection equipment, on-site environmental safety measures, etc. It can promote operation environment safety and reduce working hours of manual inspection.
(4) Defect inspection system for shoelace surface
AI visual recognition is introduced to help detect surface defects of shoelaces.
(5) Stenter automation software in the textile industry
The Internet-of-Things (IoT) is used to achieve the automation of setting machines. We help customers upgrade their machines to realize fully-automated production, including automated monitoring of production data. This raises the productivity of workers and production.