Wide range of AI visual inspection applications
Solvision has delivered outstanding results in the semiconductor, LCD display, footwear, textile, automotive, welding, and a wide range of other industries. Its flexibility has allowed it to be implemented in several applications such as defect inspection, presence detection, counting, classification, optical character recognition, and many more.
Few training samples for deep learning required
Solvision offers many easy-to-use data augmentation tools that allow users to simulate different real-life scenarios. Needing only 1/10 of the samples typically required by AI inspection software, our vision solution significantly reduces the amount of time that engineers have to spend during the labeling process.
User-friendly vision system interface
Our user-friendly design allows users to label several defect types at the same time, a very convenient feature in applications where multiple defects and features need to be simultaneously classified.
Simple industrial robot and PLC integration
Solvision provides easy integration with more than 20 robot brands and built-in PLC communications through the TCP/IP and Modbus communications protocol at no extra cost, allowing users and system integrators to choose the product that they feel most comfortable with.
Parallel defect detections
Solvision can select multiple GPUs and graphic cards to disperse the AI computing load, allowing the users to carry out simultaneous detections at the same time.
Solvision Applications
Presence/Absence Detection
Push-through-package (PTP) blister production lines on average pack 5,000-40,000 tablets or capsules per hour, and are prone to occasional errors in filling. These production errors can range from unfilled and deformed blisters to inadequate or broken tablets or capsules.
Defect Identification
Mildew and stains sometimes remain in the bottle even after the disinfection process. However, checking for defects involves rotating and moving the bottle, and there is usually a product label in the way that makes it unfavorable for manual or traditional vision systems.
Categorization
Based on deep learning technology, Solvision can locate and mark the position of eggshell defects on sample images to train an AI inspection system. The AI model can then detect pores and cracks on the eggshell surface and classify eggs into the trained categories to meet safety standards and increase commodity value.
Solvision Production Line Defect Inspection
Metal scratch defects
Chicken nugget defects
Contact lenses defects
Laser welding defects
Solvision Specifications
3D Scanner Field of View (FOV）
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