Manufacturing
Manufacturing machine vision links inspection, verification, counting and robotic handling. From wiring and laptop builds to welds, gaskets and machined parts, it catches defects and missing items, updates inventory and guides 3D bin picking for CNC and assembly operations.
Welding Bead Defect Detection Using AR + AI
AI models can be trained and uploaded into the system for qualified welding points. This enables AI inspection of welded sections using AR glasses or a tablet device to quickly recognize defective welds.
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Laser Marking Using Vision Guided Robotics + AI
SolMotion offers precise and continuous laser marking with AI-based 3D scanning technology, enabling real-time part positioning for robots to identify and mark objects accurately.
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Metal Grinding Using Vision Guided Robotics + AI
Automating precise grinding with SolMotion's 3D matching tech. Enhance quality, reduce waste, and boost productivity in metal component manufacturing.
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Packaging Seal Inspection Using AI
Based on deep learning technology, SolVision can determine whether a seal is intact by comparing a perfect packaging with potential variations.
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Product Label Inspection Using AI
Using OCR with AI deep learning, SolVision reads and detects various text and number defects on printed labels, enhancing electronics product label inspection.
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Inspecting Safety Certification Marks
Inspecting Safety Certification Marks. Solomon SolVision's AI automated detection of defective certification marks.
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AI Inspection of Power Supply Unit Cables
AI model can accurately identify errors in cable connections and eliminate substandard products in real time.
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AI Inspection of Stamped Metal Parts
There are many types of defects that may appear differently each time on the stamped parts, in particular oil or water stains, which are not easily detected.
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Visual Inspection of Stainless Steel Tubes
SolVision’s superior recognition capabilities ensures that OCR of bicycles can be accurately carried out regardless of how the identification numbers look or light refraction levels.
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