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RYOEI offers bespoke imaging methods to suit your unique inspection needs.
Features
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Uses AI to automatically sort tolerable and intolerable defects on machined surfaces
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Classifies defects into categories, such as shrinkage defects, chips, and machining traces
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Identifies defects as small as 0.02” (0.5 mm) under ideal conditions*
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Uses 3-way lighting for enhanced accuracy and detail
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Reduce the number of people required in your inspection process**
* Environmental factors such as poor lighting or mist, and variation in part size, finish, and color may affect accuracy and shooting time.
** We recommend continued human supervision to facilitate AI learning and ensure minimal error rate.
Imaging Methods
General Imaging Method
Imaging with 3-way Lighting
Imaging with Indirect Lighting
Camera
Defect
Camera
Defect
Camera
Defect
Surface for Refractory Light
* We propose various imaging methods depending on the type of defect. We also have experience in imaging methods other than the above three examples. Please contact us to learn more.
Powered by Deep Learning
Defect
Porosity
Scratch
No Defects
Milling Marks
Coolant Droplets
Easy to over-detect by mistake for defect
Coolant, chips, processing marks, etc.
Deep learning allows our AI Surface Inspection System to accurately distinguish the difference between defects, such as surface porosity and scratches, on non-defects, such as milling marks and coolant droplets.
Our surface inspection system utilizes 3-way lighting to accurately distinguish types of defects. Red, blue, and green lights shine onto the machined surface from different angles to create detailed images
Normal Image
Defects, stains, and milling marks are the same color, and there are few features.
Image With 3-way Lighting
Defects Easily Identified:
Defects → red and green
Dirt → orange
Milling marks → Purple