Augmented Reality–Based Visual Quality Inspection
Twyn is an augmented reality platform designed to support visual quality inspection using digital twins. It enables real-time, on-site verification of parts with minimal setup, helping manufacturers streamline inspection processes through a fully digital workflow.
Video source: Visometry – VisionLib & Twyn / Huisman
#inspection#AR
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Visual Quality Inspection with Augmented Reality & Digital Twins
Twyn enables visual quality inspections through an augmented reality platform, streamlining the process with a digital workflow and reduced setup times. This software allows manufacturers to verify quality in real-time, directly on-site, and wherever parts are located.
Video source: Visometry – VisionLib & Twyn / Huisman
#inspection#AR
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Visual Quality Inspection – Through Augmented Reality & Digital Twins
Perform visual quality inspections with Twyn – quickly, easily, and efficiently, assisted by a digital workflow, with reduced setup times.
Video source: Visometry – VisionLib & Twyn / Huisman
#inspection#AR
The new VisionPro is here. Visometry – VisionLib & Twyn have been waiting for this Apple announcement and release!
Video source: Visometry – VisionLib & Twyn
The new VisionPro is here. Visometry – VisionLib & Twyn have been waiting for this Apple announcement and release!
Video source: Visometry – VisionLib & Twyn
Das VDC-Netzwerk hat sich vergrößert! Wir möchten die vier neuen Mitglieder „Kompetek Interaktiv GmbH“, „@Mapstar_“, „@rooom_com“ und „Visometry GmbH (@visionlib)“ herzlich willkommen heißen. Wir freuen uns auf die gemeinsame Zusammenarbeit!
Visometry showed how continuous camera-based alignment&existence checks can benefit AR-powered quality assurance. Even trained eyes won't miss deviations when they are automatically found and marked with the help of the camera
Video source: @visionlib
Visometry showed how continuous #camera-based alignment & existence checks can benefit #AR-powered #qualityassurance. So even trained eyes won't miss deviations when they are automatically found and marked with the help of the camera.
Video source: @visionlib#computervision