AI-assisted visual inspection
For efficient quality of products & process monitoring.
AI-assisted visual inspection cameras can detect defects with around 90% greater accuracy than humans. Machines like that can obviously do so within a fraction of a second and never get bored.
Tangible benefits and ROI thru:
- automate manufacturing jobs once reserved for humans
- continuously monitor quality and count objects
- eliminate or minimize human error
- avoid disasters and unnecessary latencies
Bottom line: byteLAKE’s Cognitive Services help effectively bring out the best of both worlds: humans and machines.
Key features
- Models can be trained to detect and count objects and shapes
(defects, issues, or goods in production lines or while monitoring conveyor belts) - Measure distance and trigger position based alarms
(inspect goods or events in production processes, count them and measure how far they are from critical areas) - Part of byteLAKE’s Cognitive Services
(straightforward integration) - Models improving over time
(assisted learning as an option)
byteLAKE’s AI models for visual inspection will be available in many different versions, tailored and optimized to various industries and their specific scenarios. We will be describing these in more detail on byteLAKE’s blog under our Industry 4.0 dedicated section. Scenarios we are currently working on include:
- Food recognition for efficient self-service and automated billing in restaurants and hotels
- Intelligent cameras for paper mills, detecting issues thru visual analytics of paper production processes (i.e. wet line monitoring)
- Counting goods on conveyor belts, identifying them, and monitoring quality and finding defects
- 3D data analytics for robot arms optimal movements
Example trained AI model: AI for Paper Industry (Wet Line / Dry Line detector).