The AI.SEE™ Line Inspector is part of the AI.SEE™ suite. It is installed on the production line providing its own cameras or interfacing with existing cameras. It analyzes the camera images locally and controls the downstream process depending. This may include automatic ejection of defective products, displaying alerts, or sending messages to staff members in charge.
In combination with AI.SEE™ Core , the AI.SEE™ Line Inspector serves as a data hub that passes image data to the Core. AI.SEE™ Core enables you to track the production quality of manufactured products, including image data, across all lines.
AI.SEE™ Line Inspector Specifications
S | M | L | |
---|---|---|---|
Application | Cost-efficient testing of individual tasks | Flexible solution with higher performance | High-performance single test or several simultaneous tests |
Typ | Embedded Sensor | Embedded PC | BoxPC |
Performance evaluation per second | 1 | 2 | 10 **) |
Max. number of sensors | 1 | 2 | 4 *) |
Sensor connection types | none | 1x USB 3.0, 1x GigE mit PoE | 2x USB 3.0, 4x GigE |
Data storage | 6 GB | 128 GB | 700 GB |
Evaluation history depth (typ.) | 1.200 | 31.000 **) | 170.000 **) |
Expandable cloud storage | limited | full | full |
Data throughput | 100 Mbit/sec | 1 GBit/sec | 3 Gbit/sec |
Core required (for training) | ja | ja | nein |
OS | Linux | Linux | Windows/Linux |
Integration | Stand alone | PC im Schaltschrank, PC in control cabinet, camera in station | Standalone (IP65 control cabinet) or integrated |
*) Application-dependent
**) Typical evaluation range 4 MPixel
Can Artificial Intelligence Automate Your Optical Inspection?
When it comes to supporting companies in manufacturing, similar challenges and concerns frequently arise. To provide you with a proper evaluation of the feasibility and price, please fill out the questionnaire below.
Find out now with just a few questions whether your problem can also be solved by AI.SEE™.
AI.SEE™ Core
With AI.SEE™ Core, you collect and manage large volumes of quality assurance data and images. AI.SEE™ automatically trains the AI-assisted, self-learning, neural-network-based error-detection algorithm, further improving its accuracy with every new image.
Reference projects
References
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