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Quality Control with AI (Artificial Intelligence) 9V

Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V
Quality Control with AI (Artificial Intelligence) 9V

Quality Control with AI (Artificial Intelligence) 9V

The use of artificial intelligence in industry, education, and research is becoming increasingly important. To visualize this complex topic in a practical way, the "Quality Control with AI" model is ideally suited. By combining theory and practice, a sustainable learning experience is created. Particularly in quality control, AI offers numerous benefits, already utilized in industries such as automotive manufacturing. Processes can be streamlined, error rates and costs reduced, and error evaluation standardized.

The fischertechnik sorting system comes with workpieces in three different colors, marked with three processing characteristics and various defect patterns. The workpieces are scanned by a camera and classified using trained AI. Based on their color, characteristic, and defect pattern, the workpieces are then sorted according to their quality features by artificial intelligence. The AI is implemented using machine learning in TensorFlow, with a neural network trained on image data. The trained AI runs on the Fischertechnik TXT 4.0 controller. The system's power control is implemented in the ROBO Pro Coding programming environment and in Python.

Key Facts:
Sorting system for workpieces in 3 different colors (white, red, blue), with 3 different processing characteristics (drilled holes, milled recesses) and various defect patterns (non-circular drilled holes, missing holes, missing or partially missing milled recesses, cracks in the workpiece).

These processing and defect characteristics are simulated using corresponding adhesive labels on the workpieces.

The workpieces are scanned by a camera and classified using the trained AI. Based on their color, characteristic, and defect pattern, they are sorted into 4 different bays.

The AI is implemented using TensorFlow and runs on the TXT 4.0 controller. Custom AI models can also be created.

Essential Components / Highlights:
TXT 4.0 Controller
USB Camera
Encoder Motor
Compressor
4x 3/2-way solenoid valves
4x Pneumatic Cylinders
5x Phototransistors and 5x Photocell LEDs
4x LEDs for camera field illumination
24 Workpieces

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€1,694.00
Ex Tax: €1,400.00
  • Stock: about 5 days
  • Model: 568416
  • EAN: 4048962487213

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