Fischertechnik Quality Control with AI 9V

Product Description:

The Quality Control with AI 9V training model by fischertechnik provides a hands-on approach to understanding the growing role of artificial intelligence in quality control processes. This model is designed to visualize and simulate AI-driven quality assurance, bridging the gap between theory and practical application.

AI in Quality Assurance:
AI-based quality control, as demonstrated in industries like automotive manufacturing, offers significant advantages, including faster processes, reduced fault rates, cost minimization, and standardized fault evaluation. This model replicates such processes, using a sorting line that evaluates workpieces of three colors (white, red, blue) with various features (bore, gouges, bore + gouges) and defect patterns (e.g., out-of-round bores, missing features, or cracks).

How It Works:

• A camera scans each workpiece and classifies it using trained AI.
• AI-based classification is implemented using TensorFlow, where a neural network trained with image data analyzes each workpiece.
• Depending on the workpiece's color, features, and defect patterns, it is sorted into one of four bays based on quality.
• The AI model runs on the fischertechnik TXT 4.0 Controller, while the sorting sequence is programmed using ROBO Pro Coding and Python.

Generate Custom AI Applications:
For advanced users, the model offers the capability to create custom AI applications. Training for custom AI is performed in Python, with an example project provided for guidance.

Why Choose Quality Control with AI 9V?
This model offers a practical and engaging way to explore the principles of AI, machine learning, and quality assurance in industrial settings. Its hands-on design, customizable AI functionality, and robust construction make it an invaluable tool for education, research, and industry training in modern technology applications.