Industrial Vision System

Intelligent defect detection through machine learning

A central element of the solution is the self-learning defect analysis. The system uses machine learning algorithms to recognize typical defect patterns such as foreign particles or material defects. The system is continuously trained with new examples, so detection accuracy improves steadily during operation.

Defects that have already been detected are documented and made available for quality assurance (QA). This creates a transparent data basis for analyses, optimizations and possible complaints toward suppliers.

User-friendly operation

Operation takes place via a web-based user interface ("Operator View"), which is flexibly accessible across the machine network.

There, employees have access to:

• Live images from the process
• Overview of all detected defects
• Access to stored defect images
• Control options for the system

This ensures control is maintained at all times – without disrupting the production flow.

Hardware & Integration

For reliable inspection, a specifically tailored hardware solution was implemented:

• High-resolution line scan cameras for continuous image capture
• Powerful image processing computers for real-time analysis
• Dedicated lighting systems (light bars) for optimal defect detection
• Direct connection to the PLC for synchronization with the production process

The system is seamlessly integrated into the existing machine environment and works fully automated in the background.

Value for the customer

Using the vision system delivers clear benefits:

• Significantly reduced product failures through early defect detection
• Automated quality control without additional staffing effort
• Transparent defect documentation for quality assurance and complaints
• Relief for employees, who can focus on value-adding activities
• Continuous improvement through self-learning algorithms