SKZ Plastics Center, TRILITEC and VendOs Industrietechnik launched a joint development project to develop radar-based measuring system, which precisely and efficiently monitors the quality of plastic sheets during extrusion process.

Schematic of the radar inspection system used in sheet extrusion.

The non-destructive, non-contact, 100% coverage and completely hazard-free method of operation enables real-time monitoring. It enables the earliest possible detection of externally visible or internal defects so that immediate adjustments can be made.

The measuring system can inspect a wide variety of materials, including plastic, gypsum, wood and glass. Recycled materials can also be inspected.

During the operation, a comprehensive analysis of plastic sheets is performed using radar waves. A combined transmission and reflection setup is used. This enables reliable detection of defects such as blowholes and foreign material inclusions. The use of narrow-band and modular microwave radar systems also allows high lateral solution.

Automatic defect detection is based on machine learning techniques, especially deep learning. These self-learning techniques are based on artificial neutral networks and are particularly suitable for precise pattern recognition in images.

Pierre Pfeffer, Senior Scientist in the field of non-destructive testing at SKZ, explained that by avoiding rejects in production, resources are used efficiently, which leads to a significant reduction in material waste. This approach also promotes sustainable and digital production.

SKZ Plastics Center, TRILITEC and VendOs Industrietechnik launched a joint development project to develop radar-based measuring system, which precisely and efficiently monitors the quality of plastic sheets during extrusion process.

Schematic of the radar inspection system used in sheet extrusion.

The non-destructive, non-contact, 100% coverage and completely hazard-free method of operation enables real-time monitoring. It enables the earliest possible detection of externally visible or internal defects so that immediate adjustments can be made.

The measuring system can inspect a wide variety of materials, including plastic, gypsum, wood and glass. Recycled materials can also be inspected.

During the operation, a comprehensive analysis of plastic sheets is performed using radar waves. A combined transmission and reflection setup is used. This enables reliable detection of defects such as blowholes and foreign material inclusions. The use of narrow-band and modular microwave radar systems also allows high lateral solution.

Automatic defect detection is based on machine learning techniques, especially deep learning. These self-learning techniques are based on artificial neutral networks and are particularly suitable for precise pattern recognition in images.

Pierre Pfeffer, Senior Scientist in the field of non-destructive testing at SKZ, explained that by avoiding rejects in production, resources are used efficiently, which leads to a significant reduction in material waste. This approach also promotes sustainable and digital production.