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Home > News > Extrusion

AutoROCK digitizes extrusion: AI for error detection

Source：Adsale Plastics Network Date ：2026-03-17 Editor ：RC
Copyright： This article was originally written/edited by Adsale Plastics Network (AdsaleCPRJ.com), republishing and excerpting are not allowed without permission. For any copyright infringement, we will pursue legal liability in accordance with the law.

The SKZ Plastics Center and the Fraunhofer Institute for Integrated Circuits IIS are driving forward the digitization and automation of extrusion in their joint research project AutoROCK.

 

The aim of the project is to enable the automated, reliable detection of defects in plastic profiles directly during production. AutoROCK thus addresses a key challenge in plastics processing: identifying quality deviations at an early stage before they lead to rejects, material loss, or costly rework.


SKZ_AutoROCK project_X-ray CT measurement system.jpg

CAD model of the pure online X-ray CT measurement system without cladding and X-ray protection device. (Source: Fraunhofer IIS)

 

Creating reliable database

 

In order to create a reliable database for the development of an AI-supported monitoring system, extrudates with characteristic defects have been specifically produced in the project to date.

 

In addition, manufacturing companies have provided rejected products with typical defects. The defects present, including cavities, foreign material inclusions, pores, and geometric errors, make it possible to map reproducible and realistic scenarios.

 

The samples were then examined using state-of-the-art X-ray CT systems and established non-destructive testing (NDT) methods. The resulting data set now forms the basis for training an AI system that will be able to automatically detect, classify, and evaluate defects in terms of their relevance. Thanks to the diversity of the data collected, the AI learns to identify even complex or overlapping defect structures.

 

Specially adapted demonstrator for online measurements

 

At the same time, the project developed a concept for a specially adapted demonstrator that will enable online measurements during extrusion in the future. The requirements for such a system are high: it must guarantee robust measurements despite continuous material movement, high throughput speeds, and limited installation space, as well as ensuring radiation protection.

 

In addition, the technology must be designed in such a way that it can be seamlessly integrated into existing production lines without impairing the process flow. The developed concept takes these challenges into account and creates a basis for a new generation of inline-capable CT systems. Practical tests will take place in the course of the year.

 

AI x CT technology: Real-time monitoring in the future

 

The combination of AI and adapted CT technology opens up new possibilities for the plastics industry. Real-time monitoring will enable quality deviations to be detected immediately and process parameters to be adjusted dynamically in the future.

 

This is expected to result in a significant reduction in scrap, greater process stability, and improved resource efficiency. At the same time, continuous data collection enables comprehensive documentation of product quality.


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Source：Adsale Plastics Network Date ：2026-03-17 Editor ：RC
Copyright： This article was originally written/edited by Adsale Plastics Network (AdsaleCPRJ.com), republishing and excerpting are not allowed without permission. For any copyright infringement, we will pursue legal liability in accordance with the law.

The SKZ Plastics Center and the Fraunhofer Institute for Integrated Circuits IIS are driving forward the digitization and automation of extrusion in their joint research project AutoROCK.

 

The aim of the project is to enable the automated, reliable detection of defects in plastic profiles directly during production. AutoROCK thus addresses a key challenge in plastics processing: identifying quality deviations at an early stage before they lead to rejects, material loss, or costly rework.


SKZ_AutoROCK project_X-ray CT measurement system.jpg

CAD model of the pure online X-ray CT measurement system without cladding and X-ray protection device. (Source: Fraunhofer IIS)

 

Creating reliable database

 

In order to create a reliable database for the development of an AI-supported monitoring system, extrudates with characteristic defects have been specifically produced in the project to date.

 

In addition, manufacturing companies have provided rejected products with typical defects. The defects present, including cavities, foreign material inclusions, pores, and geometric errors, make it possible to map reproducible and realistic scenarios.

 

The samples were then examined using state-of-the-art X-ray CT systems and established non-destructive testing (NDT) methods. The resulting data set now forms the basis for training an AI system that will be able to automatically detect, classify, and evaluate defects in terms of their relevance. Thanks to the diversity of the data collected, the AI learns to identify even complex or overlapping defect structures.

 

Specially adapted demonstrator for online measurements

 

At the same time, the project developed a concept for a specially adapted demonstrator that will enable online measurements during extrusion in the future. The requirements for such a system are high: it must guarantee robust measurements despite continuous material movement, high throughput speeds, and limited installation space, as well as ensuring radiation protection.

 

In addition, the technology must be designed in such a way that it can be seamlessly integrated into existing production lines without impairing the process flow. The developed concept takes these challenges into account and creates a basis for a new generation of inline-capable CT systems. Practical tests will take place in the course of the year.

 

AI x CT technology: Real-time monitoring in the future

 

The combination of AI and adapted CT technology opens up new possibilities for the plastics industry. Real-time monitoring will enable quality deviations to be detected immediately and process parameters to be adjusted dynamically in the future.

 

This is expected to result in a significant reduction in scrap, greater process stability, and improved resource efficiency. At the same time, continuous data collection enables comprehensive documentation of product quality.


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AutoROCK digitizes extrusion: AI for error detection

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