Smart Rubber Extrusion Line Combining Multiple Sensor Techniques for AI-Based Process Control

authored by: Alexander Aschemann, Paul Felix Hagen, Simon Albers, Robin Rofallski, Sven Schwabe, Mohammed Dagher, Marco Lukas, Sebastian Leineweber, Benjamin Klie, Patrick Schneider, Hagen Bossemeyer, Lennart Hinz, Markus Kästner, Birger Reitz, Eduard Reithmeier, Thomas Luhmann, Hainer Wackerbarth, Ludger Overmeyer, Ulrich Giese
Abstract: The extrusion process is one of the most important methods for continuous processing of rubber compounds. An extruder is used to give the rubber compound a geometrically defined shape as an extrudate. To ensure that product-specific requirements are fulfilled, the extrusion process and the resulting extrudate are currently monitored using various sensor technologies. Nevertheless, a certain amount of scrap material is produced during the extrusion process, often as a result of unstable process conditions. In this context, one solution for enhancing resource efficiency is the digitalization of the production chain. The aim of this work is to demonstrate an approach for the digitalization of an extrusion line that combines the use of innovative measuring methods for process monitoring and algorithms from the field of artificial intelligence (AI) for process control. For the validation of the individual measuring systems and the process control, various production scenarios in the extrudate production are considered. The results show that the measurement systems for process and extrudate monitoring can directly detect changes in the extrusion process and extrudate quality. Furthermore, the generated data can be used to automatically adjust the extrusion process by the developed AI-based control system.
Organisation(s): Institute of Measurement and Control Engineering
Institute of Transport and Automation Technology
External Organisation(s): German Institute of Rubber Technology (DIK e.V.)
Jade University of Applied Sciences
Institute for Nanophotonics Göttingen e.V. (IFNANO)
Type: Article
Journal: Advanced engineering materials
ISSN: 1438-1656
Publication date: 25.10.2024
Publication status: E-pub ahead of print
Peer reviewed: Yes
ASJC Scopus subject areas: General Materials Science, Condensed Matter Physics
Sustainable Development Goals: SDG 8 - Decent Work and Economic Growth, SDG 12 - Responsible Consumption and Production
Electronic version(s): https://doi.org/10.1002/adem.202401316 (Access: Open)