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

verfasst von

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.

Organisationseinheit(en)

Institut für Mess- und Regelungstechnik
Institut für Transport- und Automatisierungstechnik
Automatisierungstechnik

Externe Organisation(en)

Deutsches Institut für Kautschuktechnologie e.V. (DIK)
Jade Hochschule Wilhelmshaven/Oldenburg/Elsfleth
Institut für Nanophotonik Göttingen e.V. (IFNANO)

Typ

Artikel

Journal

Advanced engineering materials

ISSN

1438-1656

Publikationsdatum

25.10.2024

Publikationsstatus

Elektronisch veröffentlicht (E-Pub)

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Allgemeine Materialwissenschaften, Physik der kondensierten Materie

Ziele für nachhaltige Entwicklung

SDG 8 – Anständige Arbeitsbedingungen und wirtschaftliches Wachstum, SDG 12 – Verantwortungsvoller Konsum und Produktion

Elektronische Version(en)

https://doi.org/10.1002/adem.202401316 (Zugang: Offen)