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

delete2024-10-25
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OA
AI
A
Alexander Aschemann *
P
Paul‐Felix Hagen
S
Simon Albers
R
Robin Rofallski
S
Sven Schwabe
M
M. Dagher
M
Marco Lukas
S
Sebastian Leineweber
B
Benjamin Klie
P
Patrick Schneider
H
Hagen Bossemeyer
L
Lennart Hinz
M
Markus Kästner
B
Birger Reitz
E
Eduard Reithmeier
T
Thomas Lühmann
H
Hainer Wackerbarth
L
Ludger Overmeyer
U
Ulrich Giese
DOI:10.1002/adem.202401316delete
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摘要

摘要

En 中文
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.
Keyword:
AI-based process control
digitalization
Laser-induced breakdown spectroscopy
optical metrology
rubber extrusion

期刊

Advanced Engineering Materials 封面图
Advanced Engineering Materials
IF:
3.3
论文数:
9.3K
被引数:
2.2W

机构

L
Leibniz University Hannover
学者数:
1.1W
论文数: 8.5K
被引数: 1.1W
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