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Title data
Shah, Karim Ali ; Albuquerque, Rodrigo Q. ; Brütting, Christian ; Ruckdäschel, Holger:
Machine learning-based time series analysis of polylactic acid bead foam extrusion.
In: Journal of Applied Polymer Science.
Vol. 141
(2024)
Issue 44
.
- e56170.
ISSN 1097-4628
DOI der Verlagsversion: https://doi.org/10.1002/app.56170
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Project information
| Project title: |
Project's official title Project's id No information F.2-M7426.10.2.1/4/16 No information RU 2586/5-1 |
|---|---|
| Project financing: |
Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst Deutsche Forschungsgemeinschaft |
Abstract
Understanding the behavior of polymer melts during extrusion is essential for optimizing processes and developing new materials. However, analyzing the continuous data generated by an extruder poses significant challenges. This paper investigates the utility of machine learning in predicting melt pressure at the die plate in polylactic acid (PLA) bead foam extrusion, a critical parameter in the extrusion process. Utilizing a random forest (RF) model, we examine how various processing parameters influence melt pressure. By segmenting the data into time-delayed intervals, we achieve accurate predictions. We present forecasts of melt pressure at the die for intervals of 5 s, 1 min, and 5 min, demonstrating particularly strong performance for the 5-min forecast with a Mean Absolute Error (MAE) of 1.88 and the coefficient of determination (R² score) of 0.90. By exploring time series data, our study demonstrates the effectiveness of the RF model and provides a foundation for more advanced and precise control strategies in polymer bead extrusion processes.
Further data
| Item Type: | Article in a journal |
|---|---|
| Keywords: | bead foam extrusion; bead foams; bio-based polymers; machine learning; PLA,; polymer foams; time series; twin screw extruder |
| DDC Subjects: | 600 Technology, medicine, applied sciences > 620 Engineering |
| Institutions of the University: | Faculties > Faculty of Engineering Science > Chair Polymer Materials > Chair Polymer Materials - Univ.-Prof. Dr.-Ing. Holger Ruckdäschel Research Institutions > Affiliated Institutes > New Materials Bayreuth GmbH Faculties Faculties > Faculty of Engineering Science Faculties > Faculty of Engineering Science > Chair Polymer Materials Research Institutions Research Institutions > Affiliated Institutes |
| Language: | German |
| Originates at UBT: | Yes |
| URN: | urn:nbn:de:bvb:703-epub-8295-5 |
| Date Deposited: | 13 Mar 2025 06:42 |
| Last Modified: | 13 Mar 2025 06:42 |
| URI: | https://epub.uni-bayreuth.de/id/eprint/8295 |
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