Learning controllers for adaptive spreading of carbon fiber tows

  • Carbon fiber reinforced polymers (CFRP) are lightweight but strong composite materials designed to reduce the weight of aerospace or automotive components - contributing to reduced greenhouse gas emissions. A common manufacturing process for carbon fiber tapes consists of aligning tows (bundles of carbon fiber filaments) side by side to form tapes via a spreading machine. Tows are pulled across metallic spreading bars that are conventionally kept in a fixed position. That can lead to high variations in quality metrics such as tape width or height. Alternatively, one could try to control the spreading bars based on the incoming tows' profiles. We investigate whether a machine learning approach, consisting of a supervised process model trained on real data and a process control model to choose adequate spreading bar positions is able to improve the tape quality variations. Our results indicate promising tendencies for adaptive tow spreading.

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Metadaten
Author:Julia KrützmannORCiD, Alexander SchiendorferORCiDGND, Sergej Beratz, Judith Moosburger-Will, Siegfried Horn, Wolfgang ReifORCiDGND
URN:urn:nbn:de:bvb:384-opus4-797133
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/79713
URL:https://lod2020.icas.xyz/program/
Parent Title (English):Proceedings of the Sixth International Conference on Machine Learning, Optimization, and Data Science - LOD 2020, 19-23 September 2020, Certosa di Pontignano, Siena, Tuscany, Italy
Type:Conference Proceeding
Language:English
Year of first Publication:2020
Publishing Institution:Universität Augsburg
Release Date:2020/09/25
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management
Fakultät für Angewandte Informatik / Institut für Software & Systems Engineering
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Lehrstuhl für Nachhaltige Materialien und Prozesse
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik / Lehrstuhl für Softwaretechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Latest Publications (not yet published in print):Latest Publications (not yet published in print)
Licence (German):Deutsches Urheberrecht