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Quality Prediction of Continuous Ultrasonic Welded Seams of High-Performance Thermoplastic Composites by means of Artificial Intelligence

Görick, Dominik and Larsen, Lars and Engelschall, Manuel and Schuster, Alfons (2021) Quality Prediction of Continuous Ultrasonic Welded Seams of High-Performance Thermoplastic Composites by means of Artificial Intelligence. In: Procedia Manufacturing, 55, pp. 116-123. FAIM 2021, 07-10. Sep. 2021, Griechenland. doi: 10.1016/j.promfg.2021.10.017. ISSN 2351-9789.

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Official URL: https://www.sciencedirect.com/science/article/pii/S2351978921002146

Abstract

Thermoplastic composites (TCs) are a famous choice when it comes to high performance designs for industrial applications. Since the growing demand on the use of this material, it is important to be able to evaluate suitable processing technologies. One of those technologies is continuous ultrasonic welding (CUSW) which creates continuous joints, also called seams, between two or more TCs parts. In CUSW mechanical oscillations are applied to the material and result in melting and connecting of the welding parts. The approach to predict joint strength (qualities) of continuous ultrasonic welded TCs by training different neural networks is investigated in this study. Quality class prediction around 72 % accuracy is achieved with a fully connected neural network. Concluding, quality prediction of welded TCs with the help of artificial intelligence seems to be a suitable approach for quality observation but more research could lead to more reliable neural networks for industrial applications.

Item URL in elib:https://elib.dlr.de/145534/
Document Type:Conference or Workshop Item (Speech)
Title:Quality Prediction of Continuous Ultrasonic Welded Seams of High-Performance Thermoplastic Composites by means of Artificial Intelligence
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Görick, DominikDominik.Goerick (at) dlr.deUNSPECIFIED
Larsen, Larslars-christian.larsen (at) dlr.dehttps://orcid.org/0000-0002-4450-8581
Engelschall, ManuelManuel.Engelschall (at) dlr.deUNSPECIFIED
Schuster, AlfonsAlfons.Schuster (at) dlr.dehttps://orcid.org/0000-0002-7444-366X
Date:3 November 2021
Journal or Publication Title:Procedia Manufacturing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:55
DOI :10.1016/j.promfg.2021.10.017
Page Range:pp. 116-123
ISSN:2351-9789
Status:Published
Keywords:Continuous Ultrasonic Welding; Thermoplastic Composites; Inline Process Monitoring; Artificial Intelligence; Neural Network; Deep Learning; 1DCNN
Event Title:FAIM 2021
Event Location:Griechenland
Event Type:international Conference
Event Dates:07-10. Sep. 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Clean Propulsion
DLR - Research area:Aeronautics
DLR - Program:L CP - Clean Propulsion
DLR - Research theme (Project):L - Advanced Materials and New Manufacturing Technologies
Location: Augsburg
Institutes and Institutions:Institute of Structures and Design > Automation and Production Technology
Deposited By: Görick, Dominik
Deposited On:12 Nov 2021 09:20
Last Modified:12 Nov 2021 09:20

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