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Defect recognition in CFRP components using various NDT methods within a smart manufacturing process

  • The manufacturing process of carbon fiber reinforced polymer (CFRP) components is playing a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing are e.g. porosity and voids which may lead to delaminations during operation and under load. To find those defects in an early stage of the manufacturing process is of huge importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we present various NDT methods which are applied to similar CFRP laminate samples in order to detect and characterize defective volume. Besides ultrasound, thermography and eddy current, different x-ray methods like radiography, laminography and computed tomographyThe manufacturing process of carbon fiber reinforced polymer (CFRP) components is playing a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing are e.g. porosity and voids which may lead to delaminations during operation and under load. To find those defects in an early stage of the manufacturing process is of huge importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we present various NDT methods which are applied to similar CFRP laminate samples in order to detect and characterize defective volume. Besides ultrasound, thermography and eddy current, different x-ray methods like radiography, laminography and computed tomography are used to investigate the samples. These methods are compared with the intention to evaluate their capability to reliably detect and characterize defective volume. Beyond the detection of flaws, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method to apply is made by the process itself. Is it possible to design an in-line or at-line testing process which can recognize defects reliably and reduce testing time and costs? This study aims to show up opportunities of designing a smart NDT process synchronized to the production based on the ideas of smart production (Industry 4.0). A set of defective CFRP laminate samples and different NDT methods were used to demonstrate how effective defects are recognized and how communication between interconnected NDT sensors and the manufacturing process could be organized.zeige mehrzeige weniger

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Metadaten
Autor*innen:David Schumacher
Koautor*innen:N. Meyendorf, I. Hakim, Uwe Ewert
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2017
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten
Freie Schlagwörter:Carbon fiber reinforced polymers; Computed tomography; Non-destructive testing; Radiography; Serial sectionning; Smart NDT
Veranstaltung:44th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE)
Veranstaltungsort:Provo, UT, USA
Beginndatum der Veranstaltung:17.07.2017
Enddatum der Veranstaltung:20.07.2017
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:01.08.2017
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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