TY - CONF A1 - Schumacher, David A1 - Meyendorf, N. A1 - Hakim, I. A1 - Ewert, Uwe ED - Chimenti, D. E. ED - Bond, L. J. T1 - Defect recognition in CFRP components using various NDT methods within a smart manufacturing process N2 - The manufacturing process of carbon fiber reinforced polymer (CFRP) components is gaining 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 process are e.g. porosity and voids which may lead to delaminations during operation and under load. To find irregularities and classify them as possible defects in an early stage of the manufacturing process is of high 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 compare various NDT methods which were applied to similar CFRP laminate samples in order to detect and characterize regions of 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 and evaluation of defects, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method shall be applied is inherent within the process. 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 concepts 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. T2 - 44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION CY - Provo, Utah, USA DA - 16.07.2017 KW - Carbon fiber reinforced polymers KW - Non-destructive testing KW - Smart industry (4.0) KW - Ultrasound KW - Laminography KW - Serial sectioning KW - Computed tompgraphy PY - 2018 SN - 978-0-7354-1644-4 U6 - https://doi.org/10.1063/1.5031521 SN - 0094-243X VL - 1949 SP - UNSP 020024, 1 EP - 11 PB - AIP Publishing AN - OPUS4-44773 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hakim, I. A1 - Schumacher, David A1 - Sundar, V. A1 - Donaldson, S. A1 - Creuz, A. A1 - Schneider, R. A1 - Keller, J. A1 - Browning, C. A1 - May, D. A1 - Abo Ras, M. A1 - Meyendorf, N. ED - Chimenti, D. E. ED - Bond, L. J. T1 - Volume imaging NDE and serial sectioning of carbon fiber composites N2 - A composite material is a combination of two or more materials with very different mechanical, thermal and electrical properties. The various forms of composite materials, due to their high material properties, are widely used as structural materials in the aviation, space, marine, automobile, and sports industries. However, some defects like voids, delamination, or inhomogeneous fiber distribution that form during the fabricating processes of composites can seriously affect the mechanical properties of the composite material. In this study, several imaging NDE techniques such as: thermography, high frequency eddy current, ultrasonic, x-ray radiography, x-ray laminography, and high resolution x-ray CT were conducted to characterize the microstructure of carbon fiber composites. Then, a 3D analysis was implemented by the destructive technique of serial sectioning for the same sample tested by the NDE methods. To better analyze the results of this work and extract a clear volume image for all features and defects contained in the composite material, an intensive comparison was conducted among hundreds of 3D-NDE and multi serial sections’ scan images showing the microstructure variation. T2 - 44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION CY - Provo, Utah, USA DA - 16.07.2017 KW - Carbon fiber reinforced polymers KW - Non-destructive testing KW - Thermography KW - Eddy current KW - Ultrasound KW - X-ray radiography KW - X-ray laminography KW - X-ray computed tomography KW - Serial sectioning PY - 2018 U6 - https://doi.org/10.1063/1.5031590 VL - 1949 SP - 120003-1 EP - 120003-10 PB - AIP Publishing AN - OPUS4-45173 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schumacher, David A1 - Meyendorf, N. A1 - Hakim, I. A1 - Ewert, Uwe T1 - Defect recognition in CFRP components using various NDT methods within a smart manufacturing process N2 - 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 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. T2 - 44th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE) CY - Provo, UT, USA DA - 17.07.2017 KW - Radiography KW - Computed tomography KW - Carbon fiber reinforced polymers KW - Non-destructive testing KW - Serial sectionning KW - Smart NDT PY - 2017 AN - OPUS4-41185 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -