TY - CONF A1 - Scheuschner, Nils T1 - In-situ Prozessüberwachung in der additiven Fertigung von Metallen (PBF-LB /M) mittels TT und ET N2 - Durch die additive Fertigung ergeben sich durch die nun mögliche wirtschaftliche Fertigung hochgradig individueller und komplexer metallischer Bauteile in kleinen Stückzahlen bis hinunter zum Einzelstück für viele Industriebereiche ganz neue Möglichkeiten. Gleichzeitig entstehen jedoch neue Herausforderungen im Bereich der Qualitätssicherung, da sich auf statistischen Methoden beruhende Ansätze nicht anwenden lassen, ohne wiederum die Vorteile der Fertigung massiv einzuschränken. Eine mögliche Lösung für dieses Problem liegt in der Anwendung verschiedener In-situ-Überwachungstechniken während des Bauprozesses. Jedoch sind nur wenige dieser Techniken kommerziell verfügbar und noch nicht so weit erforscht, dass die Einhaltung strenger Qualitäts- und Sicherheitsstandards gewährleistet werden kann. In diesem Beitrag stellen wir die Ergebnisse einer Studie über mittels L-PBF gefertigte Probekörper aus der Nickelbasis-Superlegierung Haynes 282 vor, bei denen die Bildung von Defekten durch lokale Variationen der Prozessparameter wie der Laserleistung provoziert wurde. Die Proben wurden in-situ mittels Thermographie, optischer Tomographie, Schmelzbadüberwachung und Wirbelstromprüfung sowie ex-situ mittels Computertomographie (CT) überwacht, mit dem Ziel, die Machbarkeit und die Aussichten der einzelnen Methoden für die zuverlässige Erkennung der Bildung relevanter Defekte zu bewerten. T2 - DGZfP Jahrestagung 2022 CY - Kassel, Germany DA - 23.05.2022 KW - Additive Manufacturing KW - Thermografie KW - Additive Fertigung KW - Thermography PY - 2022 AN - OPUS4-55851 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ Monitoring of PBF-LB/M by thermography, optical tomography, melt-pool-monitoring and eddy current N2 - The formation of defects such as keyhole pores is a major challenge for the production of metal parts by Laser Powder Bed Fusion (LPBF). The LPBF process is characterized by a large number of influencing factors which can be hard to quantify. Machine Learning (ML) is a prominent tool to predict the outcome of complex processes on the basis of different sensor data. In this study, a ML model for defect prediction is created using thermographic image features as input data. As a reference, the porosity information calculated from an x-ray Micro Computed Tomography (µCT) scan of the produced specimen is used. Physical knowledge about the keyhole pore formation is incorporated into the model to increase the prediction accuracy. From the prediction result, the quality of the input data is evaluated and future demands on in-situ monitoring of LPBF processes are formulated. T2 - AM Bench 2022 CY - Bethesda, Washingthon DC, USA DA - 15.08.2022 KW - Additive Manufacturing KW - Thermography KW - Additive Fertigung KW - Thermografie PY - 2022 AN - OPUS4-55854 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ monitoring of the laser powder bed fusion process by thermography, optical tomography and melt pool monitoring for defect detection N2 - For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M ) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring) but not researched to an extent that allows to guarantee the adherence to strict quality and safety standards. In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques. T2 - LiM Conference 2023 - Lasers in Manufacturing CY - Munich, Germany DA - 26.06.2023 KW - Thermography KW - High temperature alloys KW - Additive Manufacturing KW - PBF-LB/M PY - 2023 AN - OPUS4-57947 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils A1 - Heinrichsdorff, F. A1 - Oster, Simon A1 - Uhlmann, E. A1 - Polte, J. A1 - Gordei, A. A1 - Hilgenberg, Kai T1 - In-situ monitoring of the laser powder bed fusion process by thermography, optical tomography and melt pool monitoring for defect detection N2 - For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring), which have not been researched to an extent that allows to guarantee the adherence to strict quality and safety standards. In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques. T2 - Lasers in Manufacturing Conference 2023 CY - Munich, Germany DA - 26.06.2023 KW - Thermography KW - Optical tomography KW - Melt-pool-monitoring KW - Laser powder bed fusion KW - Haynes 282 KW - Additive Manufacturing PY - 2023 UR - https://www.wlt.de/lim2023-proceedings/system-engineering-and-process-control SP - 1 EP - 10 AN - OPUS4-58466 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - Emissivity Prediction of Rough Cast Iron for Laser Thermography N2 - This study presents a method for predicting the emissivity of rough cast iron surfaces to enhance the accuracy of laser thermography in industrial non-destructive testing (NDT). Traditional emissivity measurements are impractical in industrial settings due to environmental interference and equipment limitations. The proposed approach replaces complex setups like integrating spheres with a simplified illumination unit and reflection measurements. By leveraging known material properties and surface characteristics, an algorithm predicts directional emissivity. Experimental results of an initial feasibility study show strong agreement between predicted and measured values, demonstrating the method’s potential for real-time emissivity correction in industrial thermographic inspections. T2 - Advanced Infrared Technology and Applications (AITA) 2023 CY - Venice, Italy DA - 10.09.2023 KW - Thermography KW - Laser KW - NDT KW - Cast iron PY - 2023 AN - OPUS4-63121 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mohr, Gunther A1 - Chaudry, Mohsin Ali A1 - Scheuschner, Nils A1 - Blasón Gonzalez, Sergio A1 - Madia, Mauro A1 - Hilgenberg, Kai T1 - Thermal history transfer from complex components to representative test specimens in laser powder bed fusion N2 - Additively manufactured components are characterized by heterogeneous mechanical properties due to variations of the microstructure, flaws and residual stresses resulting from the inhomogeneous fabrication process. The large number of influencing factors poses a further challenge in understanding the correlation between material properties, process parameters and component geometry. Therefore, the qualification of components based on witness specimens produced within the same job is questionable. This work aims to present a new strategy for the characterization of PBF-LB/M components based on representative specimens. The key assumption is the feasibility of a transfer of the thermal history from a component to a specimen. It is assumed that similar material properties are determined for components and specimens produced adopting a similar thermal history. After the definition of a region of interest in the component, a combination of thermal analyses by means of finite elements and in-situ experimental determination of the thermal history through infrared thermography is used to produce test coupons with a similar thermal history. The effectiveness of the procedure is demonstrated on a pressure vessel for applications in the chemical industry. KW - Additive manufacturing KW - Heat accumulation KW - Thermal history KW - In situ monitoring KW - Process simulation KW - Representative specimens PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-602651 DO - https://doi.org/10.1007/s40964-024-00689-8 SN - 2363-9512 SN - 2363-9520 SP - 1 EP - 16 PB - Springer CY - Cham, Switzerland AN - OPUS4-60265 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon T1 - Local porosity prediction in metal powder bed fusion using in-situ thermography: A comparative study of machine learning techniques N2 - The formation of flaws such as internal porosity in parts produced by Metal-based Powder Bed Fusion with Laser Beam (PBF-LB/M) significantly hinders its broader industrial application, as porosity can potentially lead to part failure. Addressing this issue, this study explores the efficacy of in-situ thermography, particularly short-wave infrared thermography, for detecting and predicting porosity during manufacturing. This technique is capable of monitoring the part’s thermal history which is closely connected to the flaw formation process. Recent advancements in Machine Learning (ML) have been increasingly leveraged for porosity prediction in PBF-LB/M. However, previous research primarily focused on global rather than localized porosity prediction which simplified the complex prediction task. Thereby, the opportunity to correlate the predicted flaw position with expected part strain to judge the severity of the flaw for part performance is neglected. This study aims to bridge this gap by studying the potential of SWIR thermography for predicting local porosity levels using regression models. The models are trained on data from two identical HAYNES®282® specimens. We compare the effectiveness of feature-based and raw data-based models in predicting different porosity types and examine the importance of input data in porosity prediction. We show that models trained on SWIR thermogram data can identify systematic trends in local flaw formation. This is demonstrated for forced flaw formation using process parameter shifts and, moreover, for randomly formed flaws in the specimen bulk. Furthermore, we identify features of high importance for the prediction of lack-of-fusion and keyhole porosity from SWIR monitoring data. KW - PBF-LB/M KW - In situ monitoring KW - Thermography KW - Additive Manufacturing KW - Process monitoring KW - Porosity prediction KW - Machine Learning KW - Feature extraction PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-621798 DO - https://doi.org/10.1016/j.addma.2024.104502 SN - 2214-7810 VL - 95 SP - 1 EP - 17 PB - Elsevier B.V. AN - OPUS4-62179 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Maierhofer, Christiane A1 - Altenburg, Simon A1 - Scheuschner, Nils ED - Meyendorf, N. ED - Ida, N. ED - Singh, R. ED - Vrana, J. T1 - In Situ Real-Time Monitoring Versus Post NDE for Quality Assurance of Additively Manufactured Metal Parts N2 - In this chapter, the current state-of-the-art of in situ monitoring and in situ NDE methods in additive manufacturing is summarized. The focus is set on methods, which are suitable for making statements about the quality and usability of a component currently being manufactured. This includes methods which can be used to determine state properties like temperature or density, other physical properties like electrical or thermal conductivity, the microstructure, the chemical composition, the actual geometry, or which enable the direct detection of defects like cracks, voids, delaminations, or inclusions. Thus, optical, thermographic, acoustic, and electromagnetic methods, as well as methods being suitable for investigating particle and fume emission are presented. The requirements of in situ monitoring methods with a focus on thermographic methods are discussed by considering different additive manufacturing processes like laser powder bed fusion (PBF-LB/M) and direct energy deposition (DED-LB/M). Examples of the successful implementation and applications of such monitoring methods at BAM are given. The in situ monitoring and NDE methods are compared against post-process NDE methods. The advantages and challenges of in situ methods concerning real-time data analysis and the application of AI algorithms are addressed and discussed. KW - Additive manufacturing KW - In situ monitoring KW - In situ NDE KW - Post NDE KW - Thermography KW - Laser powder bed fusion KW - Direct energy deposition PY - 2021 SN - 978-3-030-48200-8 DO - https://doi.org/10.1007/978-3-030-48200-8_51-1 SP - 1 EP - 37 PB - Springer Nature Switzerland AG CY - Cham, Switzerland ET - 1 AN - OPUS4-52824 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon A1 - Scheuschner, Nils A1 - Straße, Anne A1 - Gumenyuk, Andrey A1 - Maierhofer, Christiane T1 - Towards the determination of real process temperatures in the LMD process by multispectral thermography N2 - Due to the rapid thermal cycles involved in additive manufacturing of metals, high internal stresses and peculiar microstructures occur, which influence the parts mechanical properties. To systematically examine their formation, in-process measurements of the temperature are needed. Since the part emissivity is strongly inhomogeneous and rapidly changing in the process, the applicability of thermography for the determination of thermodynamic temperatures is limited. Measuring the thermal radiation in different wavelengths simultaneously, temperature and emissivity can be separated. Here, we present results of a preliminary study using multispectral thermography to obtain real temperatures and emissivities in directed energy deposition (DED) processes. T2 - Thermosense: Thermal Infrared Applications XLIII CY - Online meeting DA - 12.04.2021 KW - Additive Manufacturing KW - Process monitoring KW - Multispectral thermography KW - Laser metal deposition KW - TES KW - LMD KW - Temperature emissivity separation PY - 2021 DO - https://doi.org/10.1117/12.2587881 VL - 2021 SP - 77 EP - 83 PB - SPIE AN - OPUS4-52516 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ Monitoring der Additiven Fertigung von Metallen im LPA Prozess mittels Optischer Emissionsspektrometrie (OES) und Thermografie (TT) N2 - Einer der aussichtsreichsten Ansätze, die Qualität und Sicherheit der gefertigten Teile in der metallbasierten additiven Fertigung (AM) zu erhöhen und die Notwendigkeit aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen (ZfP) nach der Fertigung zu verringern, liegt in dem Einsatz von in-situ Prozessüberwachungstechniken. Viele wichtige Prozessgrößen bei der additiven Fertigung sind thermischer Natur, wie z.B. die Temperatur des Schmelzbades. Aufgrund der Zugänglichkeit zum Werkstück während des Bauprozesses bieten sich optische Verfahren zur Temperaturbestimmung an. Für die Thermografie und Optische Emissionsspektrometrie im IR-Bereich, welche für die in-situ Anwendung prinzipiell als geeignet angesehen werden können, gibt es allerdings noch wenig konkrete praktische Umsetzungen, da die Möglichkeiten und individuellen Grenzen dieser Methoden, angewendet auf AM, noch nicht ausreichend erforscht sind. Aus diesem Grund verfolgt die BAM mit dem Projekt „Process Monitoring of AM“ (ProMoAM) im Themenfeld Material das Ziel, Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Metallbauteile weiterzuentwickeln. Im Beitrag wird der Fokus auf eine Versuchsserie gelegt, bei der Aufbau von Probekörpern aus dem austenitischen Edelstahl 316L mittels Laser-Pulver-Auftragschweißen (LPA) durch od. mit Hilfe von IR-Spektrometrie und Thermografie in-situ überwacht wurde. Hierbei stellen u.a. die hohe Bandbreite der zu messenden Temperaturen, die Bestimmung der Emissivität und ihre Änderung bei Phasenübergängen des Metalls große experimentelle Herausforderungen dar, wobei jede Methode individuelle Vor- und Nachteile aufweist, welche verglichen werden. T2 - DGZfP-Jahrestagung 2021 CY - Online meeting DA - 10.05.2021 KW - Additive Manufacturing KW - Thermography KW - Direct Energy Deposition KW - Additive Fertigung KW - Thermografie KW - Laserauftragschweißen PY - 2021 AN - OPUS4-52744 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Scheuschner, Nils A1 - Altenburg, Simon A1 - Pignatelli, Giuseppe A1 - Maierhofer, Christiane A1 - Straße, Anne A1 - Gornushkin, Igor B. A1 - Gumenyuk, Andrey T1 - Vergleich der Messungen der Schmelzbadtemperatur bei der Additiven Fertigung von Metallen mittels IR-Spektroskopie und Thermografie T1 - Comparison of measurements of the melt pool temperature during the additive production of metals by means of IR spectroscopy and thermography N2 - Im Rahmen des Themenfeldprojektes „Process Monitoring of AM“ (ProMoAM) evaluiert die Bundesanstalt für Materialforschung und -Prüfung (BAM) gegenwärtig die Anwendbarkeit verschiedenster ZfP-Verfahren zur in-situ Prozessüberwachung in der additiven Fertigung (AM) von Metallen in Hinblick auf die Qualitätssicherung. Einige der wichtigsten Messgrößen sind hierbei die Temperatur des Schmelzbades und die Abkühlrate, welche starken Einfluss auf das Gefüge und die Eigenspannung haben. Aufgrund der Zugänglichkeit zum Werkstück während des Bauprozesses bieten sich optische Verfahren zu Temperaturbestimmung an. Hierbei stellen jedoch u. a. die hohe Bandbreite der zu messenden Temperaturen, die Bestimmung der Emissivität und ihre Änderung bei Phasenübergängen der verwendeten Legierung große experimentelle Herausforderungen dar. Eine weitere Herausforderung stellt für die IR-Spektroskopie die Absorption durch das Schutzgas und weitere optische Elemente dar. Um diese auch in einem industriellen Umfeld kompensieren zu können, wurde eine Methode entwickelt, die das gemessene Spektrum bei der Verfestigung des Werkstoffes als Referenz nutzt. In diesem Beitrag wird die Anwendung dieser Methode für die IR-Spektrometrie als auch Thermografische Messungen beim Laser-Pulver-Auftragschweißen von 316L gezeigt, wobei beide Methoden weiterhin in Hinblick auf ihre individuellen Vor- und Nachteile miteinander verglichen werden. N2 - Within the topic area project “Process Monitoring of AM” (ProMoAM) the Federal Institute for Materials Research and Testing is currently evaluating the applicability of various NDT methods for in-situ process Monitoring in the additive manufacturing (AM) of metals with regard to quality assurance. Two of the most important variables to measure are the temperature of the molten pool and the cooling rate, which have a strong influence on the microstructure and the residual stress. Due to the accessibility of the workpiece during the construction process, optical methods for temperature determination are suitable. However, the wide range of temperatures to be measured, the determination of emissivity and its change during phase transitions of the alloy pose great experimental challenges. Another challenge for IR spectroscopy is the absorption by the inert gas and other optical elements. In order to be able to compensate for this in an industrial environment, a method was developed which uses the measured spectrum as a reference when the material is solidified. This paper shows the application of this method for IR spectrometry as well as thermographic measurements during laser powder cladding of 316L. Furthermore both methods are compared with respect to their individual Advantages and disadvantages. KW - Laser-Pulver-Auftragschweißen KW - Thermografie KW - Direct Energy Deposition KW - IR-Spektroskopie KW - Additive Fertigung KW - Laser metal deposition KW - Thermography KW - IR-spectroscopy KW - Additive manufacturing PY - 2021 DO - https://doi.org/10.1515/teme-2021-0056 VL - 88 IS - 10 SP - 626 EP - 632 PB - De Gruyter CY - Oldenburg AN - OPUS4-52987 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ temperature measurements of the LMD process by IR-spectroscopy and Thermography N2 - Temperature measurements of the LMD process by IR-spectroscopy and Thermography are presenet and compared. T2 - 2st Workshop on In-situ Monitoring and Microstructure Development in Additive Manufacturing CY - Online meeting DA - 19.04.2021 KW - Additive Manufacturing KW - Thermography PY - 2021 AN - OPUS4-52565 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Breese, Philipp Peter A1 - Becker, Tina A1 - Heinrichsdorff, F. A1 - Altenburg, Simon T1 - From Thermographic In-situ Monitoring to Porosity Detection – A Deep Learning Framework for Quality Control in Laser Powder Bed Fusion N2 - In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk. T2 - SMSI - Sensor and Measurement Science International 2023 CY - Nürnberg, Germany DA - 08.05.2023 KW - Porosity KW - Laser powder bed fusion KW - In-situ monitoring KW - Thermography KW - Machine Learning PY - 2023 UR - https://www.ama-science.org/proceedings/details/4404 DO - https://doi.org/10.5162/SMSI2023/C5.4 SP - 179 EP - 180 AN - OPUS4-57616 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Straße, Anne A1 - Gumenyuk, Andrey A1 - Scheuschner, Nils A1 - Altenburg, Simon A1 - Pignatelli, Giuseppe A1 - Gornushkin, Igor B. A1 - Baensch, Franziska A1 - Rethmeier, Michael T1 - In-situ Prozessüberwachung beim Laser-Pulver-Auftragschweißen (LPA) mittels Thermografie, optischer Emissionsspektroskopie (OES) und Schallemissionsanalyse (SEA) N2 - Vor allem in den letzten Jahren ist das Interesse der Industrie an der additiven Fertigung deutlich gestiegen. Die Vorteile dieser Verfahren sind zahlreich und ermöglichen eine ressourcenschonende, kundenorientierte Fertigung von Bauteilen, welche zur stetigen Entwicklung neue Anwendungsbereiche und Werkstoffe führen. Aufgrund der steigenden Anwendungsfälle, nimmt auch der Wunsch nach Betriebssicherheit unabhängig von anschließenden kostenintensiven zerstörenden und zerstörungsfreien Prüfverfahren zu. Zu diesem Zweck werden im Rahmen des von der BAM durchgeführten Themenfeldprojektes „Prozessmonitoring in Additive Manufacturing“ verschiedenste Verfahren auf ihre Tauglichkeit für den in-situ Einsatz bei der Prozessüberwachung in der additiven Fertigung untersucht. Hier werden drei dieser in-situ Verfahren, die Thermografie, die optische Emissionsspektroskopie und die Schallmissionsanalyse für den Einsatz beim Laser-Pulver-Auftragschweißen betrachtet. T2 - 41. Assistentenseminar der Füge- und Schweißtechnik CY - Magdeburg, Germany DA - 02.09.2020 KW - Laser-Pulver-Auftragschweißen (LPA) KW - Thermographie KW - Optische Emissionsspektroskopie (OES) KW - Schallemissionsanalyse (SEA) PY - 2021 SN - 978-3-96144-141-9 VL - 370 SP - 132 EP - 140 PB - DVS MEdia CY - Düsseldorf AN - OPUS4-53967 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mohr, Gunther A1 - Scheuschner, Nils A1 - Hilgenberg, Kai T1 - In situ heat accumulation by geometrical features obstructing heat flux and by reduced inter layer times in laser powder bed fusion of AISI 316L stainless steel N2 - Material qualification for laser powder bed fusion (L-PBF) processes are often based on results derived from additively manufactured (AM) bulk material or small density cubes, although it is well known that the part geometry has a tremendous influence on the heat flux and, therefore, on the thermal history of an AM component. This study shows experimentally the effect of simple geometrical obstructions to the heat flux on cooling behavior and solidification conditions of 316L stainless steel processed by L-PBF. Additionally, it respects two distinct inter layer times (ILT) as well as the build height of the parts. The cooling behavior of the parts is in-situ traced by infrared (IR) thermography during the built-up. The IR signals reveal significant differences in cooling conditions, which are correlated to differences in melt pool geometries. The acquired data and results can be used for validation of computational models and improvements of quality assurance. KW - Selective laser beam melting KW - Thermography KW - Melt pool depth KW - Inter layer time KW - Ppreheating temperature KW - Additive Manufacturing PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-512549 DO - https://doi.org/10.1016/j.procir.2020.09.030 VL - 94 SP - 155 EP - 160 PB - Elsevier B.V. AN - OPUS4-51254 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Scheuschner, Nils A1 - Oster, Simon A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Comparison of NIR and SWIR thermography for defect detection in Laser Powder Bed Fusion N2 - Since laser powder bed fusion (PBF-LB/M) is prone to the formation of defects during the building process, a fundamental requirement for widespread application is to find ways to assure safety and reliability of the additively manufactured parts. A possible solution for this problem lies in the usage of in-situ thermographic monitoring for defect detection. In this contribution we investigate possibilities and limitations of the VIS/NIR wavelength range for defect detection. A VIS/NIR camera can be based on conventional silicon-based sensors which typically have much higher spatial and temporal resolution in the same price range but are more limited in the detectable temperature range than infrared sensors designed for longer wavelengths. To investigate the influence, we compared the thermographic signatures during the creation of artificially provoked defects by local parameter variations in test specimens made of a nickel alloy (UNS N07208) for two different wavelength ranges (~980 nm and ~1600 nm). KW - Laser powder bed fusion KW - PBF-LB/M KW - Thermography KW - Additive manufacturing KW - NDT PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-610380 DO - https://doi.org/10.1016/j.procir.2024.08.122 VL - 124 SP - 301 EP - 304 PB - Elsevier B.V. AN - OPUS4-61038 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, G. T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser powder bed fusion (PBF-LB/M, L-PBF) KW - Selective laser melting KW - Thermography KW - Machine learning PY - 2023 DO - https://doi.org/10.1515/teme-2023-0062 SN - 0171-8096 SN - 2196-7113 VL - 90 SP - 85 EP - 96 PB - De Gruyter CY - Berlin AN - OPUS4-58366 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Becker, Tina A1 - Altenburg, Simon A1 - Scheuschner, Nils A1 - Breese, Philipp Peter A1 - Metz, C. A1 - Hilgenberg, Kai A1 - Maierhofer, Christiane T1 - In-situ monitoring of the Laser Powder Bed Fusion build process via bi- chromatic optical tomography N2 - As metal additive manufacturing (AM) is entering industrial serial production of safety relevant components, the need for reliable process qualification is growing continuously. Especially in strictly regulated industries, such as aviation, the use of AM is strongly dependent on ensuring consistent quality of components. Because of its numerous influencing factors, up to now, the metal AM process is not fully controllable. Today, expensive part qualification processes for each single component are common in industry. This contribution focusses on bi-chromatic optical tomography as a new approach for AM in-situ quality control. In contrast to classical optical tomography, the emitted process radiation is monitored simultaneously with two temperature calibrated cameras at two separate wavelength bands. This approach allows one to estimate the local maximum temperatures during the manufacturing process, thus increases the comparability of monitoring data of different processes. A new process information level at low investment cost is reachable, compared to, e.g., infrared thermography. T2 - LANE 2022 CY - Fürth, Germany DA - 04.08.2022 KW - Optical tomography KW - Additive Manufacturing KW - L-PBF KW - In-process monitoring PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-560270 DO - https://doi.org/10.1016/j.procir.2022.08.035 SN - 2212-8271 VL - 111 SP - 340 EP - 344 PB - Elsevier B.V. CY - Amsterdam AN - OPUS4-56027 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - SAMMIE - Research PBF-LB/M system for the development of in-situ monitoring methods N2 - By allowing economic on-demand manufacturing of highly customized and complex workpieces, metal based additive manufacturing (AM) has the prospect to revolutionize many industrial areas. Since AM is prone to the formation of defects during the building process, a fundamental requirement for AM is to find ways to assure the safety and reliability of the additively manufactured parts to become applicable in most fields. A possible solution for this problem lies in the deployment of various in-situ monitoring techniques. However, only a few of these techniques are commercially available and are not researched to an extent that allows to guarantee the adherence to strict quality and safety standards. Since commercial AM machines are not designed for research applications, they provide only limited access to the build chamber during the process and little control over the exact timing and parameters of the process. Therefore, for our research at BAM, we built a laser powder bed fusion system (PBF-LB/M), called “Sensor-based Additive Manufacturing MachInE” (SAMMIE). It provides a fully open system architecture with flexible accesses to the build camber and full control of the complete process. In this contribution, we show first results using thermographic cameras and optical tomography. The flexibility of SAMMIE allows us to use the multiple cameras either fixed relatively to the build plate or coaxially to the process laser. T2 - 20th World Conference on Non-Destructive Testing (WCNDT) CY - Incheon, South Korea DA - 27.05.2024 KW - PBF-LB/M KW - In situ monitoring KW - Custom machine KW - Additive Manufacturing KW - Thermography PY - 2024 AN - OPUS4-62471 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon A1 - Scheuschner, Nils A1 - Maierhofer, Christiane A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Thermography in laser powder bed fusion of metals: time over threshold as feasible feature in thermographic data N2 - Thermography is one on the most promising techniques for in-situ monitoring of metal additive manufacturing processes. Especially in laser powder bed fusion processes, the high process dynamics and the strong focus of the laser beam cause a very complex thermal history within the produced specimens, such as multiple heating cycles within single layer expositions. This complicates data interpretation, e.g., in terms of cooling rates. A quantity that is easily calculated is the time a specific area of the specimen is at a temperature above a chosen threshold value (TOT). Here, we discuss variations occurring in time-over-threshold-maps during manufacturing of an almost defect free cuboid specimen. T2 - 15th Quantitative InfraRed Thermography conference CY - Online meeting DA - 21.09.2020 KW - Additive Manufacturing KW - Process monitoring KW - Thermography KW - L-PBF KW - Time over threshold PY - 2020 DO - https://doi.org/10.21611/qirt.2020.005 SP - 1 EP - 5 PB - QIRT Council CY - Quebec, Canada AN - OPUS4-52014 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - Infrared Thermography of the DED-LB/M and PBF LB/M processes N2 - Infrared thermography is a technique that allows to measure the temperatures of objects by analyzing the intensity of the thermal emission without the need of direct contact with very high spatial and temporal resolution. As the temperature is a fundamental factor for the additive manufacturing processes of metals, infrared thermography can provide experimental data that can be used for the validation of simulations and improving the understanding of the processes as well as for in-situ process monitoring for nondestructive evaluation (NDE) for quality control. In this talk we will provide an overview over the possibilities of state of the art thermographic in-situ monitoring systems for the DED-LB/M and PBF-LB/M processes and the challenges such as phase transitions and unknown emissivity values in respect to the determination of real temperatures. We define the requirements for different camera systems in various configurations and give examples on the selection of appropriate measurement parameters and data acquisition techniques as well as on techniques for data analysis and interpretation. Finally, we compare in-situ monitoring methods against post NDE methods by analyzing the advantages and disadvantages of both. This research was funded by BAM within the Focus Area Materials. T2 - Coupled2021 - IX International Conference on Coupled Problems in Science and Engineering CY - Online meeting DA - 13.06.2021 KW - Additive Manufacturing KW - Thermography KW - Direct Energy Deposition PY - 2021 AN - OPUS4-54399 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ziegler, Mathias A1 - Altenburg, Simon A1 - Krankenhagen, Rainer A1 - Maierhofer, Christiane A1 - Scheuschner, Nils A1 - Marquardt, E A1 - Mühlberger, W. A1 - Nagel, F. A1 - Neumann, E. A1 - Rohwetter, P. A1 - Rutz, F. A1 - Schwake, C. A1 - Schramm, S. A1 - Schwaneberg, F. A1 - Taubert, R. D. T1 - Thermografie und Strahlungsthermometrie - Stand und Trends N2 - In vielen Umgebungen, besonders bei hohen Temperaturen, korrosiven Umgebungen oder auf bewegten oder schlecht zugänglichen Flächen, kann die Temperatur nicht oder nur mit nicht akzeptablem Aufwand mit Berührungsthermometern gemessen werden. Diese Umgebungsbedingungen sind unter anderem in der chemischen Industrie, der Lebensmittel-, Metall-, Glas-, Kunststoff- und Papierherstellung sowie bei der Lacktrocknung anzutreffen. In diesen Bereichen kommen Strahlungsthermometer zum Einsatz. Der VDI-Statusreport zeigt typische Anwendungsfelder von nicht radiometrisch kalibrierten Wärmebildkameras und von radiometrisch kalibrierten Thermografiekameras. Um verlässlich mit spezifizierten Messunsicherheiten berührungslos Temperaturen zu messen, müssen die Strahlungsthermometer und Thermografiekameras nicht nur kalibriert, sondern radiometrisch und strahlungsthermometrisch umfassend charakterisiert werden. Auch die optische Materialeigenschaft, der spektrale Emissionsgrad und die Gesamtstrahlungsbilanz (Strahlung des Messobjekts und der Umgebung) sind bei der industriellen Temperaturmessung von großer Bedeutung. In den letzten Jahrzehnten ist dazu ein umfassendes technisches Regelwerk entstanden, das wir Ihnen mit diesem VDI-Statusreport vorstellen. Manche in den Richtlinien beschriebenen Kennwerte mögen abstrakt wirken. In diesem Statusreport zeigen wir an konkreten Beispielen, was diese Kenngrößen für die berührungslose Temperaturmessung bedeuten. Beispiele von Anwendungen zeigen, wo temperaturmessende Thermografiekameras und ausschließlich bildgebende Wärmebildkameras in der Praxis eingesetzt werden. Mit einer Analyse, welche Themen und Anwendungen derzeit besonders intensiv diskutiert werden, versuchen wir Trends für zukünftige Entwicklungen herauszuarbeiten. KW - Thermografie KW - Temperaturmessung PY - 2021 UR - https://www.vdi.de/ueber-uns/presse/publikationen/details/thermografie-und-strahlungsthermometrie-stand-und-trends SP - 1 EP - 40 PB - VDI Verein Deutscher Ingenieure e.V. CY - Düsseldorf AN - OPUS4-52904 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, G. T1 - Erratum to: Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion N2 - In this erratum to our previously published study section, we correct an error related to the first paragragh of section 5 "Prediction framework". PY - 2024 DO - https://doi.org/10.1515/teme-2023-0166 SN - 0171-8096 SN - 2196-7113 VL - 91 IS - 2 SP - 139 EP - 141 PB - De Gruyter CY - Berlin AN - OPUS4-59471 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Scheuschner, Nils A1 - Bartholmai, Matthias A1 - Lilienthal, A.J. T1 - Experimental Validation of the Cone-Shaped Remote Gas Sensor Model N2 - Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements. Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold. T2 - IEEE Sensors 2019 CY - Montreal, Canada DA - 27.10.2019 KW - Remote gas sensor model KW - TDLAS KW - Gas dispersion simulation PY - 2019 SN - 978-1-7281-1634-1 SP - 104 EP - 107 PB - IEEE AN - OPUS4-49548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - Comparison of in-situ OES and Thermography in the LMD process N2 - In this talk optical emission spectroscopy (OES) and thermographic measurements of the Laser Metal Deposition Process (LMD) are presented. T2 - Workshop on Additive Manufacturing: Process, materials, simulation & implants CY - BAM, Berlin, Germany DA - 13.05.2019 KW - Additive Manufacturing KW - Infrared Thermography PY - 2019 AN - OPUS4-48054 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - Verfahrensentwicklung für die Prozessüberwachung in der additiven Fertigung - Thermografie N2 - Für die Prozessüberwachung in der additiven Fertigung (AM) werden Sensoren und Messsysteme zur Kontrolle der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie zumindest im metallbasierten AM schon kommerziell angeboten. Weitere Verfahren der Optik, Spektroskopie und zerstörungsfreien Prüfung werden in der Literatur als geeignet für die in-situ Anwendung bezeichnet, es finden sich aber nur wenige Berichte über konkrete praktische Umsetzungen. Ein neues Projekt der BAM im Themenfeld Material hat daher das Ziel, Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Metallbauteile in AM-Prozessen mit Laser- bzw. Lichtbogenquellen zu entwickeln. Dies beinhaltet neben passiver und aktiver Thermografie die optische Tomografie, die optische Emissionsspektroskopie, die Wirbelstromprüfung, die Laminografie, die Röntgenrückstreuung und photoakustische Verfahren. Diese Verfahren werden in verschiedenen AM-Systemen zum selektiven Laserschmelzen, zum Laser-Pulver-Auftragsschweißen und zum Lichtbogenschweißen mit Drahtzuführung zum Einsatz gebracht. Für die zum Teil sehr großen Datenmengen werden Algorithmen für ein effizientes Preprocessing entwickelt und Merkmale der Messdaten in Korrelation zu Fehlern und Inhomogenitäten extrahiert, welche mit Referenzverfahren wie Computertomografie und Ultraschall-Tauchtechnik ermittelt werden. Die Ergebnisse der Einzelverfahren werden fusioniert und mit den Fertigungsparametern korreliert. Diese Prozessüberwachung soll eine deutliche Reduzierung aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen nach der Fertigung des Bauteiles und zugleich eine Verringerung von Ausschussproduktion bewirken. Im Beitrag wird zunächst das Projekt als Ganzes vorgestellt und dann der Fokus auf die Thermografie mit Detektoren in verschiedenen Wellenlängenbereichen gelegt. Anforderungen an die Messtechnik für verschiedene AM-Systeme werden diskutiert und experimentelle Ergebnisse im Vergleich zur optischen Tomografie und weiterer Verfahren präsentiert. T2 - DGZfP DACH Jahrestagung 2019 CY - Friedrichshafen, Germany DA - 27.05.2019 KW - Additive Fertigung KW - 3D Druck KW - Thermografie KW - L-PBF KW - SLM PY - 2019 AN - OPUS4-50213 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ Thermografie in der additiven Fertigung mittels Laser-Pulver-Auftragsschweißen N2 - Im Rahmen des Themenfeld Projektes „Process Monitoring of AM“ (ProMoAM) evaluiert die BAM gegenwärtig die Anwendbarkeit verschiedenster ZfP-Verfahren, darunter die Thermografie, zur Prozessüberwachung in der additiven Fertigung von Metallen in Hinblick auf die Qualitätssicherung. In diesem Beitrag werden SWIR-Thermografiemessungen während des Bauprozesses mittels Laser Pulver Auftragsschweißen (LPA) vorgestellt. Eine Herausforderung im Rahmen dieser Messungen liegt in der Positionierung der Kamera, welche entweder fixiert am Schweißarm, also mitbewegt, oder fixiert in der Baukammer, also stationär, erfolgen kann, wobei beide Varianten mit individuellen Vor- und Nachteilen verbunden sind. Eine stationäre Befestigung der Kamera ermöglicht zwar eine einfachere Zuordnung der Messdaten zu der jeweiligen Position im Bauteil, führt jedoch bei komplexeren Geometrien zwangsläufig zu Problemen durch Abschattungen und zu defokussierten Bereichen. Zur Auswertung von Thermogrammen, welche durch eine mit dem Schweißarm mitbewegte Kamera aufgenommen wurden, sind hingegen für jedes Bild akkurate Positionsdaten der Kamera nötig um die Messdaten einer Position im Bauteil zuzuordnen. Da die Positionsdaten des Schweißarmes im allgemeinen Fall durch die Anlagensoftware nicht zur Verfügung gestellt werden, muss diese Information durch zusätzliche Messungen aufgezeichnet werden. Hierzu verwenden wir einen an der Kamera befestigten Beschleunigungssensor. Dieser ermöglicht einen zeitlichen Abgleich mit dem vorprogrammierten Verfahrweg des Schweißarmes, welcher im Allgemeinen noch Unsicherheiten bezüglich genauer Geschwindigkeiten und Beschleunigungen offenlässt. Weiterhin untersuchen wir den Einfluss des empfindlichen Spektralbereiches der IR-Kamera durch den Vergleich von Messungen mit verschiedenen schmalbandigen Bandpassfiltern (25 nm FWHM) in einem Bereich von 1150 nm bis 1550 nm. T2 - Thermographie-Kolloquium 2019 CY - Halle (Saale), Germany DA - 19.09.2019 KW - Additive manufacturing KW - 3D printing KW - Thermography KW - Direct energy deposition KW - Laser Metal Deposition KW - 3D Druck KW - Laser Pulver Auftragsschweißen KW - Additive Fertigung KW - Thermografie PY - 2019 AN - OPUS4-49078 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - In-situ thermographic monitoring of the laser metal deposition process N2 - By allowing economic on demand manufacturing of highly customized and complex workpieces, metal based additive manufacturing (AM) has the prospect to revolutionize many industrial areas. Since AM is prone to the formation of defects during the building process, a fundamental requirement for AM to become applicable in most fields is the ability to guarantee the adherence to strict quality and safety standards. A possible solution for this problem lies in the deployment of various in-situ monitoring techniques. For most of these techniques, the application to AM is still very poorly understood. Therefore, the BAM in its mission to provide safety in technology has initiated the project “Process Monitoring of AM” (ProMoAM). In this project, a wide range of in-situ process monitoring techniques, including active and passive thermography, optical tomography, optical emission and absorption spectroscopy, eddy current testing, laminography, X-ray backscattering and photoacoustic methods, are applied to laser metal deposition (LMD), laser powder bed fusion and wire arc AM. Since it is still unclear which measured quantities are relevant for the detection of defects, these measurements are performed very thoroughly. In successive steps, the data acquired by all these methods is fused and compared to the results of reference methods such as computer tomography and ultrasonic immersion testing. The goal is to find reliable methods to detect the formation of defects during the building process. The detailed acquired data sets may also be used for comparison with simulations. Here, we show first results of high speed (> 300 Hz) thermographic measurements of the LMD process in the SWIR range using 316L as building material. For these experiments, the camera was mounted fixed to the welding arm of the LMD machine to keep the molten pool in focus, regardless of the shape of the specimen. As the thermograms do not contain any information about the current spatial position during the building process, we use an acceleration sensor to track the movement and synchronize the measured data with the predefined welding path. This allows us to reconstruct the geometry of the workpieces and assign the thermographic data to spatial positions. Furthermore, we investigate the influence of the acquisition wavelength on the thermographic data by comparing measurements acquired with different narrow bandpass filters (50 nm FWHM) in a spectral range from 1150 nm to 1550 nm. This research was funded by BAM within the Focus Area Materials. T2 - Sim-AM 2019 - 2. International Conference on Simulation for Additive Manufacturing CY - Pavia, Italy DA - 11.09.2019 KW - Additive manufacturing KW - 3D printing KW - Thermography KW - Direct energy deposition KW - Laser Metal Deposition KW - 3D Druck KW - Laser Pulver Auftragsschweißen KW - Additive Fertigung KW - Thermografie PY - 2019 AN - OPUS4-49070 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils A1 - Altenburg, Simon A1 - Straße, Anne A1 - Gumenyuk, Andrey A1 - Maierhofer, Christiane T1 - In-situ thermographic monitoring of the laser metal deposition process N2 - In this paper shortwave infrared (SWIR) thermographic measurements of the manufacturing of thin single-line walls via laser metal deposition (LMD) are presented. As the thermographic camera is mounted fixed to the welding arm, an acceleration sensor was used to assist in reconstructing the spatial position from the predefined welding path. Hereby we could obtain data sets containing the size of the molten pool and the oxide covered areas as functions of the position in the workpiece. Furthermore, the influence of the acquisition wavelength onto the thermograms was investigated in a spectral range from 1250 nm to 1550 nm. All wavelengths turned out to be usable for the in-situ process monitoring of the LMD process. The longer wavelengths are shown to be beneficial for the lower temperature range, while shorter wavelengths show more details within the molten pool. T2 - Sim-AM 2019 - 2. International Conference on Simulation for Additive Manufacturing CY - Pavia, Italy DA - 11.09.2019 KW - Additive manufacturing KW - 3D printing KW - Thermography KW - Direct energy deposition KW - Laser Metal Deposition KW - 3D Druck KW - Laser Pulver Auftragsschweißen KW - Additive Fertigung KW - Thermografie PY - 2019 UR - http://congress.cimne.com/SIM-AM2019/frontal/Doc/proceedings.pdf SN - 978-84-949194-8-0 SP - 246 EP - 255 AN - OPUS4-49086 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -