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 -