Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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In situ microstructure analysis of Inconel 625 during laser powder bed fusion

2022 , Schmeiser, F. , Krohmer, E. , Wagner, C. , Schell, N. , Uhlmann, E. , Reimers, W.

Laser powder bed fusion is an additive manufacturing process that employs highly focused laser radiation for selective melting of a metal powder bed. This process entails a complex heat flow and thermal management that results in characteristic, often highly textured microstructures, which lead to mechanical anisotropy. In this study, high-energy X-ray diffraction experiments were carried out to illuminate the formation and evolution of microstructural features during LPBF. The nickel-base alloy Inconel 625 was used for in situ experiments using a custom LPBF system designed for these investigations. The diffraction patterns yielded results regarding texture, lattice defects, recrystallization, and chemical segregation. A combination of high laser power and scanning speed results in a strong preferred crystallographic orientation, while low laser power and scanning speed showed no clear texture. The observation of a constant gauge volume revealed solid-state texture changes without remelting. They were related to in situ recrystallization processes caused by the repeated laser scanning. After recrystallization, the formation and growth of segregations were deduced from an increasing diffraction peak asymmetry and confirmed by ex situ scanning transmission electron microscopy.

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Relative density prognosis for directed energy deposition with the help of artificial neural networks

2021 , Marko, A. , Schafner, A. , Raute, J. , Rethmeier, M.

Additive manufacturing, and therefore directed energy deposition, is gaining more and more interest from industrial users. However, quality assurance for the components produced is still a challenge. Machine learning, especially using artificial neuronal networks, is a potential method for ensuring a high-quality standard. Based on process parameters and monitoring data, part quality can be predicted. A further advantage is the ability to constantly learn and adopt to slight process changes. First tests using artificial neural networks focus on the prediction of track geometry. The results show that even a small data set is enough to provide high accuracy in the predictions. In this work, an artificial neural network for the predictive analysis of relative density in laser powder cladding has been developed. A central composite experimental design is used to generate 19 data sets. Input variables are laser power, feed rate and powder mass flow. Cubes are built up where density is considered as a target value. Several neural networks are trained and evaluated with these data sets. Different topologies and initial weights are considered. The best network reaches a confidence level of around 90 % for the prediction of relative density based on the process parameters. Finally, the optimization of the generalization performance is investigated. To this purpose, methods of variation in error limit as well as cross-validation are applied. In this way, density is predictable by an artificial neural network with an accuracy of about 95 %.

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Mit dem Wasserabrasivstrahl in eine neue Dimension

2021 , Reder, W. , Uhlmann, E. , Anders, S.

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Internal Stress Evolution and Subsurface Phase Transformation in Titanium Parts Manufactured by Laser Powder Bed Fusion - An In Situ X-Ray Diffraction Study

2021 , Schmeiser, F. , Krohmer, E. , Schell, N. , Uhlmann, E. , Reimers, W.

Laser powder bed fusion (LPBF) is a metal additive manufacturing technology, which enables the manufacturing of complex geometries for various metals and alloys. Herein, parts made from commercially pure titanium are studied using in situ synchrotron radiation diffraction experiments. Both the phase transformation and the internal stress buildup are evaluated depending on the processing parameters. For this purpose, evaluation approaches for both temperature and internal stresses from in situ diffraction patterns are presented. Four different parameter sets with varying energy inputs and laser scanning strategies are investigated. A combination of a low laser power and scanning speed leads to a more homogeneous stress distribution in the observed gauge volumes. The results show that the phase transformation is triggered during the primary melting and solidification of the powder and subsurface layers. Furthermore, the stress buildup as a function of the part height during the manufacturing process is clarified. A stress maximum is formed below the part surface, extending into deeper layers with increasing laser power. A temperature evaluation approach for absolute internal stresses shows that directional stresses decrease sharply during laser impact and reach their previous magnitude again during cooling.

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Characterization of Ti-6Al-4V Fabricated by Multilayer Laser Powder-Based Directed Energy Deposition

2022 , Ávila Calderón, Luis Alexander , Graf, Benjamin , Rehmer, Birgit , Petrat, Torsten , Skrotzki, Birgit , Rethmeier, Michael

Laser powder-based directed energy deposition (DED-L) is increasingly being used in additive manufacturing (AM). As AM technology, DED-L must consider specific challenges. It must achieve uniform volume growth over hundreds of layers and avoid heat buildup of the deposited material. Herein, Ti-6Al-4V is fabricated using an approach that addresses these challenges and is relevant in terms of transferability to DED-L applications in AM. The assessment of the obtained properties and the discussion of their relationship to the process conditions and resulting microstructure are presented. The quality of the manufacturing process is proven in terms of the reproducibility of properties between individual blanks and with respect to the building height. The characterization demonstrates that excellent mechanical properties are achieved at room temperature and at 400 C.

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Ex Situ Residual Stress Analysis of Chemical Vapor Deposited Diamond Coated Cutting Tools by Synchrotron X-Ray Diffraction in Transmission Geometry

2021 , Hinzmann, D. , Böttcher, K. , Reimers, W. , Uhlmann, E.

When machining difficult-to-cut, nonferrous materials, chemical vapor deposited (CVD) diamond-coated cutting tools are applied. The tools' favorable mechanical property profile is based on the hardness of the coating as well as the adaptability of the substrate. Nevertheless, the reproducibility of machining results and process stability are limited by insufficient coating adhesion. The resulting cutting tool failure is based on coating delamination initiated by crack development. By assessing residual stress as an influence of coating adhesion, an analysis of CVD diamond-coated tools is performed using synchrotron X-ray diffraction in transmission geometry. Investigation of a nanocrystalline and multilayer morphology on cobalt-based tungsten carbide (WC-Co) and a silicon nitride-based ceramic (Si3N4) provides the distribution of the principal in-plane residual stress tensor component s22 depending on the coating morphology and substrate material. Contrary to microcrystalline CVD diamond, nanocrystalline layers decrease the compressive residual stress. In addition, the CVD diamond coating deposited on the Si3N4 substrate material tends to induce an overall initial tensile residual stress that leads to increased tool performance compared to WC-Co-based coated tools. Variation of the coating morphology as well as the substrate material offers the possibility to extend the current model for residual stress-dependent tool failure.

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Resilienz durch dynamisches Prozessmanagement

2021 , Knothe, T. , Oertwig, N. , Woesthoff, J. , Sala, A. , Lütkemeyer, M. , Gaal, A.

Krisen treten regelmäßig auf und betreffen aufgrund zunehmender Globalisierung immer mehr Unternehmen gleichzeitig. In diesem Beitrag wird ein Ansatz für ein dynamisches Prozessmanagement vorgestellt, welches die Fähigkeit der Früherkennung von Disruptionen und gleichzeitig auch Routine sowie Agilität im Normal- wie auch im Krisenmodus durchgängig unterstützt.

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Steigerung der Energieeffizienz mittels Energiekennzahlen am Beispiel der Metallverarbeitung

2022 , Sigg, Stefan , Kühn, Armin , Schmidt, Alexander , Roder, Sven , Thiele, Gregor , Krüger, Jörg

Die Energiewende und die einhergehende Forderung nach Effizienzsteigerungen stellen produzierende Unternehmen vor betriebliche und technische Herausforderungen. Methoden und Technologien des Energiemanagements gewinnen damit auch im Mittelstand an Relevanz. Dabei sind Kennzahlen ein Schlüssel, um die aktuelle Energieeffizienz einzuschätzen und Potenziale für Einsparungen zu identifizieren. Der Artikel dokumentiert Erfahrungen der Anwender mit Bezug auf Konzepte aus der Wissenschaft, um Interessierten aus der Industrie den Einstieg in das Thema zu erleichtern.

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MBSE-Modellierung für Verhaltens- und Struktursimulation

2021 , Zimmermann, T.C.

echnische Systeme werden mithilfe von Modellbasiertem Systems Engineering (MBSE) beschrieben, um eine domänenübergreifende Wissensbasis zu erzeugen, die es den beteiligten Stakeholdern ermöglicht, Systemelemente konsistent und parallel zu entwickeln. Die Qualität dieser Modelle ist maßgeblich dafür, wie effizient dieses Wissen aus dem MBSE auch zur Systemexploration verwendet werden kann, um Systemzusammenhänge zu analysieren, indem verschiedene Modellarten gemeinsam simuliert werden.

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Steuerung von Laser-induzierten periodischen Oberflächenstrukturen

2021 , Uhlmann, E. , Schweitzer, L. , Schneider, P. , Michel, A. , Hein, C.

Laser-induzierte periodische Oberflächenstrukturen (LIPSS) weisen ein hohes Potenzial für Anwendungen in den Bereichen der Oberflächenfunktionalisierung auf. Die Steuerung der Richtung dieser Nanostrukturen kann nur durch Änderung der Laserpolarisation erfolgen. Auf dem Markt gibt es kein System zur automatischen Änderung der LIPSS-Orientierung. Für den industriellen Einsatz ist dies vom Vorteil, um Inhomogenität im Strukturverlauf zu vermeiden. In diesem Beitrag wird eine Systemlösung vorgestellt, indem die Steuerung der Richtung von Nanotexturen ermöglicht wird.

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