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The industrial use of additive manufacturing for the production of metallic parts with high geometrical complexity and lot sizes close to one is rapidly increasing as a result of mass individualisation and applied safety relevant constructions. However, due to the high complexity of the production process, it is not yet fully understood and controlled, especially for changing (lot size one) part geometries.
Due to the thermal nature of the Laser-powder bed fusion (L-PBF) process – where parts are built up layer-wise by melting metal powder via laser - the properties of the produced part are strongly governed by its thermal history. Thus, a promising route for process monitoring is the use of thermography. However, the reconstruction of temperature information from thermographic data relies on the knowledge of the surface emissivity at each position on the part. Since the emissivity is strongly changing during the process due to phase changes, great temperature gradients, possible oxidation, and other potential influencing factors, the extraction of real temperature data from thermographic images is challenging. While the temperature development in and around the melt pool, where melting and solidification occur is most important for the development of the part properties. Also, the emissivity changes are most severe in this area, rendering the temperature deduction most challenging.
A possible route to overcome the entanglement of temperature and emissivity in the thermal radiation is the use of hyperspectral imaging in combination with temperature emissivity separation (TES) algorithms. As a first step towards the combined temperature and emissivity determination in the L-PBF process, here, we use a hyperspectral line camera system operating in the short-wave infrared region (0.9 µm to 1.7 µm) to measure the spectral radiance emitted. In this setup, the melt pool of the L-PBF process migrates through the camera’s 1D field of view, so that the radiation intensities are recorded simultaneously for multiple different wavelength ranges in a spatially resolved manner. At sufficiently high acquisition frame rate, an effective melt pool image can be reconstructed. Using the grey body approximation (emissivity is independent of the wavelength), a first, simple TES is performed, and the resulting emissivity and temperature values are compared to literature values. Subsequent work will include reference measurements of the spectral emissivity in different states allowing its analytical parametrisation as well as the adaption and optimisation of the TES algorithms. An illustration of the proposed method is shown in Fig.1.
The investigated method will allow to gain a deeper understanding of the L-PBF process, e.g., by quantitative validation of simulation results. Additionally, the results will provide a data basis for the development of less complex and cheaper sensor technologies for L-PBF in-process monitoring (or for related process), e.g., by using machine learning.
Results of the project ProMoAM (Process monitoring in additive manufacturing) presented. Results from in-situ eddy current testing, optical emission spectroscopy, thermography, optical tomography as well as particle and gas emission spectroscopy are summarized and correlated to results from computed tomography for future in-situ defect detection.
Additive manufacturing of metals gains increasing relevance in the industrial field for part production. However, especially for safety relevant applications, a suitable quality assurance is needed. A time and cost efficient route to achieve this goal is in-situ monitoring of the build process. Here, the BAM project ProMoAM (Process monitoring in additive manufacturing) is briefly introduced and recent advances of BAM in the field of in-situ monitoring of the L-PBF and the LMD process using thermography are presented.
For metal-based additive manufacturing, sensors and measuring systems for monitoring of the energy source, the build volume, the melt pool and the component geometry are already commercially available. Further methods of optics, spectroscopy and non-destructive testing are described in the literature as suitable for in-situ application, but there are only a few reports on practical implementations.
Therefore, a new BAM project aims to develop process monitoring methods for the in-situ evaluation of the quality of additively manufactured metal components. In addition to passive and active thermography, this includes optical tomography, optical emission and absorption spectroscopy, eddy current testing, laminography, X-ray backscattering and photoacoustic methods. These methods are used in additive manufacturing systems for selective laser melting, laser metal deposition and wire arc additive manufacturing. To handle the sometimes huge amounts of data, algorithms for efficient preprocessing are developed and characteristics of the in-situ data are extracted and correlated to defects and inhomogeneities, which are determined using reference methods such as computer tomography and metallography. This process monitoring and fusion of data of different measurement techniques should result in a significant reduction of costly and time-consuming, destructive or non-destructive tests after the production of the component and at the same time reduce the production of scrap.
Here, first results of simultaneous measurements of optical emission spectroscopy and thermography during the laser metal deposition process using 316L as building material are presented. Temperature values are extracted from spectroscopic data by fitting of blackbody emission spectra to the experimental data and compared with results from a thermographic camera. Measurements with and without powder flow reveal significant differences between welding at a pristine metal surface and previously melted positions on the build plate, illustrating the significant influence of the partial oxidation of the surface during the first welding process on subsequent welding. The measurement equipment can either be mounted stationary or following the laser path. While first results were obtained in the stationary mode, future applications for online monitoring of the build of whole parts in the mobile mode are planned.
This research was funded by BAM within the focus area Material.
Thermography is one on the most promising techniques for in-situ monitoring for metal additive manufacturing 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 a defect free cuboid specimen.
In-situ Prozessüberwachung in der additiven Fertigung von Metallen mittels optischer Verfahren
(2020)
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. Bereits jetzt werden erste Messsysteme zur Kontrolle der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie kommerziell angeboten. Weitere ZfP Verfahren, wie z.B. die aktive und passive Thermografie, werden in der Literatur als geeignet für die in-situ Anwendung angesehen, allerdings gibt es 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 zunächst das Projekt vorgestellt und anschließend der Fokus auf eine Messserie gelegt, in der Probekörper aus dem austenitischen Edelstahl 316L mit lokal variierenden Prozessparametern mittels selektiven Laserschmelzen (L-PBF) aufgebaut wurden. Der Bauprozess wurde hierbei durch das maschineneigene, koaxial arbeitende Photodiodensystem (Melt-Pool-Monitoring), einer Mittelwellen-Infrarotkamera und einer optischen Tomografiekamera im sichtbaren Wellenlängenbereich (Langzeitbelichtung für die Dauer eines Lagenaufbaus mit einer CMOS-Kamera mit hoher Ortsauflösung) simultan überwacht. Als Referenz für diese Methoden wurden die Probekörper mittels Computertomografie untersucht. Für die dabei anfallenden teils großen Datenmengen wurden Algorithmen für ein effizientes Preprocessing entwickelt. Es wurden Merkmale der Messdaten in Korrelation zu Fehlern und Inhomogenitäten extrahiert, welche für die einzelnen Methoden vergleichend vorgestellt und diskutiert werden.
Introduction to ProMoAM
(2021)