TY - JOUR A1 - Breese, Philipp Peter A1 - Altenburg, Simon T1 - Absolute temperature determination in laser powder bed fusion (PBF-LB/M) via hyperspectral thermography N2 - Temperature is a key characteristic in laser powder bed fusion of metals (PBF-LB/M). As a quantitative physical property, the temperature can determine the actual process quality independently from the nominal process parameters. Thus, establishing a process evaluation on temperatures rather than the comparison of process conditions is expected to be more effective. However, quantitative in situ temperature measurements with classical thermographic methods are virtually impossible. The reason is that the required emissivity value changes drastically throughout the process. Additionally, large temperature ranges along with the highly dynamic nature of the PBF-LB/M process make temperature measurements difficult. Based on this challenge, this work presents a method for hyperspectral temperature determination. The spectral exitance (in W/m2⋅nm) was measured in situ at many adjacent wavelengths in the short-wave infrared (SWIR). This enabled a local temperature determination via Planck’s law in combination with a spectral emissivity function. The temperature field of the melt pool crossing the 1D measurement line was reconstructed from the information, gathered at nearly 20 kHz sampling rate. The reconstructed melt pool had a spatial resolution of 17 µm by 40 µm, and temperatures between 2700 and 1300 K were observable. Comparison of the 316L stainless steel solidification temperature and the observed solidification plateau in the gathered thermal data revealed a relative error of less than 6% in the absolute temperature measurement. These initial results of hyperspectral temperature determination in PBF-LB/M show the potential in the method. It allows for physically founded process evaluation, and the prospects for tuning and validation of numerical simulations are highly promising. KW - Additive Manufacturing KW - Infrared Thermography KW - In-situ Monitoring KW - Quantitative Temperature Measurement KW - Emissivity PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-631977 DO - https://doi.org/10.1007/s40964-025-01148-8 SN - 2363-9512 SP - 1 EP - 10 PB - Springer Science and Business Media LLC AN - OPUS4-63197 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Breese, Philipp Peter T1 - Fundamentals of quantitative temperature determination during laser powder bed fusion of metals (PBF-LB/M) via hyperspectral thermography N2 - Additive manufacturing (AM, also known as 3D printing) of metals is becoming increasingly important in industrial applications. Reasons for this include the ability to realize complex component designs and the use of novel materials. This distinguishes AM from conventional manufacturing methods such as subtractive manufacturing (turning, milling, etc.). The most widely used AM process for metals is laser powder bed fusion (PBF-LB/M, also known as selective laser melting SLM). Currently, it has the highest degree of industrialization and the largest number of machines in use. In PBF-LB/M, the feedstock is present as metal powder in an inert gas atmosphere inside a process chamber where a laser melts it locally. By repeatedly lowering the build platform, applying a new layer of powder, and then selectively melting it with the laser, a component is built up layer by layer. The local temperature distributions that occur during this process determine not only the properties of the finished component, but also the possible formation of defects such as pores and cracks. Due to the high relevance of the thermal history for precise geometries and defect formation, a temporally and spatially resolved measurement of quantitative (or real/actual) temperatures would be optimal. Quantitative values would ensure comparability and repeatability of the AM process which would also positively affect the quality and safety of the manufactured component. Furthermore, it would also contribute to the validation of simulations and to a deeper understanding of the manufacturing process itself. At present, however, only qualitative monitoring of the thermal radiation is performed (e.g., by monitoring the melt pool using a photodiode), and safety-relevant components must be inspected ex situ afterwards which is time-consuming and costly. A reason for the lack of quantitative temperature data from the process are the challenging conditions of the PBF-LB/M process with high scanning speeds and a small laser spot diameter. Furthermore, the emissivity of the surface changes at high dynamics (temporally/spatially) as well as with temperature and wavelength. This specifically makes contactless temperature determination based on emitted infrared radiation challenging for PBF-LB/M. Although classical thermography offers very good qualitative insights, it is not sufficient for a reliable quantitative temperature determination without a complex temperature calibration including image segmentation and assignment of previously determined emissivities. For this reason, this publication presents the hyperspectral thermography approach for the PBF-LB/M process: The emitted infrared radiation is measured simultaneously at many adjacent wavelengths. In this study, this is realized via a fast hyperspectral line camera that operates in the short-wave infrared range. The thermal radiation of a line on the target is spectrally dispersed and detected to measure the radiant exitance along that line. If the melt pool of the PBF-LB/M process moves through this line at a sufficient frame rate, a spatial reconstruction of an effective melt pool is possible. One approach to determine the desired emissivities and the quantitative temperature from this hyperspectral data are temperature-emissivity separation (TES) methods. A major problem is that n spectral measurements are available, but n+1 parameters are required for each image pixel (n emissivity values + one temperature value). TES methods offer the possibility to approximate this mathematically underconstrained problem in a reliable and traceable way by analytically parameterizing the spectral emissivity with a few degrees of freedom. Using this approach, setup and method are applied to a research machine for PBF-LB/M, called SAMMIE (Sensor-based Additive Manufacturing Machine). First results under AM process conditions are shown which form the basis for the determination of quantitative temperatures in the PBFLB/M process. This marks an important contribution to improving the comparability and repeatability of production, validating simulations, and understanding the process itself. When fully developed and validated, the presented method can also provide reference measurements to evaluate and optimize other, more practical monitoring methods, such as melt pool monitoring or optical tomography. In the long run, this will help to increase confidence in the safety of AM products. T2 - QIRT 2024 CY - Zagreb, Croatia DA - 01.07.2024 KW - Additive Manufacturing KW - Additive Fertigung KW - Real Temperature KW - Melt Pool KW - Emissivity PY - 2024 AN - OPUS4-60762 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -