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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.
Aktuell werden Prozessmonitoringsysteme in der additiven Fertigung (AM) zur Überwachung der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie zumindest im metallbasierten AM schon kommerziell angeboten. Weitere Verfahren aus den Bereichen 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 Umsetzungen in die Praxis.
Die Bundesanstalt für Materialforschung und -prüfung hat ein neues Projekt gestartet, dessen Ziel die Entwicklung von Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Bauteile in AM-Prozessen mit Laser- bzw. Lichtbogenquellen ist. Verschiedene Verfahren der zerstörungsfreien Prüfung, wie Thermografie, optische Tomografie, optische Emissionsspektroskopie, Wirbelstromprüfung und Laminografie werden in verschiedenen AM-Prozessen zum Einsatz gebracht und die Ergebnisse fusioniert. Die evaluierten Ergebnisse werden mit Referenzverfahren wie Computertomografie und Ultraschall-Tauchtechnik verglichen. Ziel ist eine deutliche Reduzierung aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen nach der Fertigung des Bauteiles und zugleich eine Verringerung von Ausschussproduktion.
Hier wird das Projekt als Ganzes vorgestellt und der Fokus auf verschiedene Methoden der Temperaturmessung mit Hilfe der Thermografie gelegt. Anforderungen an die Messtechnik für verschiedene AM-Systeme werden diskutiert und erste experimentelle Ergebnisse werden präsentiert.
Additive manufacturing (AM) opens the route to a range of novel applications. However, the complexity of the manufacturing process poses a challenge to produce defect-free parts with a high reliability. Since process dynamics and resulting microstructures of AM parts are strongly influenced by the involved temperature fields and cooling rates, thermography is a valuable tool for process monitoring. Another approach to monitor the energy input into the part during process is the use of optical tomography.
Common visual camera systems reach much higher spatial resolution than infrared thermography cameras, whereas infrared thermography provides a much higher temperature dynamic. Therefore, the combined application increases the depth of information. Here, we present first measurement results using a laser beam melting setup that allows simultaneous acquisition of thermography and optical tomography from the same point of view using a beam splitter. A high-resolution CMOS camera operating in the visible spectral range is equipped with a near infrared bandpass filter and images of the build plate are recorded with long-term exposure during the whole layer exposing time. Thus, areas that reach higher maximum temperature or are at elevated temperature for an extended period of time appear brighter in the images. The used thermography camera is sensitive to the mid wavelength infrared range and records thermal videos of each layer exposure at an acquisition rate close to 1 kHz.
As a next step, we will use computer tomographic data of the built part as a reference for defect detection.
This research was funded by BAM within the focus area Materials.
Aktuell werden Prozessmonitoringsysteme in der additiven Fertigung (AM) zur Überwachung der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie zumindest im metallbasierten AM schon kommerziell angeboten. Weitere Verfahren aus den Bereichen 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 Umsetzungen in die Praxis.
Die Bundesanstalt für Materialforschung und -prüfung hat ein neues Projekt gestartet, dessen Ziel die Entwicklung von Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Bauteile in AM-Prozessen mit Laser- bzw. Lichtbogenquellen ist. Verschiedene Verfahren der zerstörungsfreien Prüfung, wie Thermografie, optische Tomografie, optische Emissionsspektroskopie, Wirbelstromprüfung und Laminografie werden in verschiedenen AM-Prozessen zum Einsatz gebracht und die Ergebnisse fusioniert. Die evaluierten Ergebnisse werden mit Referenzverfahren wie Computertomografie und Ultraschall-Tauchtechnik verglichen. Ziel ist eine deutliche Reduzierung aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen nach der Fertigung des Bauteiles und zugleich eine Verringerung von Ausschussproduktion.
Hier wird das Projekt als Ganzes vorgestellt und der Fokus auf verschiedene Methoden der Temperaturmessung mit Hilfe der Thermografie gelegt. Anforderungen an die Messtechnik für verschiedene AM-Systeme werden diskutiert und erste experimentelle Ergebnisse werden präsentiert.
The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
Safety-critical applications of products manufactured by laser powder bed fusion (PBF-LB/M) are still limited to date. This is mainly due to a lack of knowledge regarding the complex relationship between process, structure, and resulting properties. The assurance of homogeneity of the microstructure and homogeneity of the occurrence and distribution of defects within complexly shaped geometries is still challenging. Unexpected and unpredicted local inhomogeneities may cause catastrophic failures. The identification of material specific and machine specific process parameter windows for production of fully dense simple laboratory specimens is state of the art. However, the incorporation of changing thermal conditions that a complexly shaped component can be faced with during the manufacturing process is often neglected at the stage of a process window determination. This study demonstrates the tremendous effect of changing part temperatures on the defect occurrence for the broadly used stainless steel alloy AISI 316L. Process intrinsic variations of the surface temperature are caused by heat accumulation which was measured by use of a temperature adjusted mid-wavelength infrared (MWIR) camera. Heat accumulation was triggered by simple yet effective temporal and geometrical restrictions of heat dissipation. This was realized by a variation of inter layer times and reduced cross section areas of the specimens. Differences in surface temperature of up to 800 K were measured. A severe development of keyhole porosity resulted from these distinct intrinsic preheating temperatures, revealing a shift of the process window towards unstable melting conditions. The presented results may serve as a warning to not solely rely on process parameter optimization without considering the actual process conditions a real component is faced with during the manufacturing process. Additionally, it motivates the development of representative test specimens.
Undetected and undesired microstructural variations in components produced by laser powder bed fusion are a major challenge, especially for safety-critical components. In this study, an in-depth analysis of the microstructural features of 316L specimens produced by laser powder bed fusion at different levels of volumetric energy density and different levels of inter layer time is reported. The study has been conducted on specimens with an application relevant build height
(>100 mm). Furthermore, the evolution of the intrinsic preheating temperature during the build-up of specimens was monitored using a thermographic in-situ monitoring set-up. By applying recently determined emissivity values of 316L powder layers, real temperatures could be quantified. Heat accumulation led to preheating temperatures of up to about 600 °C. Significant differences in the preheating temperatures were discussed with respect to the individual process parameter combinations, including the build height. A strong effect of the inter layer time on the heat accumulation was observed. A shorter inter layer time resulted in an increase of the preheating temperature by more than a factor of 2 in the upper part of the specimens compared to longer inter layer times. This, in turn, resulted in heterogeneity of the microstructure and differences in material properties within individual specimens. The resulting differences in the microstructure were analyzed using electron back scatter diffraction and scanning electron microscopy. Results from chemical analysis as well as electron back scatter diffraction measurements indicated stable conditions in terms of chemical alloy composition and austenite phase content for the used set of parameter combinations. However, an increase of the average grain size by more than a factor of 2.5 could be revealed within individual specimens. Additionally, differences in feature size of the solidification cellular substructure were examined and a trend of increasing cell sizes was observed. This trend was attributed to differences in solidification rate and thermal gradients induced by differences in scanning velocity and preheating temperature. A change of the thermal history due to intrinsic preheating could be identified as the main cause of this heterogeneity. It was induced by critical combinations of the energy input and differences in heat transfer conditions by variations of the inter layer time. The microstructural variations were directly correlated to differences in hardness.
In this presentation we discuss the online monitoring of metallic AM parts produced by the Laser Powder Bed Fusion (LPBF) process by using optical, thermographic and electromagnetic methods. In a first approach we present the detection of defects generated during the process and discuss how to improve these methods for the optimization of design and production of metallic AM parts.
The project ProMoAM is presented. The goal of the project is to evaluate which NDT techniques or combination of techniques is suited for in-situ quality assurance in additive manufacturing of metals. To this end, also 3d-data fusion and visualization techniques are applied. Additional ex-situ NDT-techniques are used as references for defect detection and quantification. Feasability studies for NDT-techniques that are presently not applicable for in-situ use are performed as well.
The presentation gives a brief overview of the whole project and the different involved NDT-techniques.
Rapid cooling rates and steep temperature gradients are characteristic of additively manufactured parts and important factors for the residual stress formation. This study examined the influence of heat accumulation on the distribution of residual stress in two prisms produced by Laser Powder Bed Fusion (LPBF) of austenitic stainless steel 316L. The layers of the prisms were exposed using two different border fill scan strategies: one scanned from the centre to the perimeter and the other from the perimeter to the centre. The goal was to reveal the effect of different heat inputs on samples featuring the same solidification shrinkage. Residual stress was characterised in one plane perpendicular to the building direction at the mid height using Neutron and Lab X-ray diffraction. Thermography data obtained during the build process were analysed in order to correlate the cooling rates and apparent surface temperatures with the residual stress results. Optical microscopy and micro computed tomography were used to correlate defect populations with the residual stress distribution. The two scanning strategies led to residual stress distributions that were typical for additively manufactured components: compressive stresses in the bulk and tensile stresses at the surface. However, due to the different heat accumulation, the maximum residual stress levels differed. We concluded that solidification shrinkage plays a major role in determining the shape of the residual stress distribution, while the temperature gradient mechanism appears to determine the magnitude of peak residual stresses.