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µCT is used to validate the capability of online monitoring for in-situ detection of defects during the L-PBF build process, which is a focus of the TF project ProMoAM.
Our first experiments show that online monitoring using thermography and optical tomography cameras are able to detect defects in the built part. But further research is needed to understand root cause of the correlation.
The literature has shown that the application of laminography provides advantages as 3D radiographic imaging with depth information for in house and mobile testing. This permits to distinguish between overlapping indications, measure the extension along radiation direction and classify indications as surface open or subsurface
ones as required in critical engineering assessment. This work provides a comparative study and measurements of the three techniques Digital Radiography (DR) with Digital Detector Arrays (DDA), Coplanar Translational Laminography (CTL) and Computed Tomography (CT), applied for composite pipeline inspection. It is demonstrated that CTL and CT provide advantages for the evaluation of pipe-to-pipe connections and the evaluation of adhesive applications. They show indications of discontinuities with higher contrast sensitivity than radiography.
Beyond it, two specimen, namely Phantom 1 and Phantom 2, were developed and manufactured by additive manufacturing to analyze the preferential detection sensitivity and the direction of features and depth information for laminographic measurements. Another goal was to show the laminographic capabilities to distinguish between overlapping discontinuities. CTL is especially suitable for mobile inspection. Special glass fiber reinforced polymer samples (GRP) were manufactured for further analysis and comparisons between the abovementioned techniques. Finally, Phantoms 1 and 2 show the capability of laminography to detect overlapping indications and also show that discontinuities oriented perpendicular to the scan direction have the highest contrast sensitivity for laminographic measurements.
The triaxial distribution of the residual stress in laser powder bed fused austenitic steel 316L was determined by X-ray and neutron diffraction. The residual stress analysis results were linked to the thermal history of the specimens, which were manufactured with varying inter-layer-times and scanning velocities. A clear link between the in-process temperature of the specimens and the residual stress was found, based on in-situ monitoring data.
The Influence of the Temperature Gradient on the Distribution of Residual Stresses in AM AISI 316L
(2019)
Steep temperature gradients and solidification shrinkage are the main contributors to the formation of residual stresses in additively manufactured metallic parts produced by laser beam melting. The aim of this work was to determine the influence of the temperature gradient.
Diffraction results show a similar pattern for both specimens, indicating the shrinkage to be more dominant for the distribution of residual stresses than the temperature gradient. Thermography results imply that a higher energy input result in higher compressive residual stresses in the bulk.
An unusual microstructure, inherent residual stresses and void formation are the three key aspects to control when assessing metallic parts made by LPBF. This talk explains an experiment to unravel the interlinked influence of the two mechanisms for the formation of residual stresses in LPBF: the temperature gradient mechanism and constricted solidification shrinkage. The impact of each mechanism on the shape and magnitudes of the residual stress distribution is described. Combined results from neutron diffraction, X-ray diffraction, computed tomography and in-situ thermography are presented.
Also, influence of scan strategies as well as surface roughness of subjacent layers on void formation is shown. Results from computed tomography and in-situ thermography of a specimen dedicated to study the interaction of the melt pool with layers of powder underneath the currently illuminated surface are presented.
The influence of the inter-layer-time and the scanning velocity on the surface and bulk residual stress in laser powder bed fused 316L specimens was investigated. This study combines X-ray and neutron diffraction results with the thermal history of the specimens acquired through in-situ process monitoring. The process parameter variations were observed to directly influence the thermal history, which gave new insights in the assessment of the residual stress results.
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.
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.
Sandwich-Schalenstrukturen in situ charakterisiert mit Thermographie und Felddehnungsmessungen
(2018)
An der BAM wurde ein Schalenprüfstand entwickelt, mit dem typische Sandwichschalenstrukturen unter simulierter Betriebsbeanspruchung belastet werden können. Im mechanischen Ermüdungsversuch wurden in situ die Entstehung von Schäden in Schalenprüfkörpern mit Test-Imperfektionen mittels der passiven Thermographie und Felddehnungsmessungen verfolgt. Damit konnten der Zeitpunkt, der Schadensursprung und der Schadensfortschritt zerstörungsfrei bestimmt werden. Zudem wurden vergleichend Schalenprüfkörper mit Luftultraschall und der Röntgen-Laminographie untersucht. Im Rahmen eines BMWi-Forschungsvorhabens wurden die Schädigungsmechanismen evaluiert und Empfehlungen für die Praxis der Fertigung von Rotorblättern abgeleitet. In diesem Beitrag wird sich auf die Darstellung der ZfP-Verfahren und der ZfP-Ergebnisse konzentriert.
Design of freedom, performance improvement, cost reduction and lead time reduction are key targets when manufacturing parts in a layer-by-layer fashion using the laser powder bed fusion process (LPBF). Many research groups are focussed on improving the LPBF process to achieve the manufacturing of sound parts from a structural integrity perspective. In particular, the formation and distribution of residual stress (RS) remains a critical aspect of LPBF. The determination of the RS in LPBF benefits from the use of neutron diffraction (ND), as it allows the non-destructive mapping of the triaxial RS with a good spatial resolution. Two case studies are presented based on experiments carried out on the angular-dispersive neutron diffractometers Strain Analyser for Large Scale Engineering Applications (SALSA) (Institut Laue Langevin, Grenoble) and STRESS-Spec (FRM II, Garching). The RS in LPBF parts having a rectangular and more complex geometry (lattice structure) is analysed. The former example discusses the mapping of the RS in a rectangular body manufactured from stainless steel 316L. The manufacturing of these parts was monitored using an in-situ thermography set-up to link the RS to the thermal history. The latter discusses the RS in a lattice structure manufactured from the nickel base superalloy IN625. This geometry is challenging to characterise, and the use of a X-ray computed tomography twin is presented as tool to support the alignment of the ND experiment. The results from these case studies show a clear link between the thermal history and the RS magnitudes, as well as giving insights on the RS formation.
Das Prozessmonitoring stellt einen wichtigen Baustein für eine Qualitätssicherung additiv gefertigter Bauteile dar, insbesondere bei kleinen Losgrößen. Der Vortrag zeigt einen Überblick aktueller Entwicklungen der BAM im Bereich des Prozessmonitorings für das Laserstrahlschmelzen (laser powder bed fusion) metallischer Werkstoffe. Durch Vergleich mit der Referenzmethode Computertomografie wird am Beispiel der thermografischen Verfahren gezeigt, wie relevante Defekte in Bauteilen detektiert werden können und Einsatzpotenziale sowie Limitierungen aufgezeigt.
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.
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
The detection of internal irregularities is crucial for quality assessment in metal-based additive manufacturing (AM) technologies such as laser powder bed fusion (L-PBF). The utilization of in-process thermography as an in situ monitoring tool in combination with post-process X-ray micro computed tomography (XCT) as a reference technique has shown great potential for this aim. Due to the small irregularity dimensions, a precise registration of the datasets is necessary as a
requirement for correlation. In this study, the registration of thermography and XCT reference datasets of a cylindric specimen containing keyhole pores is carried out for the development of a porosity prediction model. The considered datasets show variations in shape, data type and dimensionality, especially due to shrinkage and material elevation effects present in the manufactured part. Since the resulting deformations are challenging for registration, a novel preprocessing methodology is introduced that involves an adaptive volume adjustment algorithm which is based on the porosity distribution in the specimen. Thus, the implementation of a simple three-dimensional image-to-image registration is enabled. The results demonstrate the influence of the part deformation on the resulting porosity location and the importance of registration in terms of irregularity prediction.
Integration of fiber reinforcement in high-performance cementitious materials has become widely applied in many fields of construction. One of the most investigated advantages of steel Fiber reinforced concrete (SFRC) is the deceleration of crack growth and hence its improved sustainability.
Additional benefits are associated with its structural properties, as fibers can significantly increase the ductility and the tensile strength of concrete. In some applications it is even possible to entirely replace the conventional reinforcement, leading to significant logistical and environmental benefits.
Fiber reinforcement can, however, have critical disadvantages and even hinder the Performance of concrete, since it can induce an anisotropic material behavior of the mixture if the fibers are not appropriately oriented. For a safe use of SFRC in the future, reliable non-destructive testing (NDT) methods need to be identified to assess the fibers’ orientation in hardened concrete. In this study,
ultrasonic material testing, electrical impedance testing, and X-ray computed tomography have been investigated for this purpose using specially produced samples with biased or random Fiber orientations. We demonstrate the capabilities of each of these NDT techniques for fiber orientation measurements and draw conclusions based on these results about the most promising areas for future research and development.
Adopting X-ray computed tomography (XCT) for ex-situ characterization of battery materials has gained interest in the past decade. The main goal of this paper is to demonstrate the effectiveness of several X-ray computer tomography techniques to study commercial batteries. General guidelines are provided to select the most suitable imaging equipment and parameters for investigations of lithium-ion batteries, spanning the length scales from cell to electrode, down to particle level. Relevantly, such parameters would also be suitable for operando experiments.
Safety mechanisms and manufacturing inconsistencies at cell level as well as defects and inhomogeneity in cathode and anode is illustrated and quantified. Furthermore, relation of beam energy and sample-detector-distance on contrast retrieved from attenuation and phase shift is inspected using Synchrotron XCT.
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.