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Eingeladener Vortrag
- nein (1)
Laser-induced periodic surface structures (LIPSS) enable a large variety of different surface functionalizations for applications in the fields of optics, fluidics, tribology, or medicine. Moreover, high spatial frequency LIPSS (HSFL) provide an appealing and straightforward way for the generation of surface nanostructures featuring spatial periods even below 100 nm – far beyond the optical diffraction limit. However, the imposed surface functionalities are usually caused by both, topographic and chemical surface alterations. For exploring these effects in detail, multi-method characterization was performed here for HSFL processed on Ti-6Al-4V alloy upon irradiation with near-infrared ps-laser pulses (1030 nm wavelength, ~1 ps pulse duration, 1 – 400 kHz pulse repetition rate) under different scan processing conditions. The subsequent sample characterization involved morphological and topographical investigations by scanning electron microscopy (SEM), atomic force microscopy (AFM), stylus profilometry (SP), as well as near-surface chemical analyses by X-ray photoelectron spectroscopy (XPS), hard X-ray photoelectron spectroscopy (HAXPES) and depth-profiling time-of-flight secondary ion mass spectrometry (TOF-SIMS). The results allow to qualify the laser ablation depth, the geometrical HSFL characteristics and provide detailed insights into the depth extent and the nature of the ps-laser-induced near-surface oxidation arising from the laser-processing in ambient air and into the relevance of heat-accumulation effects at high pulse repetition rates. Moreover, the direct comparison of the HAXPES and XPS data reveals the role of surface-covering organic contaminants adsorbed from the ambient atmosphere without ion-sputter depth profiling. Furthermore, reduction of the oxides by sputtering can be avoided.
Per- and polyfluoroalkyl substances (PFAS) represent a class of synthetic organofluorine chemicals extensively utilized in the manufacturing of various materials such as firefighting foams, adhesives, and stain- and oil-resistant coatings. In recent years, PFAS have been considered as emerging environmental contaminants, with particular focus on perfluoroalkyl carboxylic acids (PFCAs), the most prevalent type among PFAS. PFCAs are characterized by a fully fluorinated carbon backbone and a charged carboxylic acid headgroup. Notably, they have been designated as Substances of Very High Concern and added to the REACH Candidate List due to their persistence in the environment, non-biodegradability and toxicological effects.
Conventional techniques for the analysis of PFCA, such as GC-MS, HRMS and HPLC-based methods, are laborious, not portable, costly and require skilled personnel. In contrast, fluorescence assays can be designed as easy-to-operate, portable and cost-effective methods with high sensitivity and fast response, especially when analyte binding leads to a specific increase of a probe’s emission. Integration of such probes with a carrier platform and a miniaturized optofluidic device affords a promising alternative for PFCA monitoring.
Here, a novel guanidine BODIPY fluorescent indicator monomer has been synthesized, characterized, and incorporated into a molecularly imprinted polymer (MIP) for the specific detection of perfluorooctanoic acid (PFOA). The MIP layer was formed on tris(bipyridine)ruthenium(II) chloride doped silica core particles for optical internal reference and calibration-free assays. Such system allows selective and reliable detection of PFCA from surface water samples, with minimum interference by competitors, matrix effects and other factors. Integration of the assay into an opto-microfluidic setup resulted in a miniaturized and easy-to-operate detection system allowing for micromolar detection of PFOA in less than 15 minutes from surface water sample.
Graphene and graphene-oxide (GO) are advanced materials which – similar to other graphene-related 2D materials (GR-2M) - are already used for instance in catalysis processes, biomedical applications, in inks and resins, or as composite materials for the aviation industry. The lateral/structural characterization of graphene oxide (GO) flakes is a challenging task, with steps like sample preparation, representative image selection and exact determination of the particle size distribution of well-defined size and shape descriptors being crucial for an accurate analysis. To ensure that safe-by-design principles are met within the various application fields, the commercial material must be thoroughly characterized and specified through well-known and standardized procedures.
GO flakes with different degrees of complexity were selected to assess the requirements for an accurate evaluation of their physico-chemical properties. These samples show inherent features with complex nanoscale characteristics such as porosity and edge roughness; further, the lateral size (quantified via equivalent circular diameter (ECD), minimum Feret and maximum Feret) of isolated and overlapping particles deposited on a substrate span over several orders of magnitude (nano to micron scale). The samples showed different degrees of agglomeration (and possible aggregation) with sizes ranging between submicron to a few tens of micrometers.
One focus is the automated segmentation and evaluation of images obtained by electron microscopy. The GO samples appear translucent with well-defined contrast between single and overlapping flakes both with the secondary electron detector of type InLens as well as with SEM in the transmission mode (STEM) utilizing a dedicated sample holder. To this end it is of utmost importance for the accurate image segmentation to carefully select thresholds both manually and through semi-automatic approaches using well-known threshold algorithms such as “IsoData” and pre-defined segmentation applications such as the ParticleSizer software package.
Further specific challenges in identifying and extracting key features of selected graphene oxide flakes are being discussed and approaches towards accurate and representative characterization are presented.
Im additiven Fertigungsprozess Laser-Pulverbettschweißen wird Metallpulver lagenweise mittels eines Lasers aufgeschmolzen, um Bauteile zu generieren. Hierbei werden die Eigenschaften der Bauteile zu einem großen Teil durch die im Verlauf des Prozesses vorliegenden Temperaturen bestimmt. Dies beinhaltet unter anderem Materialeigenschaften wie Mikrostruktur, Härte, thermische und elektrische Leitfähigkeiten sowie die Ausbildung von Defekten wie z.B. Anbindungsfehler, Keyhole-Porosität (Gaseinschlüsse) oder auch die Ausbildung von Rissen. Zur Überwachung bzw. Vorhersage dieser Eigenschaften sowie zum Abgleich von Simulationen ist eine orts- und zeitaufgelöste Messung der Temperaturverteilung im Prozess daher von herausragender Bedeutung. In der Industrie kommen optische Verfahren, die auf der Messung der thermischen Strahlung basieren, regelmäßig zum Einsatz. Allerdings dienen diese bislang nur der statistischen Auswertung und der Identifikation von Abweichungen vom Normalprozess. Der quantitativen Auswertung zur Temperaturbestimmung stehen aktuell noch eine Vielzahl von Herausforderungen entgegen. Einerseits stellt der Prozess an sich hohe Anforderungen an die Datenerfassung und -auswertung: der Emissionsgrad verändert sich dynamisch im Prozess und lokale Schmauchbildung sorgt für potenzielle Absorption oder Streuung der thermischen Strahlung oder auch des Fertigungslasers. Weiterhin stellt der hochdynamische Prozess hohe Anforderungen an Orts- und Zeitauflösung der eingesetzten Sensorik (z.B. Kameratechnik). Andererseits erschweren an üblichen kommerziell erhältlichen Fertigungsanlagen praktische Hindernisse wie eine eingeschränkte optische Zugänglichkeit und der fehlende Zugriff auf die Anlagensteuerung sowie fehlende Möglichkeiten der Synchronisation der Messtechnik mit dem Prozess eine eingehende Untersuchung dieser Effekte.
Um letztere Hindernisse zu umgehen, wurde an der BAM die Forschungsanlage SAMMIE (sensor-based additive manufacturing machine) entwickelt. Einerseits bietet das System alle Möglichkeiten, die auch übliche kommerzielle Systeme bieten. Dies beinhaltet die Fertigung ganzer Bauteile (maximale Größe ca. 65mm x 45 mm x 30 mm) und den Einsatz einer Inertgasatmosphäre inkl. gefiltertem Schutzgasstrom. Andererseits bietet es aber auch einen besonders kompakten Bauraum, um die Sensorik möglichst nah an den Prozess führen zu können, sechs optische Fenster zur Prozessbeobachtung aus unterschiedlichen Winkeln und die Möglichkeit der Prozessbeobachtung koaxial zum Fertigungslaser. Des Weiteren besteht eine einfache Austauschbarkeit aller Fenster, Spiegel und Strahlteiler, um den gesamten optischen Pfad der aktuellen Messaufgabe flexibel anzupassen. Die komplette Anlagensteuerung ist eine Eigenentwicklung und bietet daher auch völlige Anpassbarkeit. Eine synchrone und frei konfigurierbare Triggerung diverser Sensoriken und synchrone Datenerfassung bieten maximale Kontrolle über die Sensorsteuerung.
Dieser Beitrag gibt einen Überblick über die Fertigungsanlage SAMMIE. Wissenschaftliche Ergebnisse sowie laufende Arbeiten an der Anlage werden in weiteren Beiträgen vorgestellt.
Die metallische additive Fertigung hat in den letzten Jahren in der industriellen Fertigung zunehmend an Bedeutung gewonnen. Hierbei dominiert das Laser-Pulverbettschweißen von Metallen (PBF/LB-M) die Fertigung von kleinformatigen Bauteilen mit hoher Oberflächengüte. Die anspruchsvolle und kostspielige Qualitätssicherung stellt aber weiterhin ein Hindernis für eine breitere und kostengünstigere Anwendung der additiven Fertigung dar. Dies resultiert teilweise aus fehlenden zuverlässigen In-situ-Monitoringsystemen. Belastbarere Prozessüberwachungsdaten würden eine oft erforderliche teure nachgelagerte Prüfung mittels Computertomografie entbehrlich machen. Die Aufzeichnung der thermischen Signaturen des Aufbauprozess mittels Thermografie-Kameras zeigen hier vielversprechende Ergebnisse. Eine Korrelation zu auftretender Porosität, Delaminationen und Deformationen scheinen möglich. Die geringe räumliche Auflösung und die hohen Anschaffungskosten für thermografische Kamerasysteme stehen jedoch einer größeren industriellen Nutzung im Wege.
Ein bereits industriell angewendeter Ansatz zur in-Situ Überwachung des PBF-LB/M Prozesses ist die Optische Tomografie (OT). Hierbei wird die emittierte Prozessstrahlung jeder Bauteilschicht mittels einer hochauflösenden günstigen Kamera für den sichtbaren Wellenlängenbereich in einer Langzeitbelichtung dokumentiert. Die zeitliche Information der emittierten Strahlung geht hierbei verloren. Der gesamte Bauprozess kann jedoch in einem vergleichsweise kleinen Datensatz dokumentiert werden (ein Bild pro Schicht). Eine direkte Korrelation zu auftretenden Defekten gestaltet sich aufgrund der reduzierten thermischen Informationsdichte jedoch schwierig.
In diesem Beitrag soll deshalb das Prinzip der Multispektralen Optischen Tomografie (MOT) vorgestellt und erste Messergebnisse an der Forschungsanlage SAMMIE diskutiert werden. Bei der MOT handelt es sich um eine Übertragung des Prinzips der Quotientenpyrometrie auf das etablierte Verfahren der Optischen Tomografie. Die auftretende Prozessstrahlung wird in mehreren Wellenlängenbereichen ortsaufgelöst über die gesamte Bauplattform erfasst und zeitlich in einer Langzeitbelichtung integriert. Hierbei kommen günstige Kamerasysteme für den sichtbaren Wellenlängenbereich zum Einsatz.
Das erfasste Signal I jedes Bildpixels für jeden separat erfassten Wellenlängenbereich kann als Maß für das zeitliche Integral der spezifischen Ausstrahlung M des Schmelzbades in diesem Wellenlängenbereich gesehen werden. Nach dem Stefan-Boltzmann-Gesetz hängt die abgestrahlte thermische Leistung P eines idealen Schwarzen Körpers in der vierten Potenz von dessen absoluten Temperatur T ab. Wird nur, wie z.B. bei der klassischen OT angewendet, der nahinfrarote Wellenlängenbereich betrachtet, lässt sich mit dem Planck’schen Strahlungsgesetz sogar eine Proportionalität zur siebten Potenz der Temperatur zeigen. Deshalb liegt ein starker Einfluss der maximal auftretenden Oberflächentemperatur Tmax auf das erfasste Messsignal vor.
Das erfasste Signal I wird aber auch durch die spektrale Transmission τ der verwendeten optischen Komponenten des Kamera-Setups, z.B. Filter und Objektive, durch die spektrale Sensitivität S der verwendeten Kamera-Sensoren und den nur sehr schwer zu bestimmenden Emissionsgrad ε der emittierenden (flüssigen) Oberfläche beeinflusst.
In einer ersten Näherung wird das Schmelzbad hier als Graukörper, also ein Körper mit wellenlängenunabhängigem Emissionsgrad ε, betrachtet. Basierend auf dieser Annahme und vermessenen optischen Eigenschaften des verwendeten Systems ist es möglich, eine erste Schätzung der maximalen Oberflächentemperatur Tmax vorzunehmen, selbst ohne genaue Kenntnis des tatsächlichen Emissionsgrades ε. Dies wird durch die Anwendung des Planck‘schen Strahlungsgesetzes und die Quotienten Bildung aus den einzelnen erfassten Signalen I ermöglicht.
Auch bei diesem Verfahren geht die zeitliche Information einer Schicht, also das Aufwärm- und Abkühlverhalten des Schmelzbades, verloren. Zudem sind die Messergebnisse in Hinblick auf tatsächlich gemessene „maximal auftretende Oberflächentemperatur“ mit gebotener Zurückhaltung zu interpretieren. Trotzdem konnten erste Ergebnisse bereits zeigen, dass die MOT-Daten auch in Bereichen mit Doppelbelichtungen (das teilweise notwendige mehrfache Scannen eines Bereiches mittels des Fertigungslasers) im Gegensatz zur klassischen OT erwartbare Maximaltemperaturen liefern. Abbildung 1 zeigt das erfasste Messergebnis für drei aufeinanderfolgende Schichten eines Bauteils einmal mit MOT (links) und einmal mit einfacher OT (rechts). Deutlich zu erkennen ist das durch die doppelte Belichtung hohe Signal bei der OT. Die Daten der MOT zeigen hier keine erhöhten Werte.
Um die ermittelten Temperaturwerte mittels MOT besser einordnen zu können, sind u.a. vergleichende Messungen an Referenzmaterialien geplant. Um die Auswertung der gemessenen Daten zu verbessern, wird zudem der Zeitverlauf des Abkühlens und Aufheizens des Schmelzbades sowie die Einflüsse von Prozessbeiprodukten wie Schmauch und Spritzer näher untersucht. Auch werden Messungen zum Emissionsgrad ε an additiv gefertigten Proben und Metallschmelzen vorgenommen.
This study provides insights into the properties of 316L stainless steel produced by additive manufacturing using fused filament fabrication (FFF). One key finding is particularly noteworthy: in significant contrast to cold-rolled 316L, FFF316L develops a pronounced martensite phase after fabrication. The comprehensive comparative analysis shows that FFF316L not only retains the ferrite volume content, but that this is also significantly influenced by the build-up direction. Despite the sintering process, which typically involves densification of the material, a pore volume fraction of 8.45 % remains, which influences the mechanical properties. Although FFF316L has lower elastic
modulus and tensile strength values compared to cold-rolled 316L, its ductility is still competitive. The study further reveals that deformation-induced martensite forms at the intersections of the deformation twins and ferrite islands form at the grain boundaries during the compression and sintering phases. These findings highlight the challenges associated with FFF316L in specific application fields and signal the need to continue to carefully evaluate and improve the development of manufacturing technologies.
Guaranteeing safety and security of citizens requires a significant effort and innovative tools from national and international agencies and governments, especially when it comes to the field of explosives detection. The need to detect Improvised Explosive Devices (IEDs) and Home-made Explosives (HMEs) at a point of suspicion, has grown rapidly due to the ease with which the precursors can be obtained and the reagents synthesised. The limited availability of immunoanalytical tools for HME detection presents an opportunity for the development of new devices, which enable a rapid detection and recognise the target analyte with high specificity and sensitivity. In this work, we introduce an optical biosensor for highly specific and sensitive HME detection. The immunoassay system is placed in a hydrogel environment permeable to the analyte and transparent to light interrogating the fluorescently labelled antibodies. The readout of the immunoanalytical system is realized with Supercritical Angle Fluorescence (SAF), an advanced microscopy technique. To accomplish this, we made use of recent, commercial high resolution (< 22 µm) Liquid Crystal Display 3D printers to fabricate a parabolic optical element with high refractive index (RI>1.5) and transmission values (>90%) from photo-resin. Aiming at a new generation of sensors, which not only can meet the requirements of trace detection, but can also be used for substance identification, the combination of immunoanalytical recognition with SAF detection offers a modularity and versatility that is principally well suitable for the measurements of target analytes at trace levels.
ACCORDs is an Horizon Europe project working in the development of an imaging-based characterization framework (ACCORDs framework) for the holistic correlative assessment of Graphene Family Materials (GFMs) as a representative of 2D nanomaterials (NMs) to assess and predict 2D NMs health and environmental risks. The ACCORDs framework will operationalise safe and sustainable by design (SSbD) strategies proposed in past or ongoing H2020 projects or within OECD by correlating low-, medium-, and high-resolution physico-chemical-biological imaging-based methods with non-imaging methods in a tiered approach. ACCORDs will deliver the ACCORDs framework and user guidance, new imaging-based characterisation methods, reference in vitro tests, new reference 2D NMs for different matrices, a new minimum information reporting guideline for FAIR data sharing and reuse of images as well as an atlas with reference images for diagnostics of compromised safety of GFMs/GFM products. The new guidelines and standard proposals will be submitted to standardisation bodies to allow creation of regulatory ready products. The novelty of ACCORDs is in translating the principles of medical imaging-based diagnostics to 2D material hazard diagnostics. ACCORDs will accelerate industrial sectors in the area of aviation, marine construction, drone production, flexible electronics, photovoltaics, photocatalytics and print inks-based sensors. The value ACCORDs proposes to the graphene industry are practical, easy, imaging-based tools for GFM quality monitoring next to the production line with a possibility to be correlated with advanced highresolution imaging characterization methods in case hazard i.e. deviation from controls (benchmark values) are diagnosed. The ACCORDs framework and tools will contribute to the European Green Deal by addressing the topic: “Graphene: Europe in the lead” and to a new European strategy on standardization, released on 2nd February, 2022.
In der automatisierten Ultraschallprüfung von Komponenten mit komplexen Oberflächengeometrien werden zur Führung des Prüfkopfes zunehmend 6-Achsen-Roboter erprobt. Diese stellen die notwendige Automatisierbarkeit und Flexibilität bereit, um die lokal senkrechte Einschallung sicherzustellen. Durch den Einsatz von linearen Arrays und bildgebenden Verfahren können die Bilder oder die daraus extrahierten Merkmale zu einer Rekonstruktion in 3D zusammengesetzt werden. Die Anforderungen an die Prüfbahnen für die bildgebende Array-Ultraschallprüfung gehen dabei über konventionellen Bahnplanungsprogramme hinaus. Es wird ein Prozess vorgestellt, der Roboterbahnen auf der Grundlage des 3D-Modells von Körpern mit doppelt gekrümmter Oberfläche unter Berücksichtigung der Prüfparameter erzeugt. Hierbei wird zum einen die senkrechte Prüfkopfstellung und zum anderen eine optimale Abdeckung der Oberfläche realisiert. Dabei wird die lokale Oberflächengeometrie beachtet, da diese das Reflexionsverhalten beeinflusst und sich daher auf die optimale Verteilung und Orientierung der Prüfpositionen auswirkt. Damit einhergehend erfolgt eine Ablösung von konventionellen Konzepten, die auf linearen Prüfbahnen basieren, welches spannende neue Prüfstrategien eröffnet.
The stress–strain behavior of certain ceramics, such as aluminum titanate (AT, Al2TiO5), has features that are unusual for brittle material. In particular, a substantial nonlinearity under uniaxial tension, and load–unload hysteresis caused by the increase of the incremental stiffness at the beginning of unloading. These features are observed experimentally and attributed to microcracking. In this study, we investigate the mechanical response of an AT material at room and high temperature. Microstructure and microcracking are analyzed by means of electron microscopy, and both synchrotron micro computed tomography (µCT) and refraction radiography (SXRR). Synchrotron refraction radiography is combined with in-situ heating at high-temperatures (up to 1400°C) to be able to monitor the relative closure of microcracks as a function of increasing/decreasing temperatures.
Revealing surface functionalities of micro- and nanoplastic particles’ surface by means of XPS
(2024)
Over the last 20 years, many researchers, politicians, and citizens themselves have become increasingly aware of the growing plastic problem of our time. Inadequate recycling concepts, collection points, and careless dumping of plastic products in the environment lead to an accumulation of plastic. External weather influences can cause these to degrade and fractionate, so that today microplastics (1-1000 µm, ISO/TR 21960:2020) [1] of different polymer materials can be detected in all parts of the world.
The precautionary principle applies to microplastics. The particles can break down further to form nanoplastics (<1 µm, ISO/TR 21960:2020) [1]. Whether microplastics or nanoplastics pose a toxicological hazard is being investigated in a variety of ways. Valid results are still pending, however, investigations into the frequency, transport, possible sinks and entry paths must be taken into account. This is why monitoring of microplastics is already required in the revision of the Drinking Water Framework Directive [2]. The same is still pending in the final version of the revision of the Waste Water Framework Directive this year, but is expected.
Nanoplastics are particularly under discussion for having a toxic effect on humans and animals, as these particles are small enough to be absorbed by cells. For targeted toxicological studies, it is important to have test and reference materials that resemble the particles found in the environment. To mimic environmental samples, these materials should also have an irregular shape and show aging at the surface, which can be detected with XPS or SEM/EDS.
BAM in collaboration with the EMPIR project "PlasticTrace" works on a reference material candidate of nano-sized polypropylene (nano-PP) [3]. The nano-PP vials were tested for homogeneity with PTA and further characterized with bulk and surface-sensitive techniques. An SEM image and a corresponding XPS spectrum are presented in Figure 1. Raman measurements as well as XPS indicate an aged surface.
Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using laser-based powder bed fusion of metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up.
Microplastic and nanoplastic particles (MNP) are spread all over the world in various types, shapes and sizes making it very challenging to accurately analyse them. Each sampling procedure, sample preparation method and detection technique needs suitable reference materials to validate the method for accurate results. Furthermore, the effects of these MNPs should be evaluated by risk and hazard assessment with test particles close to reality. To better understand MNP behavior and aid in clarification of their interactions with organisms, we produced several MNP materials by top-down procedure and characterized their properties. Since surface properties mostly determine particles’ toxicity, the aim of the present study was to determine which functional groups are present on MNPs and how the surface can be affected by the production process and particle’s environment.
Metallbasierte additive Fertigungsverfahren werden zunehmend industriell zur Anfertigung von komplex geformten Komponenten eingesetzt. In diesem Zusammenhang ist das Laser-Pulverbettschweißen von Metall (PBF-LB/M) ist ein weitläufig genutztes Verfahren. Im PBF-LB/M-Prozess werden lagenweise aufgetragene Metallpulverschichten selektiv mittels eines Lasers aufgeschmolzen. Die Entstehung von internen Fehlstellen (bspw. Porosität, Lunker oder Risse) während des Fertigungsvorgangs stellt ein ernstzunehmendes Risiko für die Bauteilsicherheit und somit für die weitere industrielle Etablierung des Verfahrens dar. Die Entstehung von Fehlstellen hängt eng mit lokalen Änderungen der thermischen Historie des Bauteils zusammen. Mit Hilfe von thermografischen Kameras zur Prozessüberwachung kann die thermische Historie bereits während der Fertigung erfasst werden. Damit eröffnet sich die Möglichkeit, die Entstehung von Fehlstellen anhand der thermografischen Daten vorherzusagen und somit potenziell Kosten für eine nachgelagerte Qualitätssicherung einzusparen.
In diesem Beitrag soll die Modellierung der Fehlstellenvorhersage anhand thermografischer Prozessdaten diskutiert werden. Hierbei liegt ein Schwerpunkt auf der Fragestellung, mit welcher Genauigkeit unterschiedliche Formen von Fehlstellen, im speziellen Anbindungsfehler und Keyhole-Porosität, auf lokaler Bauteilebene vorhergesagt werden können. Weiterhin werden verschiedenen Modelltypen aus dem Bereich des Maschinellen Lernens auf ihre Eignung für die Fehlstellenvorhersage verglichen. Ein weiterer zentraler Aspekt in diesem Zusammenhang ist die Untersuchung der Eingangsdaten des Modells auf ihre Relevanz für das Vorhersageergebnis.
Als Datengrundlage für die durchgeführten Untersuchungen dienen die Fertigungsprozesse von zwei identischen Haynes-282-Bauteilen (Nickel-Basislegierung), welche mit Hilfe einer im kurzwelligen Infrarotbereich arbeitenden Thermografiekamera überwacht wurden. Das Bauteildesign umfasste lokale Bereiche, in denen mit Hilfe einer Parametervariation die Entstehung von Fehlstellen forciert wurde. Um die Position und Größe der entstandenen Defekte zu quantifizieren, wurden beide Bauteile nach erfolgter Fertigung mittels Computertomografie (CT) geprüft. Im Rahmen der Datenvorbereitung für die Modellierung erfolgte eine Reduzierung der erhobenen Thermogramme zu physikalisch-interpretierbaren Merkmalen (bspw. Schmelzbadfläche oder Zeit-über-Schwellwert). Weiterhin erfolgte eine Registrierung der thermografischen Daten mit den Fehlstellen-Referenzdaten der CT, um eine exakte örtliche Überlagerung von thermischer Information und lokalem Fehlstellenbild zu erzielen. Zur Ermöglichung einer lokalen Fehlstellenvorhersage wurden die thermografischen Daten schichtweise in kleinteiligen Volumina angeordnet, welche als Eingangsgröße für die genutzten ML-Algorithmen dienten.
Die Ergebnisse der Untersuchungen zeigen, dass sich die Porosität auf Bauteilschichtebene mit einer hohen Genauigkeit vorhersagen lässt. Eine Vorhersage der Porosität auf lokaler Bauteilebene erweist sich noch als herausfordernd. Die erprobten ML-Algorithmen zeigen vergleichbare Ergebnisse, obwohl ihnen unterschiedliche Modellierungsannahmen zugrunde liegen und sie variierende Komplexität aufweisen. Mit Hilfe der erzielten Erkenntnisse eröffnet sich die Möglichkeit, Rückschlüsse auf die gewählte Prozessüberwachungshardware und Datenvorverarbeitung zu ziehen und somit langfristig die Leistungsfähigkeit von Modellen zur Fehlstellenvorhersage zu verbessern.