Filtern
Dokumenttyp
- Zeitschriftenartikel (21)
- Vortrag (16)
- Beitrag zu einem Tagungsband (8)
- Forschungsdatensatz (3)
Schlagworte
Organisationseinheit der BAM
- 9 Komponentensicherheit (47)
- 8 Zerstörungsfreie Prüfung (31)
- 9.6 Additive Fertigung metallischer Komponenten (31)
- 8.0 Abteilungsleitung und andere (23)
- 8.5 Röntgenbildgebung (16)
- 9.3 Schweißtechnische Fertigungsverfahren (16)
- 5 Werkstofftechnik (13)
- 5.2 Metallische Hochtemperaturwerkstoffe (9)
- 5.1 Mikrostruktur Design und Degradation (8)
- 9.4 Integrität von Schweißverbindungen (5)
- 4 Material und Umwelt (2)
- 4.2 Material-Mikrobiom Wechselwirkungen (2)
- 8.3 Thermografische Verfahren (2)
- 1 Analytische Chemie; Referenzmaterialien (1)
- 1.6 Anorganische Referenzmaterialien (1)
- 5.0 Abteilungsleitung und andere (1)
- 5.4 Multimateriale Fertigungsprozesse (1)
- 5.5 Materialmodellierung (1)
- 8.4 Akustische und elektromagnetische Verfahren (1)
Laser Powder Bed Fusion (L-PBF) is a promising additive manufacturing (AM) technology for metal part production especially for complex and lightweight structures or functional designs. In L PBF processes several by-products including welding plume and its condensates, spatter and ejected powder are generated during laser exposure. Investigations of micro- and nano-sized by-products have received little attention in literature. This study focuses on the analysis of particle emissions in L PBF of 316L stainless steel using a scattered light aerosol spectrometer and a fast mobility particle sizer spectrometer during the process which allows for in-situ analysis of particle sizes in the range of 6 nm to 100 µm. A distinct correlation of emission signals to part position can be revealed. In addition, a significant influence of laser scanning vector directions on emission signals is presented. Furthermore, differing powder layer thicknesses can be recognised by deviations in emission signals.
Additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) are rapidly gaining popularity in repair applications. Gas turbine components benefit from the hybrid repair process as only damaged areas are removed using conventional machining and rebuilt using an AM process. However, hybrid repair is associated with several challenges such as component fixation and precise geometry detection. This article introduces a novel fixturing system, including a sealing concept to prevent powder sag during the repair process. Furthermore, a high-resolution camera within an industrial PBF-LB/M machine is installed and used for object detection and laser recognition. Herein, process related inaccuracies such as PBF-LB/M laser drift is considered by detection of reference objects. This development is demonstrated by the repair of a representative gas turbine blade. The final offset between AM build-up and component is analysed. An approximate accuracy of 160 μm is achieved with the current setup.
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.
Laser powder bed fusion (L-PBF) is one of the most promising additive manufacturing (AM) technologies for the production of complex metallic real part components. Due to the multitude of factors influencing process conditions and part quality and due to the layer-wise characteristic of the process, monitoring of process signatures seems to be mandatory in case of the production of safety critical components. Here, the iterative process nature enables unique access for in-situ monitoring during part manufacture. In this talk, the successful test of the synchronous use of a high-frequency infrared camera and a camera for long time exposure, working in the visible spectrum (VIS) and equipped with a near infrared filter (NIR), will be introduced as a machine manufacturer independent thermal detection monitoring set-up. Thereby, the synchronous use of an infrared camera and a VIS NIR camera combines the advantages of high framerate and high spatial resolution. The manufacture of a 316L stainless steel specimen, containing purposely seeded defects and volumes with forced changes of energy inputs, was monitored during the build. The measured thermal responses are analysed and compared with a defect mapping obtained by micro X-ray computed tomography (CT).
The first results regarding methods for data analysis, derived correlations between measured signals and detected defects as well as sources of possible data misinterpretation are presented in this talk.
One of the main advantages of additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) is the possibility to manufacture complex near-net-shape components. Therefore, the PBF-LB/M process is becoming increasingly important for the manufacturing and repair of gas turbine blades. Despite the great freedom in design, there are also limitations to the process. Manufacturing overhangs or bridging voids are some of the main challenges. In the conventional PBF-LB/M process, overhangs with angles up to 45° can be manufactured. However, gas turbine blades feature voids for cooling, which have to be bridged when using PBF-LB/M. In this work, different concepts for bridging voids are developed for future application in gas turbine blade repair. For this purpose, a test geometry is derived from the tip area of a gas turbine blade as a reference. By changing the initial geometry of the reference body, different designs for bridging voids are developed based on the PBF-LB/M requirements. Subsequently, these distinct designs are manufactured by PBF-LB/M. The different approaches are compared with respect to their volume increase. In addition, the specimens are visually inspected for warpage, shrinkage and imperfections by overheating. Out of the seven concepts developed, three concepts can be recommended for gas turbine blade repair based on low volume increase, distortion and shrinkage.
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.
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.
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.
Laser Powder Bed Fusion (L-PBF) is a promising additive manufacturing (AM) technology for metal part production especially for complex and lightweight structures or functional designs. In L PBF processes several by-products including welding plume and its condensates, spatter and ejected powder are generated during laser exposure. Investigations of micro- and nano-sized by-products have received little attention in literature. This study focuses on the analysis of particle emissions in L PBF of 316L stainless steel using a scattered light aerosol spectrometer and a fast mobility particle sizer spectrometer during the process which allows for in-situ analysis of particle sizes in the range of 6 nm to 100 µm. A distinct correlation of emission signals to part position can be revealed. In addition, a significant influence of laser scanning vector directions on emission signals is presented. Furthermore, differing powder layer thicknesses can be recognised by deviations in emission signals.
As humanity contemplates manned missions to Mars, strategies need to be developed for the design and operation of hospitable environments to safely work in space for years. The supply of spare parts for repair and replacement of lost equipment will be one key need, but in-space manufacturing remains the only option for a timely supply. With high flexibility in design and the ability to manufacture ready-to-use components directly from a computeraided model, additive manufacturing (AM) technologies appear extremely attractive. For the manufacturing of metal parts, laser-beam melting is the most widely used AM process. However, the handling of metal powders in the absence of gravity is one prerequisite for its successful application in space. A gas flow throughout the powder bed is successfully applied to compensate for missing gravitational forces in microgravity experiments. This so-called gas-flow-assisted powder deposition is based on a porous Building platform acting as a filter for the fixation of metal particles in a gas flow driven by a pressure difference maintained by a vacuum pump.