5.4 Multimateriale Fertigungsprozesse
Filtern
Dokumenttyp
- Zeitschriftenartikel (6)
- Vortrag (5)
- Posterpräsentation (4)
Schlagworte
- Gassensorik (3)
- H2Safety@BAM (3)
- Zerstörungsfreie Prüfung (3)
- 3D printing (2)
- Additive Manufacturing (2)
- Additive manufacturing (2)
- Faseroptische Sensorik (2)
- Geführte Ultraschallwellen (2)
- LTCC (2)
- Leckdetektion (2)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (15) (entfernen)
Paper des Monats
- ja (1)
Eingeladener Vortrag
- nein (5)
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.
Additive manufacturing (AM) is developing rapidly due to itsflexibility in producing complex geometries and tailored material compositions. However, AM processes are characterized by intrinsic limitations concerning their resolution and surface finish, which are related to the layer-by-layer stacking process. Herein, a self-organization process is promoted as an approach to improve surface quality and achieve optimization of 3D minimal surface lightweight structures. The self-organization is activated after the powder bed 3D printing process via local melting, thereby allowing surface tension-driven viscous flow.The surface roughness Ra (arithmetic average of the roughness profile) could bedecreased by a factor of 1000 and transparent lenses and complex gyroid structures could be produced for demonstration. The concept of self-organization is further elaborated by incorporating external magnetic fields to intentionally manipulate magnetic particles, which are mixed with the polymer before printing and self-organization. This concept can be applied to develop programmable materials with specific microtextures responding to the external physical conditions.
LTCCs (Low-temperature co-fired ceramics) consist of three-dimensionally distributed, hermetically bonded ceramic and metallic components with structure sizes within [10; 100] µm. A non-destructive imaging technique is needed that provides 3D, sharp, high-contrast resolution of these structures, as well as porosity and defect analysis, which is made difficult by the very different X-ray absorption coefficients of the individual components of the microstructure. A HDR method is being developed that allows a combination of different tomograms, each with X-ray energies adapted to individual materials.
The introduction of the 5G technology and automotive radar applications moving into higher frequency ranges trigger further miniaturization of LTCC technology (low temperature co-fired ceramics). To assess dimensional tolerances of inner metal structures of an industrially produced LTCC multilayer, computer tomography (CT) scans were evaluated by machine learning segmentation.
The tested multilayer consists of several layers of a glass ceramic substrate with low resistance silver-based vertical interconnect access (VIA). The VIAs are punched into the LTCC green tape and then filled with silver-based pastes before stacking and sintering. These geometries must abide by strict tolerance requirements to ensure the high frequency properties.
This poster presents a method to extract shape and size specific data from these VIAs. For this purpose, 4 measurements, each containing 3 to 4 samples, were segmented using the trainable WEKA segmentation, a non-commercial machine learning tool. The dimensional stability of the VIA can be evaluated regarding the edge-displacement as well as the cross-sectional area. Deviation from the ideal tubular shape is best measured by aspect ratio of each individual layer. The herein described method allows for a fast and semi-automatic analysis of considerable amount of structural data. This data can then be quantified by shape descriptors to illustrate 3-dimensional information in a concise manner. Inter alia, a 45 % periodical change of cross-sectional area is demonstrated.
The effect of particle grain sizes in different cement-based mixtures on the laser-induced plasma evolution is studied using two experimental methods: (i) temporal and spatial evolution of the laser-induced shock wave is investigated using shadowgraphy and two-dimensional plasma imaging, and (ii) temporal and spatial distribution of elements in the plasma is investigated using two-dimensional spectral imaging. This study is motivated by the interest in applying laser-induced breakdown spectroscopy (LIBS) for chemical analysis of concrete, and subsequently obtain information related to damage assessment of structures like bridges and parking decks. The distribution of grain sizes is of major interest in civil engineering as for making concrete different aggregate grain sizes defined by a sieving curve (64mm to 0.125 mm) are needed. Aggregates up to a size of 180 μm can be excluded from the data set, therefore only the amount of small aggregates with a grain size below 180 μm must be considered with LIBS. All components of the concrete with a grain size smaller than 0.125mm are related to the flour grain content. Tested samples consisted of dry and hardened cement paste (water-cement ratio w/z=0.5), which served as a reference. Aggregate mixtures were made by adding flour grains (size 40 μm) and silica fume (size 0.1 μm) in different ratios to cement: 10%, 30%, 50% and 60%, all combined to the remaining percentage of dry or hydrated cement. The visualization results show that a dependance in the evolution of the plasma as a function of sample grain size can be detected only in the initial stages of the plasma formation, that is, at the initial 3 μs of the plasma life. Spectral information reveals the elemental distribution of the silicon and calcium in plasma, in both neutral and ionized form. Here also, a significant effect is observed in the first 1 μs of the plasma lifetime.
The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the equipment, data handling pipeline as well as various examples from material science are presented.
The 5G technology promises real time data transmission for industrial processes, autonomous driving, virtual and augmented reality, E-health applications and many more. The Low Temperature Co-fired Ceramics (LTCC) technology is well suited for the manufacturing of microelectronic components for such applications. Still, improvement of the technology such as further miniaturization is required. This study focuses on the characterization of inner metallization of LTCC multilayer modules, especially on the vertical interconnect access (VIA). Critical considerations for this characterization are delamination, pore clustering in and at the edge of the VIA, deformation, and stacking offset. A LTCC multilayer consisting of a glassy crystalline matrix with silver based VIAs was investigated by synchrotron x-ray tomography (CT). The aim of this study is to propose a multitude of structural characteristic values to maximize the information gained from the available dataset. Data analysis has been done with the open source software ImageJ as well as several additional plugins. The high-resolution CT data was evaluated through 2D slices for accessibility reasons. The segmentation of all 2000 slices to assess the different regions e.g. pores, silver and glass ceramic was done by a supervised machine learning algorithm. A quantitative evaluation of shape, deformation, and porosity of the VIA with respect to its dimensions is presented and the suitability of the characterization approach is assessed.
Frass (fine powdery refuse or fragile perforated wood produced by the activity of boring insects) of larvae of the European house borer (EHB) and of drywood termites was tested as a natural and novel feedstock for 3D-printing of wood-based materials. Small particles produced by the drywood termite Incisitermes marginipennis and the EHB Hylotrupes bajulus during feeding in construction timber, were used. Frass is a powdery material of particularly consistent quality that is essentially biologically processed wood mixed with debris of wood and faeces. The filigree-like particles flow easily permitting the build-up of woodbased structures in a layer wise fashion using the Binder Jetting printing process. The Quality of powders produced by different insect species was compared along with the processing steps and properties of the printed parts. Drywood termite frass with a Hausner Ratio HR = 1.1 with ρBulk = 0.67 g/cm3 and ρTap = 0.74 g/cm3 was perfectly suited to deposition of uniformly packed layers in 3D printing. We suggest that a variety of naturally available feedstocks could be used in environmentally responsible approaches to scientific material sciences/additive manufacturing.