5 Werkstofftechnik
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- 3D imaging (1)
- 5G (1)
- Additive Manufacturing (1)
- Atomization (1)
- Co-axial monitoring (1)
- Destabilization (1)
- LTCC multilayer (1)
- Laser Beam Melting (1)
- Machine Learning (1)
- Metrology (1)
- Nanoparticles (1)
- Process Monitoring (1)
- Slurry (1)
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Organisationseinheit der BAM
- 5.4 Multimateriale Fertigungsprozesse (5) (entfernen)
Quality Aspects of Additively Manufactured Medical Implants - Defect Detection in Lattice Parts
(2019)
Additive Manufacturing technologies are developing fast to enable a rapid and flexible production of parts. Tailoring products to individual needs is a big advantage of this technology, which makes it of special interest for the medical device industry and the direct manufacturing of final products. Due to the fast development, standards to assure reliability of the AM process and quality of the printed products are often lacking. The EU project Metrology for Additively Manufactured Medical Implants (MetAMMI) is aiming to fill this gap by investigating alternative and cost efficient non-destructive measurement methods.
Considerations for nanomaterial identification of powders using volume-specific surface area method
(2019)
The EC’s recommendation for a definition of nanomaterial (2011/696/EU) should allow the identification of a particulate nanomaterial based on the number-based metric criterion according to which at least 50% of the constituent particles have the smallest dimension between 1 and 100 nm. However, it has been recently demonstrated that the implementation of this definition for regulatory purposes is conditioned by the large deviations between the results obtained by different sizing methods or due to practical reasons such as high costs and time-consuming.
For most measurement methods for particle size determination it is necessary to initially disperse the particles in a suitable liquid. However, as the particle size decreases, the adhesion forces increase strongly, making it more difficult to deagglomerate the particles and to assess accurately the result of this process. Therefore, the success of the deagglomeration process substantially determines the measurement uncertainty and hence, the comparability between different methods.
Many common methods such as dynamic light scattering (DLS), centrifugal liquid sedimentation (CLS) or ultrasound attenuation spectroscopy (US) can give good comparable results for the size of nanoparticles, if they are properly separated and stabilized (e.g. in reference suspensions).
In order to avoid the use of hardly available and expensive methods such as SEM / TEM for all powders, an agglomeration-tolerant screening method is useful.
One of the measurement methods well suited to probe the size of particulate powder is the determination of the volume-specific surface area (VSSA) by means of gas adsorption as well as skeletal density. The value of 60 m2/cm3 corresponding to spherical, monodisperse particles with a diameter of 100 nm constitutes the threshold for decisioning if the material is a nano- or non-nanomaterial. The identification of a nanomaterial by VSSA method is accepted by the EU recommendation.
However, the application of the VSSA method was associated also with some limitations. The threshold of 60 m2/cm3 is dependent on the particle shape, so that it changes considerably with the number of nano-dimensions, but also with the degree of sphericity of the particles. For particles containing micro-pores or having a microporous coating, false positive results are induced. Furthermore, broad particle size distributions made necessary to additionally correct the threshold. Based on examples of commercially available ceramic powders, the applicability of the VSSA approach was tested in relation with SEM and TEM measurements. The introduction of a correction term for deviations from sphericity and further additions improved the applicability of VSSA as a screening method.
Homogeneous introduction of organic additives is a key of ceramic powder processing. Addition of organics to ceramic slurries holds advantages compared to dry processing like organic content reduction and a more homogeneous additive distribution on the particle surface.
Investigations of the alumina slurries were primarily based on zeta potential measurements and sedimentation analysis by optical centrifugation. Both methods were combined to determine a suitable additive type, amount and composition, whereas the spray drying suitability has been ensured by viscosity measurements. Granules, yielded by spray drying of such ideally dispersed alumina slurries, are mostly hollow and possess a hard shell. Those granules cannot easily be processed and can only hardly be destroyed in the following shaping step, leading to sinter bodies with many defects and poor strength and density.
The precise slurry destabilization, carried out after ideally dispersing the ceramic powder, shows a strong influence on the drying behavior of the granules and hence on the granule properties. A promising degree of destabilization and partial flocculation was quantified by optical centrifugation and resulted in improved granule properties. Spray drying the destabilized alumina slurries yielded homogeneous “non-hollow” granules without the above mentioned hard shell. Sample bodies produced of these granules exhibited a reduction of defect size and number, leading to better results for sinter body density and strength.
The positive effect of the slurry destabilization has been further improved, by exchanging the atomizing unit from a two-fluid one to an ultrasound atomizer with only minor slurry adjustments necessary. The controlled destabilization and ultrasound atomization of the ceramic slurry show excellent transferability for zirconia and even ZTA (zirconia toughened alumina) composite 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.
Within the perspective of increasing reliability of AM processes, real-time monitoring allows part inspection while it is built and simultaneous defect detection. Further developments of real-time monitoring can also bring to self-regulating process controls. Key points to reach such a goal are the extensive research and knowledge of correlations between sensor signals and their causes in the process.