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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.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Additive manufacturing methods such as laser powder bed fusion (LPBF) allow geometrically complex parts to be manufactured within a single step. However, as an aftereffect of the localized heat input, the rapid cooling rates are the origin of the large residual stress (RS) retained in as-manufactured parts. With a view on the microstructure, the rapid directional cooling leads to a cellular solidification mode which is accompanied by columnar grown grains possessing crystallographic texture. The solidification conditions can be controlled by the processing parameters and the scanning strategy. Thus, the process allows one to tailor the microstructure and the texture to the specific needs. Yet, such microstructures are not only the origin of the mechanical anisotropy but also pose metrological challenges for the diffraction-based RS determination. In that context the micromechanical elastic anisotropy plays an important role: it translates the measured microscopic strain to macroscopic stress. Therefore, it is of uttermost importance to understand the influence of the hierarchical microstructures and the texture on the elastic anisotropy of LPBF manufactured materials.
This study reveals the influence of the build orientation and the texture on the micro-mechanical anisotropy of as-built Inconel 718. Through variations of the build orientation and the scanning strategy, we manufactured specimens possessing [001]/[011]-, [001]-, and [011]/[111]-type textures. The resulting microstructures lead to differences in the macroscopic mechanical properties. Even further, tensile in-situ loading experiments during neutron diffraction measurements along the different texture components revealed differences in the microstrain response of multiple crystal lattice planes. In particular, the load partitioning and the residual strain accumulation among the [011]/[111] textured specimen displayed distinct differences measured up to a macroscopic strain of 10 %. However, the behavior of the specimens possessing [001]/[011]-and [001]-type texture was only minorly affected. The consequences on the metrology of RS analysis by diffraction-based methods are discussed.
The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, with associated potential gains in performance and efficiency. However, high magnitude residual stresses (RS) are often a product of the rapid thermal cycles typical of the layerwise process. Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterisation of these RS is essential for safety related engineering application and supports the development of reliable numerical models. Diffraction-based methods for RS analysis using neutrons and high energy X-rays enable non-destructive spatially resolved characterisation of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys as a function of process parameters. In addition, the challenges posed by the textured and hierarchical microstructures of LPBF materials on diffraction-based RS analysis in AM materials will be discussed. This will include the question of the d0 reference lattice spacing and the appropriate choice of the diffraction elastic constants (DECs) to calculate the level of RS in LPBF manufactured alloys.
Laser powder bed fusion (LPBF) is an additive manufacturing process for materials which inherently tends to yield various degrees of metastable hierarchical microstructures, defects and high residual stresses in the as-built condition depending on the process parameters. The understanding of the evolution of these typical features during heat treatment and subsequent thermal and mechanical ageing is crucial for the wider acceptance for safety critical structures. A multi-disciplinary research project at BAM studying the development of the microstructure, defects, residual stresses typical of LPBF 316L and their evolution during thermal and mechanical ageing has led to insights into the stability of these inherent features. This presentation aims to give a broad overview of the project with a few specific cases of investigation. Firstly, the formation of residual stresses, the nature of the initial microstructure, the tensile properties and a modelling approach to understand the anisotropy will be presented. This will be followed by examples of studies of their evolution during heat treatment, long term thermal exposure, and room temperature and high temperature mechanical testing compared to a baseline of conventional wrought variant of the same alloy.
Introduction to AGIL
(2021)
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of complex structures. The quality of the feedstock material receives increasing attention, as it depicts the first part of the L-PBF process chain. The powder quality control in terms of flowability and powder bed packing density is therefore mandatory.
In this work, a workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape for three different powder batches. The polydisperse particle size distribution (PSD) was transformed into a statistically equivalent bidisperse PSD. The ratio of the small and large particles helped to understand the powder particle packing density. While the particle shape had a neglectable influence, the particle size distribution was identified as major contributor for the packing density.
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.