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In manufacturing, fusion welding processes use a lot of resources, which presents an opportunity to reduce environmental impact. While there is a general understanding of the environmental impact of these processes, it is difficult to quantitatively assess key parameters. This study introduces a welding-specific methodology that uses life cycle assessment (LCA) to evaluate the environmental impact of fusion welding technologies. Our approach analyses the main parameters that affect the environmental performance of different welding techniques, including traditional methods and additive manufacturing through the Direct Energy Deposition-Arc (DED-Arc) process. We integrate real-time resource usage data to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact, facilitating the advancement of sustainable manufacturing practices.
Life cycle assessment of fusion welding processes considering upstream and downstream process steps
(2023)
In manufacturing, fusion welding processes consume significant resources, presenting a significant opportunity for reducing environmental impact. Although there is a qualitative understanding of the environmental implications of these processes, a quantitative assessment of key parameters remains complex. This study introduces a welding-specific methodology that employs life cycle assessment (LCA) to quantitatively evaluate the environmental footprint of fusion welding technologies. Our approach identifies and analyses the principal parameters affecting the environmental performance of various welding techniques, including traditional joint welding and additive manufacturing via the Direct Energy Deposition-Arc (DED-Arc) process. Real-time resource usage data is integrated to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact. This facilitates the advancement of sustainable manufacturing practices.
New developments in nickel-based superalloys and production methods, such as the use of additive manufacturing (AM), can result in innovative designs for turbines. It is crucial to understand how the material behaves during the AM process to advance industrial use of these techniques. An analytical model based on reaction-diffusion formalism is developed to better explain the solidification behavior of the material during laser metal deposition (LMD). The well-known Scheil-Gulliver theory has some drawbacks, such as the assumption of equilibrium at the solid-liquid interface, which is addressed by this method. The solidified fractions under the Scheil model and the pure equilibrium model are calculated using CALPHAD simulations. Differential scanning calorimeter is used to measure the heat flow during the solid-liquid phase transformation, the result of which is further converted to solidified fractions. The analytical model is compared with all the other models for validation.
Additive manufacturing (AM) has revolutionized the manufacturing industry, offering a new paradigm to produce complex geometries and parts with customized properties. Among the different AM techniques, the wire arc additive manufacturing (WAAM) process has gained significant attention due to its high deposition rate and low equipment cost. However, the process is characterized by a complex thermal history, dynamic metallurgy, and mechanical behaviour that make it challenging to simulate it in real-time for online process control and optimization.
In this context, a reduced order model (ROM) using the proper generalized decomposition (PGD) method is proposed as a powerful tool to overcome the limitations of conventional numerical methods and enable the real-time simulation of the temperature field of WAAM processes. Though, the simulation of a moving heat source leads to a hardly separable parametric problem, which is handled by applying a novel mapping approach. Using this procedure, it is possible to create a simple separated representation of the model, also allowing to simulate multiple layers.
In this contribution, a PGD model is derived for the WAAM procedure simulating the temperature field. A good agreement with a standard finite element method is shown. The reduced model is further used in a stochastic model parameter estimation using Bayesian inference, speeding up calibrations and ultimately leading to a calibrated real-time simulation.
With additive manufacturing in the powder bed, the component size is limited by the installation space. Joint welding of additively manufactured parts offers a possibility to remove this size limitation. However, due to the specific stress and microstructure state in the additively built material, it is unclear to what extent existing evaluation rules of joint welding are also suitable for welds on additive components. This is investigated using laser beam welding of additively manufactured pipe joints. The welds are evaluated by means of visual inspection, metallographic examinations as well as computed tomography. The types of defects found are comparable to conventional components. This is an indicator that existing evaluation regulations also map the possible defects occurring for weld seams on additive components.
Creep and fracture behavior of conventionally and additively manufactured stainless steel 316L
(2020)
A critical task within the frame of establishing process-structure-property-performance relationships in additive manufacturing (AM) of metals is producing reliable and well-documented material behavior’s data and knowledge regarding the structure-property correlation, including the role of defects. After all, it represents the basis for developing more targeted process optimizations and more reliable predictions of performance in the future. Within this context, this contribution aims to close the actual gap of limited historical data and knowledge concerning the creep behavior of the widely used austenitic stainless steel 316L, manufactured by Laser-Powder-Bed-Fusion (L-PBF). To address this objective, specimens from conventional hot-rolled and AM material were tested under application-relevant conditions according to existing standards for conventional material, and microstructurally characterized before and after failure. The test specimens were machined from single blocks from the AM material. The blocks were manufactured using a standard scan and build-up strategy and were subsequently heat-treated. The creep behavior is described and comparatively assessed based on the creep lifetime and selected creep curves and characteristic values. The effect of defects and microstructure on the material’s behavior is analyzed based on destructive and non-destructive evaluations on selected specimens. The AM material shows shorter creep lives, reaches the secondary creep stage much faster and at a lower strain, and features lower creep ductility compared to its conventional counterpart. The creep damage behavior of the AM material is more microstructure than defect controlled and is characterized by the formation and accumulation of single intergranular damage along the whole volume. Critical features identified are the grain morphology and the grain-boundary as well as the dislocation’s density. Micro-computed tomography (µCT) proves to be an alternative to metallography to analyze the creep damage.
Rapid cooling rates and steep temperature gradients are characteristic of additively manufactured parts and important factors for the residual stress formation. This study examined the influence of heat accumulation on the distribution of residual stress in two prisms produced by Laser Powder Bed Fusion (LPBF) of austenitic stainless steel 316L. The layers of the prisms were exposed using two different border fill scan strategies: one scanned from the centre to the perimeter and the other from the perimeter to the centre. The goal was to reveal the effect of different heat inputs on samples featuring the same solidification shrinkage. Residual stress was characterised in one plane perpendicular to the building direction at the mid height using Neutron and Lab X-ray diffraction. Thermography data obtained during the build process were analysed in order to correlate the cooling rates and apparent surface temperatures with the residual stress results. Optical microscopy and micro computed tomography were used to correlate defect populations with the residual stress distribution. The two scanning strategies led to residual stress distributions that were typical for additively manufactured components: compressive stresses in the bulk and tensile stresses at the surface. However, due to the different heat accumulation, the maximum residual stress levels differed. We concluded that solidification shrinkage plays a major role in determining the shape of the residual stress distribution, while the temperature gradient mechanism appears to determine the magnitude of peak residual stresses.
Directed energy deposition is a metal additive manufacturing process that builds parts by joining material in a layer-by-layer fashion on a substrate. Those parts are exposed to rapid thermo-cycles which cause steep stress gradients and the layer-upon-layer manufacturing fosters an anisotropic microstructure, therefore stress relief heat treatment is necessary. The numerical simulation can be used to find suitable parameters for the heat treatment and to reduce the necessary efforts to perform an effective stress relieving. Suitable validation Experiments are necessary to verify the results of the numerical simulation.
In this paper, a 3D coupled thermo-mechanical model is used to simulate the heat treatment of an additive manufactured component to investigate the application of a C-ring geometry for the distortion-based validation of the numerical simulation.
Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to quantify the distortion after each process step.
The understanding of process-microstructure-property-performance (PMPP) relationships in additive manufacturing (AM) of metals is highly necessary to achieve wide-spread industrial application and replace conventionally manufactured parts, especially regarding safety-relevant applications. To achieve this understanding, reliable data and knowledge regarding material’s microstructure-property relationships (e.g. the role of defects) is needed, since it represents the base for future more targeted process optimizations and more reliable calculations of performance. However, producing reliable material data and assessing the AM material behaviour is not an easy task: big challenges are e.g. the actual lack of standard testing methods for AM materials and the occasional difficulties in finding one-to-one comparable material data for the conventional counterpart.
This work aims to contribute to end this lack of reliable material data and knowledge for the low cycle fatigue behaviour of the most used titanium alloy in aerospace applications (Ti-6Al-4V). For this purpose, two sets of test specimens were investigated. The first set was manufactured from cylindrical rods produced by an optimized DED-L process and the second was manufactured from a hot formed round bar. The test specimens were cyclically loaded until failure in the low-cycle-fatigue (LCF) regime. The tests were carried out according to ISO 12106 between 0.3 to 1.0 % axial strain amplitude from room temperature up to 400°C. The LCF behaviour is described and compared between materials and with literature values based on cyclic deformation curves and strain-based fatigue life curves. Besides, the parameters of Manson-Coffin-Basquin relationship were calculated. The microstructures (initial and after failure) and fracture surfaces were comparative characterized. Thereby, the focus lied on understanding the role of grain morphology and defects on the failure mechanisms and fatigue lifetimes. For this latter characterization, optical microscopy (OM), scanning electron microscopy (SEM) and micro computed tomography (µCT) were used.