scholarly journals Porosity in Wire Arc Additive Manufacturing of Aluminium Alloys

2021 ◽  
pp. 101993
Author(s):  
Tobias Hauser ◽  
Raven T. Reisch ◽  
Philipp P. Breese ◽  
Benjamin S. Lutz ◽  
Matteo Pantano ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Aluminium Alloys ◽  
Wire Arc Additive Manufacturing

scholarly journals Multi-Material Wire Arc Additive Manufacturing of low and high alloyed aluminium alloys with in-situ material analysis

2021 ◽  
Vol 69 ◽  
pp. 378-390
Author(s):  
Tobias Hauser ◽  
Raven T. Reisch ◽  
Stefan Seebauer ◽  
Aashirwad Parasar ◽  
Tobias Kamps ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Aluminium Alloys ◽  
Material Analysis ◽  
Wire Arc Additive Manufacturing ◽  
Alloyed Aluminium

scholarly journals Wire arc additive manufacturing of AA5183 with TiC nanoparticles

2021 ◽  
Author(s):  
Geir Langelandsvik ◽  
Magnus Eriksson ◽  
Odd M. Akselsen ◽  
Hans J. Roven
Keyword(s):  
Additive Manufacturing ◽  
Grain Refinement ◽  
Aluminium Alloys ◽  
The Novel ◽  
Grain Refiner ◽  
Screw Extrusion ◽  
Coarse Microstructure ◽  
Tic Nanoparticles ◽  
Wire Arc Additive Manufacturing ◽  
Extrusion Method

AbstractAluminium alloys processed by wire arc additive manufacturing (WAAM) exhibit a relatively coarse microstructure with a columnar morphology. A powerful measure to refine the microstructure and to enhance mechanical properties is to promote grain refinement during solidification. Addition of ceramic nanoparticles has shown great potential as grain refiner and strengthening phase in aluminium alloys. Thus, an Al-Mg alloy mixed with TiC nanoparticles was manufactured by the novel metal screw extrusion method to a wire and subsequently deposited by WAAM. Measures to restrict oxidation of magnesium during metal screw extrusion were examined. Purging of CO2 gas into the extrusion chamber resulted in a remarkable reduction in formation of MgO and Mg(OH)2. TiC decomposed to Al3Ti during WAAM deposition, leading to a significant grain refinement of 93% compared to a commercial benchmark. The presence of remaining TiC nanoparticles accounted for an increased hardness of the WAAM material through thermal expansion mismatch strengthening and Orowan strengthening. Exposure of TiC to moisture in air during metal screw extrusion increased the internal hydrogen content significantly, and a highly porous structure was seen after WAAM deposition.

scholarly journals Oxidation in wire arc additive manufacturing of aluminium alloys

2021 ◽  
Vol 41 ◽  
pp. 101958
Author(s):  
Tobias Hauser ◽  
Raven T. Reisch ◽  
Philipp P. Breese ◽  
Yogesh Nalam ◽  
Kaivalya S. Joshi ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Aluminium Alloys ◽  
Wire Arc Additive Manufacturing

scholarly journals Geometry and Distortion Prediction of Multiple Layers for Wire Arc Additive Manufacturing with Artificial Neural Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4694
Author(s):  
Christian Wacker ◽  
Markus Köhler ◽  
Martin David ◽  
Franziska Aschersleben ◽  
Felix Gabriel ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Welding Process ◽  
High Energy ◽  
Welding Distortion ◽  
Direct Energy Deposition ◽  
Direct Energy ◽  
Industrial Use ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Wire Arc Additive Manufacturing

Wire arc additive manufacturing (WAAM) is a direct energy deposition (DED) process with high deposition rates, but deformation and distortion can occur due to the high energy input and resulting strains. Despite great efforts, the prediction of distortion and resulting geometry in additive manufacturing processes using WAAM remains challenging. In this work, an artificial neural network (ANN) is established to predict welding distortion and geometric accuracy for multilayer WAAM structures. For demonstration purposes, the ANN creation process is presented on a smaller scale for multilayer beads on plate welds on a thin substrate sheet. Multiple concepts for the creation of ANNs and the handling of outliers are developed, implemented, and compared. Good results have been achieved by applying an enhanced ANN using deformation and geometry from the previously deposited layer. With further adaptions to this method, a prediction of additive welded structures, geometries, and shapes in defined segments is conceivable, which would enable a multitude of applications for ANNs in the WAAM-Process, especially for applications closer to industrial use cases. It would be feasible to use them as preparatory measures for multi-segmented structures as well as an application during the welding process to continuously adapt parameters for a higher resulting component quality.

Control of humping phenomenon and analyzing mechanical properties of Al–Si wire-arc additive manufacturing fabricated samples using cold metal transfer process

2021 ◽  
pp. 095440622199840
Author(s):  
Yashwant Koli ◽  
N Yuvaraj ◽  
Aravindan Sivanandam ◽  
Vipin
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Heat Input ◽  
Large Scale ◽  
High Deposition Rate ◽  
Bead Geometry ◽  
Layer By Layer ◽  
Cold Metal Transfer ◽  
Geometrical Shapes ◽  
Wire Arc Additive Manufacturing

Nowadays, rapid prototyping is an emerging trend that is followed by industries and auto sector on a large scale which produces intricate geometrical shapes for industrial applications. The wire arc additive manufacturing (WAAM) technique produces large scale industrial products which having intricate geometrical shapes, which is fabricated by layer by layer metal deposition. In this paper, the CMT technique is used to fabricate single-walled WAAM samples. CMT has a high deposition rate, lower thermal heat input and high cladding efficiency characteristics. Humping is a common defect encountered in the WAAM method which not only deteriorates the bead geometry/weld aesthetics but also limits the positional capability in the process. Humping defect also plays a vital role in the reduction of hardness and tensile strength of the fabricated WAAM sample. The humping defect can be controlled by using low heat input parameters which ultimately improves the mechanical properties of WAAM samples. Two types of path planning directions namely uni-directional and bi-directional are adopted in this paper. Results show that the optimum WAAM sample can be achieved by adopting a bi-directional strategy and operating with lower heat input process parameters. This avoids both material wastage and humping defect of the fabricated samples.

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