Integrating robotic wire arc additive manufacturing and machining: hybrid WAAM machining
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Metal Big Area Additive Manufacturing is an additive manufacturing technique based on Gas Metal Arc Welding (GMAW) with the option to use many shielding gases, and materials. The system is equipped with a dual torch design allowing for printing different materials; in our study, AISI 410 stainless steel and AWS ER70S-6 mild steel are both printed in the same component. Different print strategies were designed to highlight changes in material and mechanical properties. Deformation behaviour of a materials’ interface was analysed by two-dimensional digital image correlation of uniaxial tensile specimens in displacement-controlled tests. Instances of non-homogeneous local strains adjacent to the interface are observed, as well as variability in mechanical behaviour and microstructure based on location within the print. Optical and electron microscopy are used to evaluate three microstructural zones in a 5 mm range of the interface between mild steel and stainless steel. Areas far from the interface produced polygonal ferrite and pearlite, while areas close to the interface produced acicular ferrite and bainite. Chromium redistribution profiles are dependent on the print strategy used, as shown by scanning electron microscopy with Energy dispersive spectroscopy. Evidence produced via electron backscatter diffraction is shown to support the argument that transformation induced plasticity is not the cause for the non-homogeneous deformation.
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This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.
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The Department of Defense (DOD) programs of records desire to reduce the time and cost of the development and delivery loop in metal additive manufacturing (AM), including establishing forwarded AM capabilities. The success of these efforts relies on a robust and qualified process. To achieve this, the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center Materials Engineering (GVME) needs to be able to quickly evaluate, test, and develop feedstocks, processes, and parts. This report is directed towards demonstrating the need for a framework for metal AM processes, defining and exploring geometries for metal AM process qualification, testing resultant deposition, and delivering actionable data.
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