MATEC Web Conf.
Volume 269, 2019IIW 2018 - International Conference on Advanced Welding and Smart Fabrication Technologies
|Number of page(s)||8|
|Section||Additive Smart Manufacturing|
|Published online||22 February 2019|
Development of Bead Modelling for Distortion Analysis Induced by Wire Arc Additive Manufacturing using FEM and Experiment
Faculty of Mechanical Engineering, UiTM Shah Alam, Selangor, Malaysia
2 Professorship of Virtual Production Engineering, Chemnitz University of Technology, Chemnitz, Germany
3 Chair of Welding Engineering, Chemnitz University of Technology, Chemnitz, Germany
4 Taylor's University, Malaysia
Corresponding author e-mail: firstname.lastname@example.org
In this research, Wire Arc Additive Manufacturing is modelled and simulated to determine the most suitable bead modelling strategy. This analysis is aimed to predict distortion by means of thermomechanical Finite Element Method (FEM). The product model with wire as feedstock on plate as substrate and process simulation are designed in form of multi-layered beads and single string using MSC Marc/Mentat. This research begins with finding suitable WAAM parameters which takes into account the bead quality. This is done by using robotic welding system with 01.2mm filler wire (AWS A5.28 : ER80SNi1), shielding gas (80% Ar/ 20% CO2) and 6mm-thick low carbon steel as base plate. Further, modelling as well as simulation are to be conducted with regards to bead spreading of each layers. Two different geometrical modelling regarding the weld bead are modelled which are arc and rectangular shape. Equivalent material properties from database and previous researches are implemented into simulation to ensure a realistic resemblance. It is shown that bead modelling with rectangular shape exhibits faster computational time with less error percentage on distortion result compared to arc shape. Moreover, by using the rectangular shape, the element and meshing are much easier to be designed rather than arc shape bead.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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