Gas Metal Arc Welding (GMAW) has been one of the most widely used industrial welding processes since around the middle of the 20th Century. However, the large number of input parameters and variables makes it extremely challenging to understand exactly what impact the variation of each of the inputs (and their interactions with each other) has on the resultant fillet weld. Although the GMAW welding process is a mature and generally well understood process, there is little to no evidence of research specifically focused on understanding what impact the torch orientation (travel angle and gun angle) and parameter interactions have on the resultant fillet weld geometry and structure. The purpose of this study is to provide an improved understanding of the main GMAW process parameters (current, voltage, travel speed, shielding gas flow rate, electrode, travel angle and gun angle), which can then be applied to a robotic welding set up in order to optimise the process by minimising heat input, distortion and cost whilst achieving satisfactory penetration and leg length. Artificial Neural Networks (ANNs) and Regression analysis were used to identify the key parameters and interactions that impact a fillet weld geometry.;These results highlighted that the torch travel angle was significant in determining both the shape and also the level of asymmetry between the horizontal and vertical leg lengths of the fillet weld. Finite Element Analysis was then used to determine how the fillet weld geometry impacts the temperature distribution and distortion of the fillet welded assembly.;The FEA model demonstrated that varying the fillet weld geometry impacts the temperature distribution and distortion of the fillet welded structure. Specifically the results suggest that welding the fillet with a larger horizontal leg length appears to generate less overall deflection on the baseplate. This reinforces that that in order to control the level of distortion of a welded structure it is important to tightly control the size and shape of the fillet weld. A Schlieren study was conducted to visualise the behaviour of the shielding gas around the filet weld. This study highlighted that the shielding gas flow rate can be significantly reduced, for a fillet weld, without compromising the quality of the weld.;This improved understanding, from the ANN, FEA and visualisation studies has the potential to generate significant benefits if applied to a robotic welding set up. Creating a more robust process that can be optimised to achieve a target geometry, minimise the heat input and distortion and minimise the overall cost of the weld.
|Date of Award||20 Jan 2021|
- University Of Strathclyde
|Supervisor||Alexander Galloway (Supervisor) & Margaret Stack (Supervisor)|