Experimental and Theoretical Investigation into the Effect of Welding-Parameters and Magnetic-Field on Structure and Properties of Weld in Arc-Welding

This paper investigated the multi-response optimization of shielded metal arc welding (SMAW) process for an optimal parametric combination to yield favorable bead geometry and mechanical properties of welded joints using artificial neural networks method. Total twenty five sets of experimental input output data were obtained to train the ANN model and to verify the prediction made by the model. Cross slide of a lathe machine was used to have constant welding speed. External magnetic field was obtained with the help of a bar magnet mounted on tailstock side of the lathe machine with a wooden structure. The main aim was to derive objective functions like welding current, voltage, speed of welding and external magnetic field to be optimized within experimental domain. The objective functions have been selected in relation to parameters of SMAW welding bead geometries like bead width, reinforcement height, depth of penetration, and mechanical properties like hardness, impact strength and tensile strength. The model was trained with the help of eighteen sets of data. Optimal results have been verified through seven other data sets of experiments. This shows application feasibility of the artificial neural networks for continuous improvement in product quality in manufacturing industry. Citation: Rudra Pratap Singh. "Experimental and Theoretical Investigation into the Effect of Welding-Parameters and Magnetic-Field on Structure and Properties of Weld in Arc-Welding." Global Research and Development Journal For Engineering 5.11 (2020): 43 - 56.