| Abstract: | Recently, there has been a rapid development in computer technology, which has in turn led todevelop the fully robotic welding system using artificial intelligence (AI) technology. However, therobotic welding system has not been achieved due to difficulties of the mathematical model andsensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry,such as bead width, bead height, bead penetration and bead area in the robotic GMA (gas metalarc) welding process is presented. The approach, a well-known method to deal with the problemswith a high degree of fuzziness, is used to build the relationship between four process variablesand the four quality characteristics, respectively. Using these models, the proper prediction of theprocess variables for obtaining the optimal bead geometry can be determined. |
