Prediction of Mild Steel Weld Properties Using Artificial Neural Network and Regression Analysis

Joseph I. Achebo and Martins Ufuoma Eki
Keywords: Bead height, Ultimate tensile strength, Brinell hardness number, welding process parameters, Regression analysis, Artificial neural network.
Tropical Journal of Science and Technology 2020 1(2), 37-49. Published: March 10, 2021


Safety hazards resulting from structural material failure occur mostly in less developed countries where material standard specifications are not strictly adhered to, due to failure of government policy implementation. These hazards often result in loss of life. Failures tend to occur at welded joints, and various research institutions are making attempts to prevent such failures by developing new methods that could predict and improve welded joint qualities. The concern goes beyond safety, but also encompasses economic and other similar long term considerations. In this study, experimental methods were used to obtain the Bead Height (BH), Ultimate Tensile Strength (UTS) and Brinell Hardness Number (BHN) of mild steel welded joints. Thereafter, the artificial neural network (ANN), and Regression analysis methods were applied to predict the corresponding values of the BH, UTS, and BHN. The resulting performance of these two predictive methods was compared side by side to determine which one of the two methods better predicted these quality properties. This comparative analysis was carried out by comparing the percentage error of ANN to that of the Regression analysis. From the results obtained, it was found that for the bead height, Regression analysis method produced a total of 1.72% error. For UTS, ANN method produced a total of 63.31% error whereas Regression analysis produced a total of 0.39% and for BHN, ANN method produced a total of 353.86% error whereas, Regression analysis method produced a total of 2.58% error. The results shows that overall, regression analysis method predicted the properties better. Also, the effect of the process parameters on the weld properties were investigated. In this study, a step by step method is applied.