Multi Response Optimization of Submerged Arc Welding Using Taguchi Fuzzy Logic Based on Utility Theory

The submerged-arc welding (SAW) process is an essential metal-joining process used in industry. SAW is applied for pressure vessels, heat exchangers, shipbuilding, line piping, and petroleum industries. The present work investigated the optimization of SAW parameters of 10-mm thick SA516 grade 70 steel to achieve the desired mechanical properties of the weld. Three SAW process parameters were investigated, each at three different levels welding current (300, 350, and 400 A), arc voltage (32, 36, and 40 V), and welding speed (26, 28, and 30 cm/min). Sample plates measuring 50050010 mm were used to test the parameters. The weld quality and properties were evaluated using the following response parameters Ultimate Tensile Strength (UTS), Ultimate Bending Force (UBF), HB Macrohardness (HB), and the Charpy Impact Test (CIT). Utility-based fuzzy logic was used to convert the complex multiple objectives into a single utility, Multi Performance Characteristic Index (MPCI). The MPCI response values were measured using the fuzzy inference system, Mamdani type. The results revealed that the optimal SAW parameters are welding current 400 A, arc voltage 40 V, and welding speed 30 cm/min. All process parameters had significant effects based on analysis of variance (ANOVA) (P