Fuzzy Logic to predict the Hardness of Melted Zone in the Submerged Arc Welding of Steel Plate Using TiO2 Nano Particle

Submerged arc welding (SAW), is a high quality arc welding process used in heavy industry in this welding process is essential in order to control the properties of weldment. Hardness testing of welds provides an indication to the determination of a successful weld joint. The tensile of steel is proportional to its hardness. Thus the hardness test can become a quick screening test to determine if the steel in question has the expected tensile strength or not. In this paper, the welding current, arc voltage, welding speed, contact tip-to-plate distance and thickness of coated TiO2 nano particles on plates were considered as input variables. Experiments were performed based on rotatable central composite design (RCCD) with five factors, each of them set as its five levels. Hardness of melted zone was measured as the response. Finally, the hardness of melted zone was modeled as a function of input variable by fuzzy logic. Moreover, it has been concluded that, fuzzy logic is a powerful technique used for predicting the hardness of melted zone due to its low error rate as compared with experimental outputs.