Prediction of Bead Width in Submerged Arc Welding Process using Nano-TiO2 by Fuzzy Logic

Submerged arc welding (SAW) is a high quality arc welding process used in heavy industry. In this process an electric arc is established between a continuous filler metal and the weld pool with protecting by a granular flux. Selecting appropriate values for input variables in this welding process is essential in order to control the properties of weldments. In this paper, the welding current, arc voltage, welding speed, contact tip-to-plate distance and thickness of TiO2 nano particles coated 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. After that width of weld bead was measuredas the output variable or the response. Finally weld bead width was modeled as a function of input variables and predicted by fuzzy logic. Moreover, it has been concluded that, fuzzy logic is a powerful technique used for predicting the bead width of weldments due to its low error rate as compared with experimental outputs.

Keywords:

Submerged arc welding , Weld bead width , Fuzzy logic , Titanium dioxide