PREDICTION OF WELD BEAD WIDTH IN SUBMERGED ARC WELD OF MILD STEEL USING FUZZY LOGIC MODELING
Keywords:
Fuzzy Logic, Weld Quality, Submerged Arc WeldingAbstract
Artificial Intelligent tools such as expert systems, artificial neural network, and fuzzy logic support decision-making in intelligent manufacturing systems. Success of intelligent manufacturing systems depends on effective and efficient utilization of intelligent tools. This paper discusses the development of a fuzzy logic model to predict weld quality for Submerged Arc Welding process (SAW) under given set of input weld parameters such as welding current, arc voltage, welding speed, and electrode stickout. The model is developed using Matlab toolbox functions and is validated.
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