Experimental validation and Parametric Optimization in MIG welding of A-36 steel plate using Taguchi-Fuzzy logic approach

Abstract

Metal inert gas (MIG) welding is one of the most effective and highly economic methods in automotive repair, welding pipes, and machinery reconstruction. Mass production can be achieved by MIG welding as it has a high weld metal deposition rate. MIG welding operating parameters are current, speed, and nozzle-to-plate distance (NPD) have a significant impact on joining material and joint quality. Good quality joints can be obtained by minimum weld penetration, minimum dilution, maximum bead width, and maximum weld reinforcement by optimizing the process set of the input parameters using optimization techniques. The Taguchi methodology and the Fuzzy logic technique were used to optimize MIG welding operating conditions for the A-36 steel plate. The experimental plan is developed using a Taguchi L9 orthogonal array of three factors and three levels. Taguchi has been used for optimizing the effects of process parameters. Linguistic rules and fuzzy quantitative analysis were used to create a correlation among operating parameters and output response. The Prediction of Output response from the Fuzzy logic developed model and the experiment results are visualized.

Keywords- MIG Welding, Taguchi, Fuzzy logic, Parametric, Optimization.