Determining the effective Variable to improve the Quality of Welding with Response Surface Methodology and comparing it with Simulation Annealing Algorithm

In this paper, the critical parameters of a method of welding with shielding gas arc welding (GMAW) are discussed; this method is an important process in creating high quality metal permanent connections in various industries, including the automobile industry to improve the quality of stem diameter welding parameters. One of the most useful techniques for modeling and solving the problems is Response Surface Method. In this paper, considering five most important factors such as speed welder, torch angle with the work piece, electrode diameter, wire speed, gas consumption, and CO2 levels as input variables, can be controlled independently from the level of response, the relationship between the input variables and the response variables were determined using linear regression. Then optimum value for each factor was calculated using non-linear programming model to evaluate the results obtained along with the comparison of output of the Simulation Annealing Algorithm. In this study, both qualitative and quantitative variables are considered to evaluate and optimize all response variables regarding that these variables are not the same, and then fuzzy set theory and LP metric are used to find answers for multi-objective optimization methods.