Optimization of Process Parameter of Tungsten Inert Gas Welding for Austenitic Stainless Steel using Grey Wolf Optimization
Keywords:Tungsten inert gas, optimization, austenitic stainless steel, ultimate tensile strength, yield strength
Optimization of welding parameters is essential on austenitic stainless steel for industrial applications since they declare the best parameters compared with prioritized constraints. However, available optimization methods, such as the Taguchi method, widely used in this research domain, are weak. Their results are merely comparative and fail to particularly show the specific factor that displays the highest performance in the process. In this paper, the aim is specifically to position the parameters in order of importance and present them in a grey wolf optimization framework. The ultimate tensile strength and yield strength were optimized, and the optimization was conducted using the C++ programming code. Literature data were analyzed for austenitic stainless steel under un-notched/smooth and notched specimen conditions. Empirical models were developed for the ultimate tensile strength and yield strength, among other principal criteria of the material. For the ultimate tensile strength, the best value was obtained at the 100th iteration as 640.75. For the yield strength, the best value of 394.98 was obtained after 100 iterations. A value of 31.07 for the PE was obtained. These results are for the unnotched specimens. However, the PE, NTS, and yield strength values for the notched specimens are 16.32, 780.12, and 494.46, respectively. Based on the findings of this study and compared with other optimization methods, the optimal parameters and outputs predicted using the grey wolf optimization approach were found to produce reliable results. This shows that the grey wolf optimization approach is a good option for predicting the optimal parameters of the tungsten arc welding process by utilizing austenitic stainless steel. The usefulness of this research effort is to help process engineers to implement robust and effective cost decisions in the production of materials based on austenitic stainless steel.
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