Optimization of TIG Welding Parameters for Enhanced Surface Quality and Mechanical Performance of AISI 316L Stainless Steel
Optimization of TIG Welding Parameters for Enhanced Surface Quality and Mechanical Performance of AISI 316L Stainless Steel
M. Kanan,Articl Info
Abstract
Present research work deals with the design of experiments and optimization of TIG welding parameters to improve the surface quality and mechanical properties of austenitic stainless-steel grade. The key process parameters (welding current, welding speed and shielding gas flow rate) were finalized by conducting systematic experiments on the welding characteristics and properties. Experiments were conducted by Response surface methodology (RSM) using Box-Behnken design to analyze the effect of the above parameters on the surface quality aspects such as weld bead width, surface smoothness, surface defect formation and mechanical properties like ultimate tensile strength (UTS) and hardness. The experimental results indicated that the surface quality is very sensitive to heat input, which is dominated by welding current and velocity. When welding current was 90 A, the fusion went insufficient, which result in the irregular surface profile and the presence of surface discontinuity. When the welding current increased to 115-120 A, the surface finished very well and the weld bead was uniform and smooth, with width of 5.0-5.5 mm. When welding current was increased to 130 A, the welding pool melted excessively, and the width of weld bead was increased to 7.0 mm. When the welding velocity increased from 100 to 200 mm/min, the surface was smooth, and the surface was irregular when the velocity was decreased; the surface was irregular. For the shielding gas flow rate of 15 L/min, good surface appeared, and the oxidation and plasma formation were prevented effectively. The hardness of the base metal decreased from 150 HV to 170 190 HV and the UTS increased to the maximum of 605-615 MPa under the optimal welding condition. The RSM models predicted the surface quality and mechanical properties with high accuracy with the R2 higher than 0.95. Desirability Function Approach (DFA), Teaching learning-based optimization (TLBO) and Grey Relational Analysis (GRA) were used to found optimized welding parameters combination of 115-120 A current, 140-150 mm/min of welding speed and 15 L/min of gases flow rate. These conditions produced performances of around 20% improvements in surface quality and overall weld performance. As a whole, the results give quantitative guidance on how to weld in high quality with great surface finish in industry.
