Performance optimization and investigation of metal-cored filler wires for high-strength steel during gas metal arc welding

Abstract

This study examines the utilization of metal-cored filler wire in conjunction with the gas metal arc welding (GMAW) technique for welding high-strength S690QL steel. Since welding parameters significantly impact the bead quality and weld joint integrity, the main objective was to identify the optimal welding parameters. To achieve this, the input variables including the current (A), voltage (V), and gas flow rate (GFR), and their effects were evaluated for reinforcement (R), width (W), depth of penetration (DOP), and the width of the heat-affected zone (HAZ). For a more efficient and cost-effective investigation, a Box–Behnken design, which is based on response surface methodology, was used for bead-on-plate trials. Mathematical regression models, derived from experimental data, were rigorously validated using the analysis of variance, main effects plots, residual analysis, and the R 2 and Adj. R 2 values. Additionally, the heat transfer search (HTS) algorithm was employed for process optimization. While single-objective optimization provided optimal settings for individual responses, simultaneous optimization aimed to strike a balance between multiple, sometimes conflicting, objectives. This comprehensive approach resulted in specific values, including a reinforcement (R) of 4.285 mm, a width (W) of 9.906 mm, a DOP of 2.039 mm, and an HAZ width of 2.020 mm. These values were achieved with specific input parameters: current (221 A), voltage (24 V), and GFR (21 L·min−1). The Pareto solutions offered a nuanced selection of the most suitable configuration, taking into account the desired values for R, W, DOP, and HAZ. The close alignment between predicted and experimentally measured values for the responses highlights the precision and suitability of the HTS algorithm in estimating critical bead geometries during GMAW of S690QL plates.

Keywords

• metal-cored arc welding
• high-strength steel s690ql
• heat transfer search algorithm
• analysis of variance