An Approach to Enhance the Tensile Properties of Friction Stir Welds using Teaching Learning Based Optimization

In this paper, teaching and learning based optimization has applied to enhance the tensile properties of friction stir welding AA6061 and AA2024 aluminum alloys. Four significant variables were considered to conduct welding on age hardened aluminum alloys namely, tool rotational speed, welding speed, axial force, and tool pin profile. The effect of process variable on tool pin profile were analyzed by scanning electron micrographs, tensile testing, and elongation. The nugget zone is characterized by the onion rings whereas some of the weldments dealt with the defects such as cavities, tunnel, etc. TLBO algorithm has utilized to intend to minimize the defects by enhancing the tensile properties of the fabricated welds. From the experimental and algorithmic results, it is observed that the proposed RSM based TLBO approach is an effective approach for enhancing the tensile properties of fabricated age hardenable weldments.