Meta-heuristic optimization of copper friction stir weldments

Abstract

This work focused on the optimization of process parameters, which may result in increasing mechanical properties of copper weldments. The different tool pin profiles such as plain taper cylindrical, taper cylindrical with threaded, triangular, square, pentagonal and hexagonal having constant shoulder diameters were used to fabricate the weldments. The experiments were conducted at different levels of tool rotational speed and weld speeds using six different tool pin profiles. The experimental results revealed that the defect free weldments could be obtained by using different tool pin profiles. From the investigation, it was found the weldments made by using a square (SQ) tool pin profile resulted in better mechanical properties compared to other tool pin profiles. Objective functions are developed for the mechanical properties in terms of input parameters. The input parameters of an SQ tool pin profile were optimized using a metaheuristic optimization based algorithm named teaching learning based optimization (TLBO) technique to improve mechanical properties. The TLBO suggests a combination of 900 rpm of tool rotation speed and 40 mm/min weld speed for better properties.

Keywords

• friction stir weldments
• mechanical properties
• tlbo
• mathematical models
• multi-objective optimization