Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms

Abstract

The concepts and inspiration of biological evolution in nature are used to create new and effective competing tactics in the burgeoning field of bio-inspired computing optimization algorithms. In the present work, nine specimens of similar alloys i.e., AA6262 were Friction Stir Welded. Spindle Speed (RPM), Traverse Speed (mm/min), and Plunge Depth (mm) were the input parameters while the Ultimate Tensile Strength (MPa) was an output parameter. The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. The results showed that the Differential Evolution algorithm resulted in a slightly higher value of the Ultimate Tensile Strength in comparison to the Max LIPO algorithm.