Characterization and Process Parameter Optimization of Friction Stir Welded Aa6061 Rutile Composites

Abstract

Increased demand for sophisticated materials has revealed characteristics including low density, high strength-to-weight ratio, and outstanding mechanical capabilities for use in aircraft, shipbuilding, and railroad construction. Fusion welding, which is frequently used for such materials, might cause cracks to form. The Welding Institute in the United Kingdom developed and patented a revolutionary welding method called Friction Stir Welding (FSW), which is used to join similar/dissimilar metals and composites. As a solid-state welding method that doesn't use inert gases and doesn't release any harmful gases when welding, friction stir welding is also known as "green welding." FSW has several advantages over fusion welding, including a higher joint strength, a defect-free weld, a more uniform distribution of grain structure in the weld zone, and reduced power consumption. The primary goal of the current study is to determine the optimal way to join aluminium matrix composites. Stir cast AA6061-3 (wt.%) Rutile composite has been used as the material for friction stir welding. With the help of a CNC vertical machining centre, the specimen is welded. A scanning electron microscope is used to perform a microstructural study of the weld area. Energy Dispersive X-ray Analysis (EDAX) of the weld zone is carried out to examine the chemical composition. Additionally, mechanical properties are evaluated by measuring the hardness and tensile strength of the welded composite. Composites that undergo friction stir welding develop an equiaxed grain structure with a uniform distribution of reinforced particles at the weld zone. The size of the rutile particles shrank at Nugget Zone, and the particles were observed to be redistributed. The mechanical properties of the joint have therefore been enhanced. At the Heat Affected Zone, the heat effect of the welding process causes the development of coarse grain (HAZ). The obtained results were examined using a classical approach. The joint strength of composites is improved via friction stir welding. Due to the small grain and presence of rutile particles, the nugget zone experienced a significant hardness increase. Experimental investigation shows that friction stir welding of stir cast AA6061-3 (wt.%) rutile composites using a combined square and threaded cylindrical profiled pin tool with a rotational speed of 1000 rpm and a welding speed of 75 mm/min results in welds that are defect-free and have the best strength. According to the research carried out using Taguchi design of experiments, rotating speed, welding speed, and tool pin profile are the factors that contribute most to an improvement in mechanical strength. The Taguchi technique's optimal process parameters and the related predicted value are experimentally verified using the confirmation test. The optimization of process parameters to get joints with superior mechanical properties was done using statistical techniques as well as an evolutionary algorithm. The usage of an optimization strategy can produce the best results for the given problems within the constraints. To establish the optimum optimization strategy, various multi-objective optimization strategies are compared, including Grey Relational Analysis (GRA), Desirability Approach, and Teaching-Learning Based Optimization (TLBO). Additionally, a multilayer perception neural network model based on genetic algorithms is used to predict the mechanical properties of composite joints. It is renowned for its nonlinear mapping of intricate static data. The validation experiments were conducted to validate the trained model. It is discovered that the mechanical property predictions are accurate and within reasonable bounds.