A Review on the Fabrication of Surface Composites via Friction Stir Processing and Its Modeling Using ANN

Friction Stir Processing (FSP) is a surface modification and surface composite fabrication technique that was first theorized and demonstrated in 2002. Since then, it has grown exponentially in the industry due to its efficiency, ease of usability and various other advantages over conventional surface modification and fabrication processes. Artificial Neural Networks provide a computational model that can handle complex relationships between the various determinants involved in FSP and the effect they have on the final output. ANN has been used extensively to predict the impact of various FSP determinants and hence model the most efficient values of these determinants for various base metals. This paper has tried to encapsulate the plethora of research done on the optimization of FSP determinants using ANN architecture.