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2021 | OriginalPaper | Chapter

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

Authors : Kartikeya Bector, Aranyak Tripathi, Divya Pandey, Ravi Butola, Ranganath M. Singari

Published in: Advances in Manufacturing and Industrial Engineering

Publisher: Springer Nature Singapore

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Abstract

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.

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Metadata
Title
A Review on the Fabrication of Surface Composites via Friction Stir Processing and Its Modeling Using ANN
Authors
Kartikeya Bector
Aranyak Tripathi
Divya Pandey
Ravi Butola
Ranganath M. Singari
Copyright Year
2021
Publisher
Springer Nature Singapore
Book
Advances in Manufacturing and Industrial Engineering

Print ISBN: 978-981-15-8541-8

Electronic ISBN: 978-981-15-8542-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8542-5_1

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