G. Senthilkumar This email address is being protected from spambots. You need JavaScript enabled to view it.1 and R. Ramakrishnan2

1Research Scholar, Department of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
2Professor & Head, Department of Sports Technology, Tamilnadu Physical Education and Sports University, Chennai, India


Received: July 18, 2020
Accepted: December 17, 2020
Publication Date: June 1, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202106_24(3).0011  


The aim of this work is to recommend a method to model a friction welding process parameters for ASTM A516 Grade 70 alloy steel using techniques like regression analysis, fuzzy logic and finite element analysis. The techniques used in this study were used to determine the welding process variable by which the expected burn off length is obtained in friction welding. The 9 set of input parameters like friction pressure, upset pressure, forging time and rotational speed and corresponding output parameter burn off length gathered based on L9 Orthogonal array. While error estimated for regression analysis is 6.01 %, finite element analysis is 4.98 % marginally outperforms, fuzzy logic analysis which is yielded error only 3.26 %. The fuzzy logic analysis is the proposed methodology used to predict burn off length parameter for any set of welding input parameters. This model helps us to find out the actual length of the material in the joining process.

Keywords: Burn off length, Regression Analysis, Fuzzy Logic Analysis, Finite Element Analysis.


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