Optimization of Ti-6Al-4V/AISI304 diffusion bonding process parameters using RSM and PSO algorithm

Arun Negemiya A. (Manufacturing Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, India)
Rajakumar S. (Manufacturing Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, India)
V. Balasubramanian (Manufacturing Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, India)

Multidiscipline Modeling in Materials and Structures

ISSN: 1573-6105

Publication date: 24 June 2019

Abstract

Purpose

The purpose of this paper is to develop an empirical relationship for predicting the strength of titanium to austenitic stainless steel fabricated by diffusion bonding (DB) process. Process parameters such as bonding pressure, bonding temperature and holding time play the main role in deciding the joint strength.

Design/methodology/approach

In this study, three-factors, five-level central composite rotatable design was used to conduct the minimum number of experiments involving all the combinations of parameters.

Findings

An empirical relationship was developed to predict the lap shear strength (LSS) of the joints incorporating DB process parameters. The developed empirical relationship was optimized using particle swarm optimization (PSO). The optimized value discovered through PSO was compared with the response surface methodology (RSM). The joints produced using bonding pressure of 14 MPa, bonding temperature of 900°C and holding time of 70 min exhibited a maximum LSS of 150.51 MPa in comparison with other joints. This was confirmed by constructing response graphs and contour plots.

Originality/value

Optimizing the DB parameters using RSM and PSO, PSO gives an accurate result when compared with RSM. Also, a sensitivity analysis is carried out to identify the most influencing parameter for the DB process.

Keywords

Citation

Arun Negemiya, A., Rajakumar, S. and Balasubramanian, V. (2019), "Optimization of Ti-6Al-4V/AISI304 diffusion bonding process parameters using RSM and PSO algorithm", Multidiscipline Modeling in Materials and Structures, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MMMS-07-2018-0134

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Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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