Parametric optimization of friction stir welding process for marine grade aluminum alloy

Abstract

Purpose

The purpose of this paper is to deal with the experimental data related to the friction stir welding (FSW) of marine grade Al-Mg4.2 alloy. Mathematical models are developed to study the individual and interaction effects of input variables on the performance characteristics of joints. FSW parameters are optimized to maximize the yield strength and weld nugget microhardness of the welded joints.

Design/methodology/approach

Response surface methodology is applied to establish the mathematical relationship between six input factors, namely, tool rotational speed, transverse speed, tool shoulder diameter, tool material hardness, tilt angle and pin profile; and two response variables, namely, yield strength and weld nugget microhardness. Six factors–five-level rotatable central composite matrix is used for the design of experiments. The quadratic model is used, as suggested by the design expert software, to express the response parameters as a function of investigated input parameters. The competence of the developed models is verified through analysis of variance.

Findings

The present investigation clearly indicates that the studied input factors have a significant effect on the quality of the joints. The optimal combination of input factors is determined to achieve the desired responses.

Originality/value

This paper teems a new look on tensile and hardness properties of Al-Mg4.2 joints by relating the microstructure, fractrographs and grains distribution with the dynamic recrystallization and plasticized material movement during the FSW process. The outcome of this research will help in seizing the opportunities of joining Al-Mg4.2 alloy using FSW, in the offshore and marine applications.

Citation

Goyal, A. and Garg, R.K. (2019), "Parametric optimization of friction stir welding process for marine grade aluminum alloy", International Journal of Structural Integrity, Vol. 10 No. 2, pp. 162-175. https://doi.org/10.1108/IJSI-01-2018-0007