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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 20, Issue 3 (September 2026).... Submit articles

TAGUCHI-BASED OPTIMIZATION OF GMAW WELDING PARAMETERS FOR JOINT STRENGTH

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  • TAGUCHI-BASED OPTIMIZATION OF GMAW WELDING PARAMETERS FOR JOINT STRENGTH

Innocent Mapindu *, Destine Mashava, Vongai Shangwa, Tecclar Tarisai Chigavazira-Gwara and Gilbert Munhuwamambo 

Department of Industrial and Manufacturing Engineering, National University of Science and Technology (NUST) Bulawayo, Zimbabwe.
* Corresponding Author: innocent.mapindu@nust.ac.zw 
ORCID Details
Innocent Mapindu: https://orcid.org/0009-0007-2024-1919   
Destine Mashava: https://orcid.org/0009-0002-9487-9038

Research Article

 

World Journal of Advanced Engineering Technology and Sciences, 2026, 20(03), 206–219

Article DOI: 10.30574/wjaets.2026.20.3.0448

DOI url: https://doi.org/10.30574/wjaets.2026.20.3.0448

Received on 14 August 2026; revised on 24 September 2026; accepted on 26 September 2026

There is a set of process variables that defines the quality of a gas metal arc weld (GMAW) joint. The iteration of these process variables to find the optimum setting is time-consuming and does not have a statistical basis. The Taguchi method of robust parameter design is used to determine the optimum combination of welding current, arc voltage, shielding gas flow rate and travel speed to maximize the transverse tensile strength and minimize the weld defect count of mild-steel GMAW joints. Three replicates per trial (27 specimens) were used in a 3²7 experiment designed by a 4 factor 3 level L9(3⁴) orthogonal array.This was a 3²7 experiment using 3 replicates per trial in the form of an L9 (3⁴) orthogonal array. To estimate the influence of the factors and to determine single response optima, signal-to-noise (S/N) ratios, analysis of variance (ANOVA) and response-table analysis were used, and grey relational analysis (GRA) was applied to solve the conflict between the two response optima in order to select a compromise set of parameters. Of the 12 factors evaluated, the current and the arc voltage were found to be the most significant factors for both responses, contributing 35.28% and 31.06% of the variance in tensile strength, respectively, and 25.47% and 21.72% of the variance in number of defects, respectively, and for both responses were statistically significant at 1% level. Based on the GRA-based compromise optimum of 220 A / 24 V / 15 L/min / 350 mm/min, the tensile strength of 534.4 MPa with an acceptable defect level is predicted. The methodology, equations, and complete statistical processing are explained in detail in this paper, so that the study can be directly repeated using data measured in the laboratory

Taguchi method, Design of experiments, Gas metal arc welding, GMAW, Signal-to-noise ratio, Analysis of variance, ANOVA, Grey relational analysis, Joint strength, Weld defects, Parameter optimization

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2026-0448.pdf

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Innocent Mapindu, Destine Mashava, Vongai Shangwa, Tecclar Tarisai Chigavazira-Gwara and Gilbert Munhuwamambo. TAGUCHI-BASED OPTIMIZATION OF GMAW WELDING PARAMETERS FOR JOINT STRENGTH. World Journal of Advanced Engineering Technology and Sciences, 2026, 20(03), 206–219. Article DOI: https://doi.org/10.30574/wjaets.2026.20.3.0448

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