Journal of Advanced Manufacturing Systems, Volume (19), No (4), Year (2020-12) , Pages (869-891)

Title : ( Optimization of A-TIG Welding Process Using Simulated Annealing Algorithm )

Authors: Masoud Azadi Moghaddam , Farhad Kolahan ,

Citation: BibTeX | EndNote

Abstract

Flux-assisted tungsten inert gas welding process, also known as activated tungsten inert gas (ATIG) welding, is extensively used in order to improve the performance of the conventional TIG welding process. In this study, the orthogonal array Taguchi (OA-Taguchi) method, regression modeling, analysis of variance (ANOVA) and simulated annealing (SA) algorithm have been used to model and optimize the process responses in A-TIG welding process. Welding current (I), welding speed (S) and welding gap (G) have been considered as process input variables for fabricating AISI316L austenitic stainless steel specimens. Depth of penetration (DOP) and weld bead width (WBW) have been taken into account as the process responses. In this study, SiO2, nano-particle has been considered as an activating °ux. To gather required data for modeling, statistical analysis and optimization purposes, OA-Taguchi based on the design of experiments (DOE) has been employed. Then the process responses have been measured and their corresponding signal-to-noise (S/N) ratio values have been calculated. Di®erent regression equations have been applied to model the responses. Based on the ANOVA results, the most ¯tted models have been selected as an authentic representative of the process responses. Furthermore, the welding current has been determined as the most important variable a®ecting DOP and WBW with 68% and 88% contributions, respectively. Next, the SA algorithm has been used to optimize the developed models in such a way that WBW is minimized and DOP is maximized. Finally, experimental performance evaluation tests have been carried out, based on which it can be concluded that the proposed procedure is quite e±cient (with less than 4% error) in modeling and optimization of the A-TIG welding process.

Keywords

, Activated TIG welding process; OA, Taguchi method; regression modeling; analysis of variance; optimization; simulated annealing algorithm
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@article{paperid:1083555,
author = {Azadi Moghaddam, Masoud and Kolahan, Farhad},
title = {Optimization of A-TIG Welding Process Using Simulated Annealing Algorithm},
journal = {Journal of Advanced Manufacturing Systems},
year = {2020},
volume = {19},
number = {4},
month = {December},
issn = {0219-6867},
pages = {869--891},
numpages = {22},
keywords = {Activated TIG welding process; OA-Taguchi method; regression modeling; analysis of variance; optimization; simulated annealing algorithm},
}

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%0 Journal Article
%T Optimization of A-TIG Welding Process Using Simulated Annealing Algorithm
%A Azadi Moghaddam, Masoud
%A Kolahan, Farhad
%J Journal of Advanced Manufacturing Systems
%@ 0219-6867
%D 2020

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