Design and Development of Knowledge Bases for Forward and Reverse Mappings of TIG Welding Process

2009 ◽  
pp. 185-200
Author(s):  
J. P. Ganjigatti ◽  
Dilip Kumar Pratihar
Keyword(s):  
Regression Analysis ◽  
Welding Process ◽  
Knowledge Bases ◽  
Tig Welding ◽  
Inert Gas ◽  
Statistical Regression ◽  
A Tig Welding ◽  
Input Variables ◽  
Forward Mapping ◽  
Reverse Mapping

In this chapter, an attempt has been made to design suitable knowledge bases (KBs) for carrying out forward and reverse mappings of a Tungsten inert gas (TIG) welding process. In forward mapping, the outputs (also known as the responses) are expressed as the functions of the input variables (also called the factors), whereas in reverse mapping, the factors are represented as the functions of the responses. Both the forward as well as reverse mappings are required to conduct, for an effective online control of a process. Conventional statistical regression analysis is able to carry out the forward mapping efficiently but it may not be always able to solve the problem of reverse mapping. It is a novel attempt to conduct the forward and reverse mappings of a TIG welding process using fuzzy logic (FL)-based approaches and these are found to solve the said problem efficiently.

Performance of weld bead profile during A-TIG welding on nitrogen alloyed stainless steel

2021 ◽  
Author(s):  
Akash Deep ◽  
Vivek Singh ◽  
Som Ashutosh ◽  
M. Chandrasekaran ◽  
Dixit Patel
Keyword(s):  
Stainless Steel ◽  
Welding Process ◽  
Weld Bead ◽  
Tig Welding ◽  
Inert Gas ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
A Tig Welding ◽  
Arc Welding Process

Abstract Austenitic stainless steel (ASS) is widely fabricated by tungsten inert gas (TIG) welding for aesthetic look and superior mechanical properties while compared to other arc welding process. Hitherto, the limitation of this process is low depth of penetration and less productivity. To overcome this problem activated tungsten inert gas (A-TIG) welding process is employed as an alternative. In this investigation the welding performance of conventional TIG welding is compared with A-TIG process using TiO2 and SiO2 flux with respect to weld bead geometry. The experimental investigation on A-TIG welding of ASS-201 grade shows TiO2 flux helps in achieve higher penetration as compared to SiO2 flux. While welding with SiO2 the hardness in HAZ and weld region higher than that of TIG welding process.

Optimization of A-TIG welding process parameters for RAFM steel using response surface methodology

2015 ◽  
Vol 232 (2) ◽  
pp. 121-136 ◽  
Author(s):  
P Vasantharaja ◽  
M Vasudevan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Welding Process ◽  
Tig Welding ◽  
Depth Of Penetration ◽  
Bead Width ◽  
A Tig Welding ◽  
Input Variables ◽  
Haz Width

In the present work, the optimization of Activated TIG (A-TIG) welding process parameters to achieve the desired weld bead shape parameters such as depth of penetration, bead width, and heat-affected zone (HAZ) width have been carried out using response surface methodology (RSM). The main problem faced in fabrication of weld joints is the selection of optimum combination of input variables for achieving required quality of welds. This problem can be solved by development of mathematical model and execution of experiments by RSM. Central composite design of RSM has been used to generate the design matrix for generating data on the influence of A-TIG welding process parameters. The input variables considered were welding current, torch speed, electrode tip angle, and arc gap. The response variables considered were depth of penetration, bead width and HAZ width. A second-order response surface model is developed for predicting the response for the set of given input process parameters. Then, numerical and graphical optimization is performed using RSM to obtain the desired depth of penetration, bead width, and target HAZ width using desirability approach.

Optimization of A-TIG Welding Process Using Simulated Annealing Algorithm

2020 ◽  
Vol 19 (04) ◽  
pp. 869-891
Author(s):  
Masoud Azadi Moghaddam ◽  
Farhad Kolahan
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Welding Process ◽  
Welding Current ◽  
Tig Welding ◽  
Inert Gas ◽  
Regression Equations ◽  
Depth Of Penetration ◽  
Bead Width ◽  
A Tig Welding

Flux-assisted tungsten inert gas welding process, also known as activated tungsten inert gas (A-TIG) 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 flux. 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. Different regression equations have been applied to model the responses. Based on the ANOVA results, the most fitted models have been selected as an authentic representative of the process responses. Furthermore, the welding current has been determined as the most important variable affecting 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 efficient (with less than 4% error) in modeling and optimization of the A-TIG welding process.

An Investigation of Dissimilar Welding Aluminum Alloys to Stainless Steel by the Tungsten Inert Gas (TIG) Welding Process

2017 ◽  
Vol 904 ◽  
pp. 19-23
Author(s):  
Van Nhat Nguyen ◽  
Quoc Manh Nguyen ◽  
Dang Thi Huong Thao ◽  
Shyh Chour Huang
Keyword(s):  
Stainless Steel ◽  
Aluminum Alloy ◽  
Welding Process ◽  
Dissimilar Materials ◽  
Welding Current ◽  
Tig Welding ◽  
Inert Gas ◽  
Dissimilar Welding ◽  
Adjacent Area ◽  
Welding Seam

Welding dissimilar materials has been widely applied in industries. Some of them are considered this as a strategy to develop their future technology products. Aluminum alloy and stainless steel have differences in physical, thermal, mechanical and metallurgic properties. However, selecting a suitable welding process and welding rods can solve this problem. This research aimed to investigate the T-joint welding between A6061 aluminum alloy and SUS304 stainless steel using new welding rods, Aluma-Steel by the Tungsten Inert Gas (TIG) welding process. The mechanical properties, the characteristics of microstructure, and component analysis of the welds have been investigated by the mechanical testing, scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). As a result, the fracture occurred at the adjacent area between welding seam and A6061 alloys plate. The thermal cracking appeared at central welding-seam along the base metals if high welding current. A large amount of copper elements found in the welds due to using the new welding rod, Aluma-Steel rod.

Experimental and numerical simulation of thermomechanical phenomena during a TIG welding process

2004 ◽  
Vol 120 ◽  
pp. 697-704
Author(s):  
L. Depradeux ◽  
J.-F. Jullien
Keyword(s):  
Numerical Simulation ◽  
Numerical Models ◽  
Welding Process ◽  
Central Zone ◽  
Mechanical Analysis ◽  
Tig Welding ◽  
General Ability ◽  
Reduced Dimensions ◽  
Simple Geometry ◽  
A Tig Welding

In this study, a parallel experimental and numerical simulation of phenomena that take place in the Heat Affected Zone during TIG welding on 316L stainless steel is presented. The aim of this study is to predict by numerical simulation residual stresses and distortions generated by the welding process. For the experiment, a very simple geometry with reduced dimensions is considered: the specimens are disks, made of 316L. The discs are heated in the central zone in order to reproduce thermo-mechanical cycles that take place in the HAZ during a TIG welding process. During and after thermal cycle, a large quantity of measurement is provided, and allows to compare the results of different numerical models used in the simulations. The comparative thermal and mechanical analysis allows to assess the general ability of the numerical models to describe the structural behavior. The importance of the heat input rate and material characteristics is also investigated.

Study of Weldability for Aluminide Coated Steels through A-TIG Welding Process

2021 ◽  
Vol 11 (2) ◽  
pp. 20200168
Author(s):  
Arunsinh B. Zala ◽  
N. I. Jamnapara ◽  
Vishvesh J. Badheka ◽  
C. S. Sasmal ◽  
Shiju Sam ◽  
...  
Keyword(s):  
Welding Process ◽  
Tig Welding ◽  
A Tig Welding

Joining Dissimilar Metals between Steel and Aluminum by TIG Welding

2015 ◽  
Vol 819 ◽  
pp. 45-49 ◽  
Author(s):  
Shamsul Baharin Jamaludin ◽  
Mohd Zahir Abd Latif ◽  
Mohd Noor Mazlee ◽  
Kamarudin Hussin
Keyword(s):  
Shear Strength ◽  
Aluminum Alloy ◽  
Microstructural Analysis ◽  
Welding Process ◽  
Welding Current ◽  
Tig Welding ◽  
Inert Gas ◽  
Dissimilar Metals ◽  
Tensile Shear Strength ◽  
Tensile Shear

The effect of welding current on the joining of mild steel and aluminum 6063 has been investigated. The joining was carried using a tungsten inert gas (TIG) welding. The welding currents used were 30 A to 80 A. The formation of intermetallic reaction layers (IML) and tensile shear strength of the joining were investigated. The result showed that tensile shear strength increased as welding current increased up to 55 A. Microstructural analysis showed that intermetallic reaction layer was formed at the interface between steel and aluminum alloy during welding process. The thickness of IML was decreased with decreasing welding current.

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