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J Weld Join > Volume 35(1); 2017 > Article
TERNER, BAYARSAIKHAN, HONG, and LEE: Influence of Gas Metal Arc Welding Parameters on the Bead Properties in Automatic Cladding
Research Paper

Journal of Welding and Joining 2017; 35(1): 16-25.

DOI: https://doi.org/10.5781/JWJ.2017.35.1.16

Influence of Gas Metal Arc Welding Parameters on the Bead Properties in Automatic Cladding

Mathieu TERNER*, †, Tsend-Ayush BAYARSAIKHAN**, Hyun-Uk HONG*, Je-Hyun LEE*

* Department of Materials Science and Engineering, Changwon National University, Changwon 51140, Korea

** Department of Mechatronics, School of Mechanical and Transportation, Mongolian University of Science and Technology, Ulaanbaatar 14191, Mongolia

†Corresponding author : mathieu@changwon.ac.kr

Received December 2, 2016       Revised December 23, 2016       Accepted January 3, 2017

Copyright: © The Korean Welding and Joining Society

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Gas Metal Arc Welding is a widely used process in Industry due to its high productivity and potential to automation. The present study investigates the effects of the welding speed, arc voltage, welding current and shielding gas on the bead geometry for a low-carbon steel. The Response Surface Methodology (RSM) is used to choose an experimental design and perform test runs accordingly in order to produce mathematical models predicting the geometry, the hardness and the heat input of the bead as functions of the welding parameters. The direct and interaction effects of the four welding parameters are represented graphically and allow to determine an optimum set of welding parameters.

Key words: Gas metal arc welding, Welding parameters, Low carbon steels, Response surface methodology, Experimental design

1. Introduction

Gas Metal Arc Welding (GMAW) is a process in which a continuous wire electrode and a shielding gas are fed through the nozzle of a welding gun. This process is widely found in the industry thanks to a high productivity and its potential to automation. It is primarily used for repairing worn out parts, applying corrosion resistant surfaces or metal joining in a large scale. This arc welding technique is used in particular for the rebuilding and improvement of the service life of rolls operating in metal to metal wear conditions.
The quality of the weld is critical and can be evaluated in various ways, in particular the characteristics of the weld bead geometry which plays an important role with regards to the mechanical properties of the weld1, 2). The bead geometry is directly influenced by the welding process parameters2-5). To avoid weld bead defects and insure satisfactory mechanical properties, it is therefore necessary to carefully set-up the process parameters. These parameters are welding current, arc voltage, welding speed, torch angle, free wire length, nozzle-to-plate distance, welding direction, position and the flow rate and composition of the shielding gas6).
It is often very costly and time consuming to optimize the welding process by experimental analysis. This is due to the effects and interactions of the numerous process parameters influencing the quality of the weld bead. This is why analytical approaches have been developed using in particular designed experiments1-3,6-12). The Response Surface Methodology (RSM)13) is one of those methods and has been widely used to study the weld bead geometry as a function of several process parameters1,2,6-12).
In the present study, the RSM optimization technique is used to study the effects of welding parameters on the bead geometry of bead on plate welds deposited by GMAW on low-carbon steel. Four parameters are selected as input variables: welding speed (S), arc voltage (U), welding current (I) and shielding gas (SG). The responses are: penetration (p), width (w), height (h), contact angle (θ), hardness (HR), dilution (D) and heat input (HI). A mathematical model is proposed for predicting the weld bead geometry and the optimal range for the parameters is given.

2. Experimental section

2.1 Cladding process

The cladding experiments were carried out using a direct current inverter welding machine (JASIC-MIG250, 5 to 300 A output range) and a semiautomatic carriage (speed from 1 to 400 mm.min-1). The cladding material was an AWS classification E-7012 solid wire (OK Autrod 13.12) with a diameter of 1.2 mm. The base metal were 20×20×100 mm plates of C-CH35ACR low carbon steel. The chemical compositions of the base material and the cladding wire are given in Table 1.
Table 1
Chemical compositions of the base material and the welding wire
C Si Mn Cr Ni Cu Mo P S
Base metal: C-CH35ACR mild steel 0.01-0.03 0.08-0.1 0.2-0.4 0.1 0.1 0.1 0.03 0.04
Welding wire: OK Autrod 13.12 0.1 0.5 1.1 0.5 0.5 0.2 0.03 0.03
A critical parameter identified during trial runs was the wire feed rate (WF). This wire feed rate was proportional to the welding arc current (I) and followed a linear relationship. This relationship between the wire feed rate (WF) and the welding current (I) is given by Eq.
(1)
I=1.3596WF−245.17
The wire feed rate should be greater than a critical value to avoid defects4, 5). The wire feed rate and the welding arc current accordingly were chosen to obtain similar welding bead profiles according to different welding speed. The faster the welding speed, the fewer the melted wire deposited per unit length and therefore the smaller the bead geometry.
The shielding gas used for GMAW processes plays an important role. It can influence the quality and aspect of the welding joint, the welding speed and the actual costs of the process5, 14). Boiko at al.14) studied the effect of shielding gases on the MAG welding process. The different thermal conductivity of the shielding gases has a considerable influence on the arc configuration and the bead geometry. In the present study, different shielding gases were used with between argon, CO2, O2 and mixture gases at a constant flow rate of 15 L/min. The standard names and composition of the gases are given in Table 2.
Table 2
Standard name and chemical composition of the shielding gases
Coded value ISO 14175:2008 Composition (%)
Ar CO2 O2
1 M14 ArCO - 5/2 93 5 2
2 M26 ArCO - 20/2 78 20 2
3 M21 ArCO - 20 80 20
4 M24 ArCO - 12/2 86 12 2
5 C-C 100

2.2 Experimental design

The experimental work in this study was carried out according to the Response Surface Methodology (RSM)13) and was similar to previous similar studies2,7-11). This empirical method is commonly used for process in an industrial setting to optimize a response (here the bead geometry) influenced by several independent variables (here the process parameters). This method has been found to be valuable for the particular case of GMAW optimization1). As described for example by Bezerra et al.15), some stages in the application of RSM include: (1) selection of independent variables of major effects on the system and delimitation of the experimental region, (2) choice of the experimental design and experimental runs according to the selected design matrix, (3) mathematical-statistical treatment of the obtained experimental data through the fit of a polynomial function, (4) evaluation of the model’s fitness, (5) evaluation of the optimum values for each studied variables.

2.2.1 Process variables and response

The independent process variables identified as input parameters were adequately selected to carry out the experimental work and develop the mathematical models. The input variables were: welding speed (S), arc voltage (U), welding current (I) and shielding gas (SG). To describe the bead geometry, the responses or output parameters were: penetration (p), width (w), height (h), contact angle (θ), hardness (HR), dilution (D) and heat input (HI).

2.2.2 Limits of the process variables

The lower and upper limit values of the process variables were found by conducting trial runs and inspecting the bead for smooth appearance without any visible defects such as porosity, undercut, humping, etc. The lower limits were coded as -2 while the upper limits were coded as +2 according to the central composite rotatable factorial design selected for this study. The intermediate levels (-1, 0 and +1) were determined by interpolation. The list of input variables and their values as per coded value are given in Table 3.
Table 3
Input variables selected for the RSM and their levels
Input variable Unit Notation Level
-2 -1 0 +1 +2
Welding speed cm/min S 30 50 70 90 110
Arc voltage V U 19 21 23 25 27
Welding current A I 180 210 240 270 300
Shielding gas % SG 1 2 3 4 5

2.2.3 Design matrix

The design matrix chosen to conduct the experiment was a central composite rotatable design consisting in 32 coded conditions. The design matrix is constituted of a full replication of 24 (16) factorial design, 8 star points (one variable at its highest level +2 or lowest level -2 with all the other variables at the intermediate level 0) and 8 center points (all variables at the intermediate level 0). In this way, the 32 experimental runs allowed the estimation of linear, quadratic and linear-linear interactive effects of the welding parameters on the bead geometry. The design matrix is given in Table 4.
Table 4
Design matrix and measured or calculated values of the responses
Sample Input Factor Penetration Width Height Contact angle Hardness Dilution Heat input
S U I SG p, mm w, mm h, mm q, degree HR, HB D, % HI, J/mm
1 -1 -1 -1 -1 2.6 8.2 3.1 53.50 216 54 455.11
2 +1 -1 -1 -1 1.9 5.5 2.2 55.10 232 54 252.84
3 -1 +1 -1 -1 1.75 10.3 2.2 36.30 202 56 541.80
4 +1 +1 -1 -1 1.5 5.9 2.3 52.70 216 61 301.00
5 -1 -1 +1 -1 2.8 8.8 3.3 61.90 210 54 585.14
6 +1 -1 +1 -1 2.1 7.6 2.8 50.10 251 57 325.08
7 -1 +1 +1 -1 2.6 10.9 3.1 39.75 202 54 696.60
8 +1 +1 +1 -1 1.6 9.4 2.5 38.35 216 61 387.00
9 -1 -1 -1 +1 2.4 5.8 2.9 65.35 233 55 455.11
10 +1 -1 -1 +1 1.6 5.9 1.9 48.50 260 54 252.84
11 -1 +1 -1 +1 1.4 10.7 2.5 35.35 216 64 541.80
12 +1 +1 -1 +1 1.6 6.5 2.0 39.95 251 56 301.00
13 -1 -1 +1 +1 2.1 9.2 4.2 60.35 216 67 585.14
14 +1 -1 +1 +1 1.9 6.0 2.8 61.00 251 60 325.08
15 -1 +1 +1 +1 3.1 9.4 3.6 50.25 196 54 696.60
16 +1 +1 +1 +1 2.8 6.9 2.9 56.45 233 51 387.00
17 -2 0 0 0 3.0 12.8 3.3 51.50 183 52 949.44
18 +2 0 0 0 1.3 6.1 1.6 41.45 271 55 258.94
19 0 -2 0 0 1.8 6.6 3.2 63.90 233 64 336.14
20 0 +2 0 0 2.1 9.3 2.5 41.55 216 54 477.67
21 0 0 -2 0 1.3 6.7 1.6 41.50 251 55 305.18
22 0 0 +2 0 2.1 8.4 3.7 62.95 225 64 508.63
23 0 0 0 -2 1.9 7.3 3.1 64.40 225 62 406.90
24 0 0 0 +2 2.1 7.1 2.7 58.60 225 56 406.90
25 0 0 0 0 2.1 7.0 2.7 54.00 225 56 406.90
26 0 0 0 0 1.9 6.8 2.5 50.25 233 57 406.90
27 0 0 0 0 2.1 7.0 2.8 55.20 233 57 406.90
28 0 0 0 0 2.5 7.4 2.5 46.60 233 50 406.90
29 0 0 0 0 2.1 7.8 2.4 42.45 216 53 406.90
30 0 0 0 0 2.4 7.5 2.6 53.30 216 52 406.90
31 0 0 0 0 2.2 6.8 3.0 59.95 216 58 406.90
32 0 0 0 0 2.4 7.1 2.9 54.45 210 55 406.90

2.2.4 Experimental work according to the design matrix and record of the responses

The 32 experimental runs as described in the design matrix (Table 4) were realized for the four welding parameters selected as the input parameters. The bead on plate welds were subsequently cut and the cross section of the beads were polished and observed by optical microscopy. Figure 1 shows the photographs of the 32 specimens where the bead geometry could be studied. The profiles of the beads for the different sets of parameters were traced using an image analysis software so that the bead geometry could be measured accurately. Figure 1 also shows a schematic drawing of a bead on plate profile. For each single experimental run, the bead geometry was defined by measuring several out parameters: the width (w), the height (h), the penetration (p) and the contact angle (θ).
Fig. 1
Photographs of the bead profile in cross section for the 32 samples and schematic representation of the weld bead geometry
jwj-35-1-16f1.gif
The percentage of dilution, hereafter referred to as dilution, was calculated for