INTRODUCTION:

Welding is a process in which two or more parts are joined permanently at their touching surfaces by a suitable application of heat and/or pressure. Often a filler material is added to facilitate coalescence. The assembled parts that are joined by welding are called a weldment. Welding is primarily used in metal parts and their alloys.

Welding processes are:

1) Fusion welding: In this process, base metal is melted by means of heat. Often, in fusion welding operations, a filler metal is added to the molten pool to facilitate the process and provide bulk and strength to the joint. Commonly used fusion welding processes are: arc welding, resistance welding, oxyfuel welding, electron beam welding and laser beam welding.

2) Solid-state welding: In this process, joining of parts takes place by application of pressure alone or a combination of heat and pressure. No filler metal is used. Commonly used solid-state welding processes are: diffusion welding, friction welding, ultrasonic welding.

CLASSIFICATION OF WELDING PROCESSES ON THE BASIS OF TECHNICAL FACTORS:

A weld joint can be developed just by melting of edges (faying surfaces) of plates or sheets to be welded especially when thickness is lesser than 5 mm thickness. A weld joint developed by melting the fating surfaces and subsequently solidification only (without using any filler metal) is called “autogenous weld”. Thus, the composition of the autogenous weld metal corresponds to the base metal only. However, autogenous weld can be crack sensitive when solidification temperature range of the base metal to be welded is significantly high (750^o - 100^oC). Following are typical welding processes in which filler metal is generally not used to produce a weld joint.Laser beam welding, Electron beam welding, Resistance welding,Friction stir welding etc.

However, for welding of thick plates/sheets using any of the following processes filler metal can be used as per needs according to thickness of plates. Application of autogenous fusion weld in case of thick plates may result in concave weld or under fill like discontinuity in weld joint. The composition of the filler metal can be similar to that of base metal or different one accordingly weld joints are categorized as homogeneous or heterogeneous weld, respecting.

In case of autogenous and homogeneous welds, solidification occurs directly by growth mechanism without nucleation stage. This type of solidification is called epitaxial solidification. The autogenous and homogeneous welds are considered to be of lesser prone to the development of weld discontinuities than heterogeneous weld because of a uniformity in composition and (b) if solidification largely occurs at a constant temperature. Metal systems having wider solidification temperature range show issues related with solidification cracking and partial melting tendency. The solidification in heterogeneous welds takes place in conventional manner in two stages i.e. nucleation and growth.

OBJECTIVE:

This research work does the study of submerged arc welding process. The analysis of parameters for the submerged arc welding process. And the Implementation of Taguchi method for quality improvement in the process is achieved with the regression analysis. The Taguchi method has been implemented in order to improve the quality of the submerged arc welding process. The research work has been used on the following aspect:

To study the submerged arc welding process.

To Implementation of Taguchi method for quality improvement.

To perform Regression Analysis

IMPORTANT PARAMETERS IN SUBMERGED ARC WELDING:

1. Arc voltage

The arc voltage plays a vital role in determining the width, shape and to some extend the penetration of the arc. High arc voltage used for joining flat sheet in an I-joint will produce a wider weld. While in case of fillet radii, X-joint and V-joint high arc voltage will result in a concave weld. Although there will be a risk of undercutting and hardly removable slag. While low arc voltage will result in a round weld in I-joints and V-joints, while in case of fillet radii and X-joints low arc voltage will result in a convex weld. Problem of hardly removable slag also persist here.

2. Welding current:

Welding current is a parameter of greatest importance in terms of penetration. The setting of current depends on the type of joint and the thickness of the metal. Although the width of bead is no effected by the current but has too high current can result in burning of beads while too low current will result in insufficient penetration which will cause root defects.

3. Welding speed:

The welding speed is also a important parameter that effects penetration. In general welding speed is inversely proptonial to the penetration depth. That is if the speed is increased, penetration will be decreased and narrower weld will be obtained while if the speed is reduced, increased penetration and wider weld will be obtained (cf. manual welding). However, reducing the welding speed to a certain limit depending on the actual value of the current will have the opposite effect. If the welding speed is changed while the penetration is constant then adjustment of the welding current is needed to be done for compensating the effect. is necessary to compensate by, i.e. to increase or decrease it.

4. Wire diameter:

For a given current, change in current density will be observed when there is a change in wire size. A reduction in penetration is observed with wires of greater diameter. Risk of burning at the bottom of the weld is sometimes also observed. In addition to this stability of arc will be adversed and arc will become more difficult to strike.

5. Submerged Arc Welding Methods:

Single-wire welding: In this type of method diameter of filler wires varies from 1.2 mm to 6 mm and welding currents ranges from 120–1500 A.

Twin-arc welding: In this type of method two electrodes held in a special holder are used for maintaining arc between them. Use of double wire has now become more common because of higher productivity. Increased deposition rate in comparison with that of a single-wire machine without very much capital cost can be obtained using twin arc welding method. Since the equipment uses a single wire feed unit and the welding current will be shared equally between the electrodes.

EXPERIMENTATION:

In the present work, experimental dataset for validation of the proposed GA-Taguchi model has been obtained from literature [6]. Eight sets of experiments on sub-merged arc welding of 100mmx50mmx12mm thick mild steel plates have been conducted based on design of ex-periments with semiautomatic saw-1000 setup. During experimental design, 2 levels of welding current, A (C), arc voltage, V (V), welding speed, mm/min(S), electrode stick out, mm (ESO) has been considered as independent operating variables. Corresponding output variables measured are as weld bead width, mm (BW) of top sur-face and weld bead hardness, HRC (H) by Rockwell hardness test machine. The experimental dataset and corresponding levels of the process parameter have been given in Table 2 and Table 3.

CALCULATIONS AND ANALYSIS:

Table:1. Experiment Welding Parameter Levels

Symbol	Welding parametres	Level 1	Level 2
C	Welding current, A	300	360
V	Arc voltage, V	25	27
S	Welding speed, mm/min	900	1000
ESO	Electrode stick out, mm	19	25

Taguchi Method

Taguchi’s philosophy is an efficient tool for the design of high quality manufacturing system. Dr. Genichi Taguchi, a Japanese quality management consultant, has developed a method based on orthogonal array experiments, which provides much- reduced variance for the experiment with optimum setting of process control parameters. Orthogonal array (OA) provides a set of well- balanced (minimum experimental runs) experiments and Taguchi’s signal-to-noise ratios (S/N), which is logarithmic functions of desired output serve as objective functions for optimization. This technique helps in data analysis and prediction of optimum results. In order to evaluate optimal parameter settings, Taguchi method uses a statistical measure of performance called signal-to-noise ratio. The S/N ratio takes both the mean and the variability into account. The S/N ratio is the ratio of the mean (signal) to the standard deviation (noise). The standard S/N ratios generally used are as follows: Nominal is best (NB), lower the better (LB) and higher the better (HB). The optimal setting is the parameter combination, which has the highest S/N ratio.

Significant factors are:

Step 1: Identification of important process variables.

Step 2: Development of process plan.

Step 3: Conducting experiments as per the plan.

Step 4: Recording the responses.

Step 5: Testing the welded job.

Step 6: Finding out the optimized values of the parameters

Step 7: Presenting the main and substantial effects of process parameters.

Experimentation: Taguchi Method

The Taguchi method uses a special design of orthogonal arrays to study the entire parameter space with only a small number of experiments. The greatest advantage of this method is the saving of effort in conducting experiments; saving experimental time, reducing the cost, and discovering significant factors quickly. Levels of process parameters identified are shown in Table 1. The experiment was conducted at the Welding Centre of “K. R. Casting”, Nagpur with the following set up.automatic SAW equipment with a constant voltage, rectifier type power source with a 1000A capacity was used to join the two mild steel pipes of size12000mm (length) X 1250 mm (width) X 12 mm (thickness) with a V angle of 30o to 45o ,4 mm root height and 0.75 mm gap between the two plates. Copper coated Electrode Auto melt EH-14 wire size: 3.20 mm diameter, of coil form and basic fluoride type granular flux were used.Text Font of Entire Document.

Table :2. Welding parameters with different levels

Symbol	Welding parametres	Level 1	Level 2	Level 3
A	Welding current (amp)	500	600	700
B	Arc voltage (volts)	31	32	33
C	Welding speed (mm/min)	450	550	650
D	Electrode stick out(mm)	28	30	32

Level Taguchi Orthogonal Array :

Taguchi’s orthogonal design uses a special set of predefined arrays called orthogonal arrays (OAs) to design the plan of experiment. These standard arrays stipulate the way of full information of all the factors that affects the process performance (process responses). The corresponding OA is selected from the set of predefined OAs according to the number of factors and their levels that will be used in the experiment. Below Table No.2 shows L9 Orthogonal array.

Experimental layout using L9 orthogonal array

Trial No.	Welding Current	Arc Voltage	Welding Speed	Electrode Stick Out
1	1	1	1	1
2	1	2	2	3
3	1	3	3	2
4	2	1	2	3
5	2	2	3	2
6	2	3	1	1
7	3	1	3	2
8	3	2	2	1
9	3	3	1	3

Multiple Regression Analysis

Multiple regression analysis technique is used to ascertain the relationships among variables. The most frequently used method among social scientists is that of linear equations. The multiple linear regression take the following form:

Where Y is the dependent variable, which is to be predicted;X1,X 2,X3 . . . . . . . .X k are the known variables on which the predictions are to be made and a, b1, b2, b3,……….bk are the co- efficient, the values of which are determined by the method of least squares. Multiple regression analysis is used to determine the relationship between the dependent variables of bead width and weld bead hardness with welding current, arc voltage, welding speed, and electrode stick out. The regression analysis was done by Minitab 15 version. After completion of the welding process the welded specimen has been kept properly on a table and the weld bead width has measured with the help of a measuring scale. Similarly S/N ratio for weld bead width has been found separately. The largest signal to noise ratio (mean) is considered to be the optimum level, as a high value of signal to noise ratio indicates that the signal is much higher than the random effects of the noise factors. Table 3 shows the mean S/N ratios for the welding current, arc voltage, welding speed and electrode stick out. From the Table 3, it is evident that largest signal to noise ratio (average) is the optimum level, because a high value of signal to noise ratio indicates the signal is much higher than the random effects of the noise factors. The largest S/N avg for parameter is indicated by Optimum in the Table 5. Results shown in table 5, it can be stated that contribution of current is maximum and contribution of speed and electrode stick out are minimum in optimum bead width.

Table :3. Training data sets

Trial No.	Welding Current (Amps)	Arc Voltage (Volts)	Welding Speed mm/min	Electrode Stick Out (mm)	Bead Width Measured (mm)
1	500	31	450	28	14
2	500	32	550	32	14
3	500	33	650	30	15
4	600	31	550	32	16
5	600	32	650	30	16
6	600	33	450	28	17
7	700	31	650	30	16
8	700	32	550	28	17
9	700	33	450	32	17

Table :4. Experimental layout using L9 orthogonal array and S/N ratio for weld bead width

Trial No.	WeldingCurrent (Amps)	Arc Voltage (Volts)	WeldingSpeed mm/min	Electrode Stick Out (mm)	BeadWidth Measured (mm)	Meansquare deviation	S/N ratio (dB)
1	500	31	450	28	14	196	22.92
2	500	32	550	32	14	196	22.92
3	500	33	650	30	15	225	23.52
4	600	31	550	32	16	256	24.08
5	600	32	650	30	16	256	24.08
6	600	33	450	28	17	289	24.60
7	700	31	650	30	16	256	24.08
8	700	32	550	28	17	289	24.60
9	700	33	450	32	17	289	24.60

RESULT:

Table : Mean S/N ratio for weld bead width

Weld Parameters	Levels	Mean S/N ratio
Welding Current	Level 1(500)	23.12
	-----------------	-------
	Level 2 (600)	24.25
	---------------	------
	Level 3(700)	24.42
Arc Voltage	Level 1(31)	23.69
	----------------	------
	Level 2 (32)	23.86
	---------------	-------
	Level 3(33)	24.24
Welding Speed	Level 1(450)	24.04
	----------------	-------
	Level 2 (550)	23.86
	------------------	-------
	Level 3(650)	23.89
Electrode Stick Out	Level 1(28)	24.04
	-------------	------
	Level 2 (30)	23.89
	---------------	-------
	Level 3(32)	23.86

CONCLUSION:

An experiments was carried out to establish the relationship between process variables and optimization tools are used to find an optimal solution. It is observed that the developed of model is a powerful tool in experimental welding optimization, even when experimenter does not have to model the process. A Taguchi orthogonal array, the signal to noise (S/N) ratio and analysis of variance were used for the optimization of welding parameters. A confirmation experiment was also conducted and verified the effectiveness of Taguchi optimization method.

A test sample, having same size and dimension as per earlier specification has been taken and performed welding at the optimum predicted process parameters at path, welding current, 600A, Arc voltage 32 V, Welding speed 450mm/min and Electrode stick out 28 mm. A protective slag over the weld pool is formed by melting of flux. During cooling slag helps to keep oxygen offweld bead. Flux produces protective gas around well pool. Welding uses high speed and quality (4 – 10x SMAW) and 300 – 2000 amps (440 V) for general purpose. On metal transfer in SAW very less work has been reported, which influences the metallurgy and chemical composition of weld metal, weld bead geometry, arc stability as well as strength of the weld. On current voltage transient study very less work in submerged arc welding has been reported due to current voltage many characteristics are influence. The amount of heat generated at work piece and welding electrode is affected by polarity change. Thus influences the metal, weld bead, deposition rate, HAZ and mechanical properties of the weld metal.

a. It is concluded that Decrease in welding voltage, decrease in welding current and increase in welding speed up to limit will decrease weld bead width.

b. It is concluded that Decrease in welding voltage, decrease in welding current and increase in welding speed up to limit will decrease weld bead width.

c. Increase in welding voltage, increase in welding current and decrease in welding speed up to limit will increase the quality of the weld bead hardness.

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Received on 09.04.2018 Accepted on 28.04.2018

Int. J. Tech. 2018; 8(1): 41-46

DOI:10.5958/2231-3915.2018.00007.X