Effect of GTAW Process Parameters on Weld Bead Geometry of AA 7075-T6 Weldments

Table.2 Process parameters and their levels

The GTAW experiments are conducted as per the Taguchi orthogonal array (OA) L27. The rolled plates of AA7075-T6 aluminium alloy were cut in to the required size (300x150x3.46mm) by using a Jig saw cutting and grinding. It was investigated by Leijun Li et.al [9] that, the joint strength of the AL7075-T6 plate when welded with ER5356 filler wire with a 0°groove angle gives higher strength compared to 600 and 900 groove this is because the loss of Zn elements is less in making the groove. In this study we used single butt joint with 300 groove and 2mm root gap to fabricate AL7075-T6 plate. The plates to be welded were kept on steel temporary backing plate which having groove of size 7×0.9 mm and ends were clamped to maintain the alignment and gap. High purity (99.99%) argon gas was used as shielding gas.

Initially aluminium plates pickled with NaOH for 10 minutes to remove any grease, dust particles following by HNO3 for 15 minutes to remove the oxide layer. The initial joint configuration was obtained by securing the plate in position by tack welding. The direction of welding was normal to the rolling direction. Single pass welding procedure was applied to fabricate the joints.

To evaluate the quality of TIG welds, the measurements of the weld bead geometry are performed as shown in Fig.3. In this study, the Penetration (A), Face width (B), and Back width (C) of the weld bead are used to describe the weld pool geometry. The weld bead geometries were measured using Up-right reflected and transmitted metallurgical microscopy system; Make: VT Vacuum Technologies Pvt. Ltd; Model No. EQ- MSXJM213H-3M. Typical weld bead geometry is shown in Fig.3 and measured by a Metallurgical Microscope. Sample preparation and mounting was done as per ASTM E 3-11standard [13]. Two samples at a distance of 15 mm to each other are cut at the middle of the welded joint [14]. Samples being located at 15 mm behind the trailing edge of the crater at the end of the weld to eliminate the end effects (Fig.4). The samples are mounted using cold setting binder and cold setting compound as shown in Fig 5. The etching reagent Kellers was made by using chemicals 2 ml HF,3ml HCl, 20ml HNO3and 175ml H2O with an etching time of 30 sec. Weld pool geometry parameters were observed and recorded using a metallurgical microscope. The recorded specimen weld pool geometry quality characteristics namely Penetration (A), Face width (B), and Back width (C) are as shown in the Table 3.

1. The Utility concept.

   A client evaluates a product on a number of diverse quality characteristics. To be able to make a rational choice, these evaluations on different characteristics should be combined to give a combined index. Such a combined index represents the utility of a product. The overall utility of a product measures the usefulness of that product in the view of the client. The utility of a product on a particular characteristic measures the usefulness of that particular characteristic of the product. The overall utility of a product is the sum of utilities of each of the quality characteristics.

   Table.3 Experimental layout using an L27 orthogonal array and Experimental results for the weld pool geometry

   Expt.No	GTAW Process Parameters						Weld pool geometry (mm)
   	Ip	Ib	S	F	Pon	GF	A1	A2	B1	B2	C1	C2
   1.	195	93	200	4	40	9	4.5	4.3	7.0	6.8	3.5	3.6
   2.	195	93	300	6	50	10	5.0	4.6	8.5	8.6	5.0	4.9
   3.	195	93	400	8	60	11	4.5	4.2	7.0	7.2	3.0	3.1
   4.	195	98	200	6	50	11	4.5	4.6	7.0	6.9	5.0	4.9
   5.	195	98	300	8	60	9	4.5	4.2	8.0	8.1	3.0	3.1
   6.	195	98	400	4	40	10	2.0	2.1	6.0	6.2	1.0	1.2
   7.	195	103	200	8	60	10	5.0	4.9	8.5	8.2	3.5	3.4
   8.	195	103	300	4	40	11	2.0	1.9	6.5	6.3	0.1	0.2
   9.	195	103	400	6	50	9	4.5	4.3	6.5	6.3	0.1	0.1
   10.	200	93	200	6	60	10	4.6	4.4	7.0	6.8	6.5	6.3
   11.	200	93	300	8	40	11	2.0	1.9	6.0	5.9	0.2	0.2
   12.	200	93	400	4	50	9	1.5	1.4	7.0	6.9	0.3	0.2
   13.	200	98	200	8	40	9	2.0	1.8	7.0	6.8	0.5	0.4
   14.	200	98	300	4 /td>	50	10	5.0	4.8	8.0	7.8	2.0	2.2
   15.	200	98	400	6	60	11	4.5	4.3	6.5	6.4	3.5	3.4
   16.	200	103	200	4	50	11	4.6	4.7	6.0	6.0	3.0	3.2
   17.	200	103	300	6	60	9	5.0	4.8	5.5	5.5	4.0	4.5
   18.	200	103	400	8	40	10	3.0	2.9	6.5	6.3	0.1	0.2
   19.	205	93	200	8	50	11	4.5	4.4	5.5	5.5	4.0	3.8
   20.	205	93	300	4	60	9	4.5	4.4	7.5	7.2	6.0	6.1
   21.	205	93	400	6	40	10	4.3	4.2	6.0	5.9	3.0	3.1
   22.	205	98	200	4	60	10	4.0	3.9	9.0	8.8	6.5	6.4
   23.	205	98	300	6	40	11	4.5	4.4	7.0	6.8	1.5	1.4
   24.	205	98	400	8	50	9	5.0	4.9	6.0	5.9	3.5	3.3
   25.	205	103	200	6	40	9	4.5	4.6	7.5	7.4	4.5	4.4
   26.	205	103	300	8	50	10	4.5	4.6	8.5	8.4	6.5	6.3
   27.	205	103	400	4	60	11	4.0	3.9	8.0	7.9	6.5	6.3

   Thus if xi is the measure of effectiveness of the attribute i and there are n attributes evaluating the outcome space, then the joint utility function can be expressed as:

   In linear case, the function becomes:

   .(1)

   . (2)

   where, Wi, is the weightage assigned to the attribute i and the sum of the weightage for all attributes is equal to 1. If the overall utility is maximized the quality characteristics considered for evaluation of utility will automatically be optimized maximized or minimized whatsoever the case may be.

   Figure 3: Weld pool geometry; Penetration (A), Face width (B), Back width (C)

   Fig. 4. Marking for cutting specimen

   In this study for optimizing the process parameters, three quality characteristics were considered as a single characteristic by using above mentioned utility concept.

   Fig. 5. Specimens for measuring weld pool geometry

   The utility value (Single characteristics response) of each GTAW specimen has been calculated using the following relation: U(n,R)=PA(n,R)xWA+PB(n,R)xWB+PC(n,R)xWC ..(3)

   Where, n = trial number

   n = 1,2, . . ., 27

   R = repetition, R = 1, 2,

   WA, WB, WC are the weightage for weld pool geometry Penetration (A), Face width (B),Back width (C) respectively. From the previous literature survey it has been found that the quality characteristics Penetration (A), Face width (B), and Back width (C) are not equally important [12] and hence unequal weightage has been assigned but summation of all weightage must be equal to 1[12]. The weights assigned are:

   WA = 0.50, WB=0.35, WC=0.15

   PA, PB , PC are the preference scale for weld pool geometry Penetration (A), Face width (B),Back width (C) respectively. These values calculated as given below;

   If a log scale is chosen the preference ) is given by Equation

   . (4)

   Where = any value of quality characteristic or attribute i

   = minimum acceptable value of quality characteristic or attribute i K = a constant

   At optimum value ) of attribute i, Pi= 9 So, K at

   optimal value of is given by

   . (5)

   Preference scale calculation for A

   = Maximum acceptable value considering the 27 experiments =4.5 mm (assumed)

   = Minimum acceptable value considering the 27 experiments =2 mm (assumed)

   (All the A values in Table 3 are in between 1.5 to 5)

   Using these values and the Equations 4 & 5, the following preference scale for A has been constructed;

   . (6)

   Preference scale calculation for B

   = Minimum acceptable value considering the 27 experiments =6.0 mm (assumed)

   = Maximum acceptable value considering the 27 experiments =8.0 mm (assumed)

   (All the B values in Table.3 are in between 6 to 9.0)

   Using these values and the Equations 4 & 5, the following preference scale for B has been constructed;

2. Results and discussion.

   1. Single response optimization and its confirmation. Effect on penetration (A)

      The penetration (A) was considered as the quality characteristic with the concept of "the larger-the-better". The analysis was made using the popular software specifically used for design of experiment applications known as MINITAB 15. The average values of penetration

      (A) for each parameter at levels 1, 2 and 3 for raw data are plotted in Fig.6 From the this Fig. it clears that peak current (Ip), frequency (F), and pulse on time (Pon) are the most significant process parameters compared to other process parameters.

      Fig.6 shows that as the increase in Peak current (Ip) up to 200A the penetration (A) value decreases and penetration (A) value increases with further increase in Ip value. This is because at low Ip up to 200 Amp the heat input is less and it is not sufficient to melt base metal with the filler material. The Peak current (Ip) more than 200A gives more heat and it melts the base metal with filler metal completely and gives full penetration (A). So Peak current (Ip) plays an important role in the determination of penetration (A) value. As the base current (Ib) increases the up to 98 A the penetration (A) value go on increasing and after 98 A further increase in Ib value there is decrease in penetration (A) value. As the base current (Ib) increases higher the value of penetration (A). This is because the Ib is mainly helpful in maintaining continuous arc during welding [13], so it melts more base metal and filler material in narrow direction so penetration (A) increases. Though from Fig.7 Ib process parameter not as significant as other parameters. As the welding speed (S) decreases the penetration (A) value go on increasig this is mainly because, lesser the speed complete melting of submerged filler material and base metal leads to complete diffusion of filler metal in to base metal and forms a perfect joint. As the Frequency (F) increases penetration (A) go on increasing proper diffusion of filler metal in to the base metal so the penetration (A) value increases. But further increase in the F from 6Hz more penetration than required leads to undercut and decrease in penetration (A) value.

      .. (7)

      Preference scale calculation for C

      = Minimum acceptable value considering the 27 experiments =0.1 mm (assumed)

      = Maximum acceptable value considering the 27 experiments =6.0 mm (assumed)

      (All the C values in Table.3 are in between 0.1 to 6.5)

      Using these values and the Equations 4 & 5, the following preference scale for C has been constructed;

      . (8)

      The utility values with mean are calculated and given in Table 4.

      Table. 4 Utility Data Based on Quality Characteristics A,B and C with its Mean.

      Expt.no	Utility 1	Utility 2	Mean Utility
      1.	6.13881	6.19467	6.16674
      2.	4.48002	3.89601	4.18801
      3.	6.18962	5.48759	5.83861
      4.	6.02124	6.30738	6.16431
      5.	4.72761	4.19801	4.46281
      6.	3.74038	3.59197	3.66618
      7.	4.59759	4.88847	4.74303
      8.	3.62301	3.45213	3.53757
      9.	8.12215	8.21209	8.16712
      10.	6.05669	6.13775	6.09722
      11.	4.27090	4.17034	4.22062
      12.	0.85340	0.76181	0.80760
      13.	2.28110	2.08749	2.18430
      14.	5.44582	5.46512	5.45547
      15.	6.95020	6.87728	6.91374
      16.	7.99932	8.09737	8.04835
      17.	9.31977	9.05446	9.18712
      18.	5.87258	5.79819	5.83538
      19.	8.73522	8.62745	8.68133
      20.	5.20575	5.52257	5.36416
      21.	7.62515	7.66781	7.64648
      22.	2.52969	2.64039	2.58504
      23.	6.41810	6.63354	6.52582
      24.	8.41112	8.50245	8.45678
      25.	5.30058	5.57689	5.43874
      26.	3.80898	4.07080	3.93989
      27.	3.81927	3.82683	3.82305

      Ip

      Main Effects Plot for Means(WP-A)

      Data Means

      Ib

      S

      4.5

      4.0

      3.5

      3.0

      195

      200

      F

      205

      93

      98

      Pon

      103

      200

      300

      GF

      400

      4

      6

      8

      40

      50

      60

      9

      10

      11

      4.5

      4.0

      3.5

      3.0

      Mean of Means

      Fig.6 Effects of Process Parameters on WP-A (Raw Data)

      Though from Fig.6 Ib process parameter not as significant as other parameters. As the welding speed (S) decreases the penetration (A) value go on increasing this is mainly because, lesser the speed complete melting of submerged filler material and base metal leads to complete diffusion of filler metal in to base metal and forms a perfect joint. As the Frequency (F) increases penetration (A) go on increasing proper diffusion of filler metal in to the base metal so the penetration (A) value increases. But further increase in the F from 6Hz more penetration than required leads to undercut and decrease in penetration (A) value.

      From the Table 4 it was found that Gas flow rate (GF), Base current (Ib) and welding speed (S) are lesser

      percentage of contribution (P%) i.e. non significant process parameters for penetration (A). As penetration

      5

      Ip

      4

      5

      Ib

      93

      98

      103

      Ip

      195

      200

      205

      (A) is the higher the better type quality characteristic, it can be seen from Fig.6 that the III level of Ip , III level of Ib, I level of S, II level of F, III level of Pon and II level of GF provide maximum value of penetration (A).

      Interaction Plot for Means(WP-A)

      Data Means

      93

      98

      103

      3

      3

      3

      195

      200

      205

      200

      300

      400

      S

      4

      5

      Ib

      4

      S

      200

      300

      400

      Fig. 7 Effects of Interactions on WP-A (Raw Data)

      The optimal GTAW process parameters for maximum penetration (A) are Ip-205A , Ib-103A, S-200mm/min, F- 6Hz, Pon=60%, and GF-10 lit/min. Fig. 7 reveal that the interactions between Peak current (Ip), Base current (Ib), Welding speed (S) affect highly the output responses since the responses are not parallel to each other. So our suspected interactions are significant on responses.

      Effect on Face width (B)

      The face width (B) was considered as the quality characteristic with the concept of "the smaller-the-better". The average values of face width (B) for each parameter at levels 1, 2 and 3 for raw data are plotted in Fig.8. From this Fig it clears that Peak current (Ip), welding speed (S), pulse on time (Pon) and gas flow rate (GF) are the most significant process parameters compared to other process parameters. Fig.8. shows that as the increase in Peak current (Ip) up to 200A the face width (B) value decreases and face width (B) value increases with further increase in Ip value. This is because at low Ip up to 200 Amp the heat input is less and it is not sufficient to melt base metal with the filler material. The Peak current (Ip) more than 200A gives more heat and it melts the base metal with filler metal completely and increases face width (B). So Peak current (Ip) play an important role in the determination of face width (B) value. As the base current (Ib) increases the up to 98 A the face width (B) value go on increasing and after 98 A further increase in Ib value there is decrease in face width (B) value. As the base current (Ib) increases higher the value of face width (B). This is because the Ib is mainly helpful in maintaining continuous arc during welding [13], so it melts more base metal and filler material in narrow direction so face width (B) increases. On the other hand from Fig. 8 Ib process parameter not as significant as other parameters.

      As the higher welding speed (S) lesser the time for the contact between arc and base material with submerged filler material, this leads to lesser face width (B). The decrease in welding speed (S) increases the face width (B) this is because more time for contact between arc and face of base metal with submerged filler material. As the

      frequency (F) increases face width (B) go on decrasing this is because more pulse rate and more heat contact in narrow direction. Similar observation made by investigators [13] in welding of AISI 304L.

      Table 4 Analysis of Variance for Means (A)

      Source	DF	Seq SS	Adj SS	Adj MS	F	P %
      Ip	2	3.5150	3.5150	1.7575	2.78	11.2563
      Ib	2	0.2850	0.2850	0.1425	0.23	0.9126
      S	2	1.5439	1.5439	0.7719	1.22	4.9441
      F	2	4.8106	4.8106	2.4053	3.81	15.4054
      Pon	2	8.7072	8.7072	4.3536	6.89	27.8838
      GF	2	0.2839	0.2839	0.1419	0.22	0.9091
      Ip*Ib	4	4.8067	4.8067	1.2017	1.90	15.3929
      Ip*S	4	2.0311	2.0311	0.5078	0.80	6.5043
      Ib*S	4	3.9794	3.9794	0.9949	1.57	12.7435
      Residual Error	2	1.2639	1.2639	0.6319		4.0474
      Total	26	31.2267				100
      S = 0.7949 R2 = 96.0%

      7.50

      7.25

      7.00

      6.75

      6.50

      Ip Ib S

      From the Table 5 it was found that Ip,Ib,S, and F are lesser percentage of contribution (P%) i.e. non significant process parameters for face width (B). From these tables, it is also clear that pulse on time (Pon), and interaction factors are more significant compare to individual process parameters. These are significantly affected both the mean and the variation in the face width (B) values. As face width (B) is the lower the better type quality characteristic, it can be seen from Fig.9 that the II level of Ip , I level of Ib, III level of S, II level of F, I level of Pon and III level of GF provide minimum value of face width (B). The optimal GTAW process parameters for minimum face width (B) are Ip-205A , Ib-103A, S-200mm/min, F- 6Hz, Pon=60%, and GF-10 lit/min. Fig.9 reveal that the interactions between Peak current (Ip), Base current (Ib), Welding speed (S) affect highly the output responses since the responses are not parallel to each other. So our suspected interactions are significant on responses.

      Effect on Back width (C)

      The back width (C) was considered as the quality characteristic with the concept of "the smaller-the-better". The average values of back width (C) for each parameter at levels 1, 2 and 3 for raw data and S/N data are plotted in Fig. 10. From the Fig.10 it clears that Peak current (Ip), welding speed (S), pulse on time (Pon) are the most significant process parameters compared to other process parameters.

      Main Effects Plot for Means (WP-B)

      Data Means

      4

      6

      8

      40

      50

      60

      9

      10

      11

      Ip

      7

      8

      Ib

      93

      98

      103

      Ip

      195

      200

      205

      7.50

      7.25

      7.00

      6.75

      6.50

      400

      300

      200

      103

      98

      93

      205

      200

      195

      F Pon GF

      Mean of Means

      Fig. 8 Effects of Process Parameters on WP-B (Raw Data)

      Interaction Plot for Means (WP-B)

      Data Means

      93

      98

      103

      6

      8

      8

      6

      6

      195

      200

      205

      200

      300

      400

      S

      7

      Ib

      7

      S 200

      300

      400

      Fig.9 Effects of Interactions on WP-B (Raw Data) Fig.10 shows that as the increase in Peak current (Ip)

      up to 200A the back width (C) value decreases and back width (C) value increases with further increase in Ip value. This is because at low Ip up to 200 Amp the heat input is less and it is not sufficient to melt the metal and reach the root. The Peak current (Ip) more than 200A gives more heat and it melts the base metal with filler metal completely and reach the root with more back width (C). So Peak current (Ip) play an important role in the

      determination of back width (C) value. As the base current (Ib) increases the up to 98 A the back width (C) value go on increasing and after 98 A further increase in Ib value there is decrease in back width (C) value. As the base current (Ib) increases higher the value

      of back width (C). This is because the Ib is mainly helpful in maintaining continuous arc during welding [13], so it

      melts more base metal and filler material towards the root so back width (C) increases. However from Fig.10 Ib process parameter not so significant as other parameters. As the higher welding speed (S) lesser the time for the contact between arc and base material with submerged filler material, this leads to lesser back width (C).

      Table 5 Analysis of Variance for Means (WP-B)

      Source	DF	Seq SS	Adj SS	Adj MS	F	P %
      Ip	2	2.3735	2.37352	1.18676	100.92	9.8462
      Ib	2	0.4891	0.48907	0.24454	20.80	2.0289
      S	2	2.0830	2.08296	1.04148	88.57	8.6411
      F	2	0.6430	0.64296	0.32148	27.34	2.6674
      Pon	2	3.2096	3.20963	1.60481	136.47	13.3146
      GF	2	4.0946	4.09463	2.04731	174.10	16.9860
      Ip*Ib	4	6.1348	6.13481	1.53370	130.43	25.4495
      Ip*S	4	1.4959	1.49593	0.37398	31.80	6.2055
      Ib*S	4	3.5587	3.55870	0.88968	75.66	14.7628
      Residual Error	2	0.0235	0.02352	0.01176		0.0974
      Total	26	24.1057				100
      S = 0.1084 R2 = 99.9%

      195

      Mean of Means

      The decrease in welding speed (S) increases the back width (C) this is because more time for contact between arc and face of base metal with submerged filler material. As the frequency (F) increases back width (C) go on decreasing this is because more pulse rate and more heat contact in narrow direction. Similar observation made b investigators [13] in welding of AISI 304L.

      From the Table 6 it was found that gas flow rate (GF), base current (Ib) and frequency (F) are lesser percentage of contribution (P%) i.e. non significant process parameters for back width (C). From these tables, it is also clear that pulse on time (Pon), welding speed (S), and peak current (Ip), and interaction (Ip*Ib) significantly affect both the mean and the variation in the back width (C) values.

      As back width (C) is the smaller the better type quality characteristic, it can be seen from Fig.10 that the II level of Ip , II level of Ib, III level of S, III level of F, I level of Pon and I level of GF provide minimum value of back width (C). The optimal GTAW process parameters for minimum back width (C) are Ip-200A , Ib-98A, S- 400mm/min, F-8Hz, Pon=40%, and GF-9 lit/min. Fig.11 reveal that the interactions between Peak current (Ip), Base current (Ib), Welding speed (S) affect highly the output responses since the responses are not parallel to each other. So our suspected interactions are significant on responses.

      Main Effects Plot for Means (WP-C)

      Data Means

      5

      4

      3

      2

      Ip

      Ib

      S

      4

      6

      8

      40

      50

      60

      9

      10

      11

      5

      4

      3

      2

      400

      300

      GF

      200

      103

      98

      Pon

      93

      205

      200

      F

      Fig. 10 Effects of Process Parameters on WP-C (Raw Data)

   2. Multi response optimization using Taguchi and Utility concept and its confirmation.

Fig. 12 and 13 show graphically the effect of the six GTAW Process Parameters and its interactions on, Utility (A,B,C). The data from Table 4 are plotted in Fig.12 it is clear from the Fig. that GTAW process parameters at level Ip-3,Ib-3,S-1, F-2, Pon-2 and GF-3 yield best performance in terms of Utility value within the selected range of process parameters. Fig.13 reveal that the interactions between Peak current (Ip), Base current (Ib), Welding speed (S) affect highly the output responses since the responses are not parallel.

Interaction Plot for Means (WP-C)

Data Means

93 98 103

6

4

Ip

Ip 195

200

205

2

6

Ib 93

Ib

4 98

103

2

6

4

S

S 200

300

400

2

195 200 205

200 300 400

Fig.11` Effects of Interactions on WP-C (Raw Data) Table 6 Analysis of Variance for Means (WP-C)

4.4 Confirmation of experiments

The Analysis of Variance (ANOVA) for mean of Utility values (A, B and C) is given in Table 7. By observing percentage of contribution in the Table 7 it clears that, among all the process parameters Frequency (F) 21.351% is the most significant parameter. And also it is found that interactions, especially (Ip*Ib) 31.465% and (Ib*S) 18.755% are most significant, in determining Utility values, so selected interaction is most affective in analysis. And for Residual Error percentage of contribution is 4.537%. The percent of contribution due to error provides an estimate of adequacy of the experiment and should not be more than 50%. If the percent contribution due to error is low (15% or less), then it is assumed that no important factors were omitted from the experiment [15].Although factors Ip,Ib and S do not show significant effect but significant interaction (Ip*Ib), (Ip*S) and (Ib*S) is observed for Utility values (A, B and C) as shown in Table

7 and Fig.13.So, it is recommended to use the process parameters at level Ip3, Ib3, S1, F2, Pon2 and GF3 yield best performance in terms of Utility value i.e. to get maximum penetration (A), minimum face width (B) and minimum back width (C).

The optimal combination of GTAW process parameters has been determined in the previous analysis. Still the final step is to predict and verify the improvement of the observed values through the use of the optimal combination level of GTAW process parameters. In the WP-A response Ib, S, and GF are least significant compared to other process parameters. But the interactions Ip*Ib and Ib*S are significant so process parameters Ib and S also considered in prediction equation.

Ip

Main Effects Plot for Means

Data Means

Ib

S

6.5

6.0

5.5

5.0

4.5

195

200

F

205

93

98

Pon

103

200

300

GF

400

4

6

8

40

50

60

9

10

11

6.5

6.0

5.5

5.0

4.5

Mean of Means

Fig. 12 Effect of GTAW process parameters on Utility values (A,B &C) Raw Data

Ip

6

8

103

98

93

Interaction Plot for Means

Data Means

Ip

195

200

205

. (11)

8

4

Ib

93

98

103

By combining like terms, the prediction equation reduces to

Ib

6

4

8

S 200

300

400

Where,

S

6

= overall mean of WP-B = 6.97 mm

. (12)

4

195

200

205

200

300

400

Fig. 13 Effects of GTAW Interactions on Utility values (A,B &C) Raw Data

Considering significant factors the predicted optimal value calculated by the following equations:

All remaining values are determined from the plot as shown in Fig.8 and Fig. 9.

Similarly for predicted optimal value for WP-C

(13)

By combining like terms, the prediction equation reduces to

Where,

. = overall mean of WP-C=6.87mm

. (14)

(9)

By combining like terms, the prediction equation reduces to

All values are determined from the plot as shown in Fig.10 and Fig. 11.

Table 9 Optimal value as per prediction equation

(10)

Where,

= overall mean of WP-A = 3.96mm

And remaining values are determined from the plot as shown in Fig.6 and Fig.7.Substituting the values of various terms in the above equation no.10 and its values are given in Table 9. A experimental set up with GTAW process parameters levels are III level of Ip , III level of Ib, I level of S,II level of F, and III level of Pon provide maximum value of WP-A, non significant process parameters considered at economical value. Above prediction equation is considered to predict the WP-A value.

The predicted optimal value for the remaining weld pool geometry responses (WP-B, WP-C) calculated by the following equations:

Table 7. Analysis of Variance (ANOVA) for Means of Utility values (A, B and C)

The optimum combination is observed in weld pool geometry responses i.e. A, B, and C are given in the following Table 9. For validations of the optimum results, experiments are conducted as per the optimum conditions and weld pool geometry are evaluated and the averages of

two test results are presented in Table 10. It is observed that, experimental values were closer to the optimum values.

The predicted mean for Utility value can be calculated with the help of following prediction equation

. (15)

By combining like terms, the prediction equation reduces to

. (16)

Above values are determined from the Table. 4 and plot as shown in Fig.13 and 14. Substituting the values of various terms in the above equation no. 10 and it is found to be

Prediction Utility . Two confirmation experiments have been conducted at the optimum settings of the process parameters i.e. Ip=205A, Ib=103A, S=200mm/min, F=6Hz, Pon=50% and GF=11 lit/min. Two specimens at optimal condition as shown in the Fig.15.The average values for weld pool geometry are A=3.7mm, B=5.2mm, and C=2.5mm.

The actual Utility value of the weld pool geometry has been calculated using the equation 3 and it is found that

µABC

=8.390. The predicted utility value and actual utility values are very close together so the adequacy of the Utility value model of GTAW specimen as given below (Eqn.3) is justified and the results are validated.

U (n, R) = PA (n, R) x WA + PB (n, R) x WB + PC (n, R) x WC

values with initial and optimal process parameters it can be seen that weld pool geometry are greatly improved by optimization technique.

5 CONCLUSIONS

The present work is concerned to determine the optimum setting of process parameters for multi-response optimization during GTAW of AA7075T6 Aluminium alloy. On the basis of Taguchi approach and Utility concept, a model was developed to attain this. The L27 OA was used for experimental planning. In multi-response, the analysis of means establishes that a combination of higher levels of Peak current, Base current, Gas flow rate and lower level of welding speed and intermediate level of Pulse on time, and Frequency is essential to achieve simultaneous maximization of Penetration and minimization of Face width and Back width. Based on the ANOVA the most statistical significant

Table 10 Validation of optimum results

and percent contribution of the process parameters for multiple performances is, Frequency (F) is the most significant parameter. And also it is found that interactions, especially (Ip*Ib) and (Ib*S) are most significant, in determining Utility values, so interaction consideration is most affective in analysis. The validation experiment confirmed that the adequacy of Utility value model is justified. It is found that the proposed model based on Taguchi approach and Utility concept is useful and provides an appropriate solution for multi-response optimization problems.

ACKNOWLEDGEMENTS

The authors are grateful to the Department of Mechanical Engineering, VTU Belgaum, India for extending the facilities of Metal Joining Laboratory and Materials Testing Laboratory to carry out this investigation. The authors also wish to express their sincere thanks to AICTE, New Delhi for the financial support to carry out this investigation through sponsored project No.8023/RID/RPS-116 (Pvt).2011-12.The authors also thankful to Dr.B.V.R.Ravi Kumar, Professor in V.N.R.V.J.I.E.T, Hyderabad, India, for his valuable suggestions, guidance and discussion. And also thankful to Dr Mrithyunjay Dodamani Asst.Prof.NITK Suratkal India for giving valuable suggestion for applying Taguchi technique.

As per the trial and data hand book the usual GTAW process parameters (Initial process parameters) for welding GTAW of AA 7075-T6 alloys are Ip-200A,Ib-93A,S- 200mm/min, F-4Hz,Pon-50%,GF-9 lit/min . With these process parameters the average values for weld pool geometry are A=4.7mm, B=6.2mm, and C=3.5mm. And the utility value is µABC =6.030. So by comparing utility

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