Temperature Measurement During Welding
Chapter 4 Experimental Investigation and Characterization of Welds
4.4 Results and Discussions
4.4.2 From Different Multi Response Analysis Techniques
4.4.2.6 ANOVA Analysis and Confirmation Experiments
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material mixing. So there is an appropriate welding speed for obtaining good welded joints.
DT is required to plasticize the material initially and increase the temperature of the workpiece to a level at which the joining process can be started. So, lesser DT caused inadequate heat generation whereas too much of DT resulted excessive heat generation.
Both these cases resulted in lower joint quality.
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+ ∑ (#+ ) (4.23) where, is the total mean GRG/UV/DV/MPCI values, is the mean GRG/UV/DV/MPCI value at the optimal level and o is the number of process parameters that affect the joint quality characteristics. Table 4.23 contains the predicted GRG, UV, DV and MPCI values at optimal parameter setting obtained from GRA, UC, DFA and FZ-GRA, respectively.
Table 4.22 % Influence of Factors for Various Analysis Techniques
% Influence
Factors GRA UC DFA FZ-GRA
PD 0.00 0.65 0.69 0.37
RPM 11.23 30.49 31.71 18.07
WS 10.65 2.99 1.02 9.40
TG 33.01 22.67 22.73 27.95
SD 6.04 3.30 3.59 4.34
PnD 14.06 13.90 15.94 13.76
TPL 5.53 4.41 5.10 5.18
DT 4.81 10.68 9.68 9.93
Table 4.23 Initial Best, Optimal Parameter Settings and Corresponding Predicted GRG/UV/DV/MPCI values
Methods Cases Parameter setting Corresponding values
(GRG / UV / DV / MPCI) GRA
Initial best PD1 RPM4 WS3 TG4 SD3 PnD1 TPL1 DT2 0.8455 Predicted (Optimal) PD1 RPM1 WS3 TG4 SD3 PnD1 TPL1 DT2 0.9468 UC
Initial best PD1 RPM2 WS4 TG4 SD3 PnD3 TPL2 DT2 7.82 Predicted (Optimal) PD2 RPM1 WS3 TG4SD3 PnD1 TPL1 DT2 9.90 DFA
Initial best PD1 RPM2 WS4 TG4 SD3 PnD3 TPL2 DT2 0.9584 Predicted (Optimal) PD2 RPM1 WS3 TG4SD3 PnD1 TPL1 DT2 1.1940 FZ-GRA
Initial best PD1 RPM2 WS4 TG4 SD3 PnD3 TPL2 DT2 0.9144 Predicted (Optimal) PD2 RPM2 WS3 TG4 SD3 PnD1 TPL1 DT2 1.0787
To verify the improvement of the weld quality characteristic, confirmation experiments were performed by using the optimal parameter combinations (shown in Table 4.23) which were obtained from GRA, UC, DFA and FZ-GRA methods. In the conformation experiment, the plunging depth, rotational speed, transverse speed, tool geometry, shoulder
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and pin diameter, tool pin length and dwell time were set at 0.09 mm, 600 rpm, 132 mm/min, threaded tool geometry, 30 mm, 5 mm, 5.2 mm and 15 second, respectively, for GRA method. Both for UC and DFA methods, only the PD was set at 0.15 mm keeping all other parameters at same level as in the case of GRA. For FZ-GRA method, only RPM was changed to be set at 815 rev/min keeping all other parameters at same level as in case of UC and DFA. The weld qualities of the confirmation experiments for UTS, YS, % Elng., WBT and HRD are given in Table 4.24.
Table 4.24 Output Values Obtained from Confirmation Runs Weld Quality
Characteristic
Analysis Methods
GRA UC and DFA FZ-GRA
UTS 133.43 124.66 130.68
YS 55.09 66.87 69.94
% Elng. 19.87 15.7 16.26
WBT 5.60 5.47 5.57
HRDNS 57.91 57.28 56.87
From the conformational test results, it can be seen that the tensile strength and ductility value is higher for the joints produced at the optimal parameter setting obtained from grey relational analysis as compared to all other methods. This is due to the lower plunging depth used for GRA. But the yield strength is the lowest for the experiment in case of GRA and also there was no significant difference between the measured hardness values for all the methods. As in the present investigation thickness of the weld bead was considered as one of the output parameter, defect free joints with higher weld bead thickness were expected to have higher mechanical properties. For all the analysis theories except PD (0.09 for GRA and 0.15 for UC, DFA and FZ-GRA) and RPM (600 rev./min for GRA, UC and DFA and 815 rev./min for FZ-GRA) other parameter levels are same. Higher PD leads to increase the material flashing from the weld zone. As a result of which material thinning takes place. So even though the joint quality is good, the phenomenon of material thinning reduced the strength and consequently the elongation. For a good joint all the output values should be improved. So from the present experimental investigation it is really difficult to conclude any of the four above mentioned methods to be the best one for multi-objective analysis of FSW process. However if the UTS, ductility and weld bead thickness values are taken into
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account then GRA method is better than all other methods. But if the overall mechanical properties will be considered then FZ-GRA method is better having highest yield strength compared to GRA, UC and DFA methods. The predicted optimal corresponding values (GRG, UV, DV and MPCI) for all the multi-response techniques were also improved as compared to initial best values.
In the present study, for recording the temperature variation of the workpiece, Infra Red camera was used during the experiments. From the experimental results it could be seen that the change in maximum interface temperature was not significant. It was found that the variation of maximum interface temperature was about 9° C (480.32°C to 489.18°C) among all the 32 experiments. So, the information about the weld quality cannot be extracted from the interface temperature. The temperature generated during the FSW process is from 70- 85% of the melting temperature of the base material [Thomas et al., 1991]. Here the interface temperature was measured which is nothing but the temperature of the plasticized material around the shoulder periphery. Once the material got plasticized, the workpiece flow stress falls rapidly as the solidus is approached, so that heating of the nugget at the tool/workpiece interface limits the available heat generation by reducing the torque, because of this temperature variation is insignificant. But still if it is considered as an output parameter then TG was found to be the most influencing factor having 51.51% weightage.
This was due to the larger area of contact for straight cylindrical tools, pulsating effect of squared tool and a material flow along the tool axis due to the threaded tool. TPL was found to be the next influencing factor due to the effect of its depth of penetration inside the workpiece. DT was another factor which was responsible for temperature generation as it decides the time held in the plunged stage of the joining.
In the above mentioned temperature study surprisingly RPM was found to be insignificant in interface temperature generation. To cross verify the influence of RPM on interface temperature generation some more number of experiments were carried out with different RPM keeping all other parameters constant. The detail experimental layout is presented in Table 4.25. The interface temperature profile and peak temperatures recorded during the experiments are represented in Figs. 4.10(a) and (b), respectively. From the temperature profiles it can be seen that the effect of RPM on shoulder workpiece interface temperature generation is not significant.
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Table 4.25 Process Parameter Values and their Levels
Sl. No. RPM TG WS
Exp. 1 600 SC 63
Exp. 2 815 SC 63
Exp. 3 1100 SC 63
Exp. 4 1500 SC 63
(a) (b) Figure 4.10 (a) Temperature profile and (b) peak temperatures with respect to RPM