2. Fig. 1 Springback variation and its sources
springback is treated as a function of the variation of materials, ing direction 62 mm2. The blank material used was DP600
the variation of the process, and the variation of tooling. Total Steel. The thickness of the blank varied with the material supplier,
variation of springback in the stamping process has several com- i.e., Supplier No. 1, 1.5 mm; Supplier No. 2, 1.2 mm; and Sup-
ponents. Generally, different variation components can be attrib- plier No. 3, 1 mm. The surface conditions i.e., coating of the
uted to different sources 19 . The following are the major catego- sheet material varied from supplier to supplier. Supplier No. 1
ries of variation source Fig. 2 . sheet blanks were galvanized, Supplier No. 3 sheet blanks were
galvannealed, and Supplier No. 2 sheet blanks had no coating.
• Part-to-part variation is also referred to as system-level
variation or inherent variation. It is the amount of variation
that can be expected across consecutive parts produced by
the process during a given run. It is caused by the random
variation of all the uncontrolled process variables.
• Within batch variation is usually due to the variations of the
controlled variables such as blank holder force BHF , ma-
terial property, and friction. In this study, we focused on the
effects of this type variation.
• Batch-to-batch variation represents the variability among
the individual batches, which is mostly caused by material
variation from batch to batch and the variation introduced
by tooling setup.
3 Phase I Experiments
3.1 Experimental Condition and Measurement of
Springback. In this section, HSS material grades from different
suppliers under different conditions were tested. Channel drawing
experiments were conducted to investigate the effect of variations
in material and process condition on the springback variation.
Information about the geometry and dimensions of the tooling and
blank are presented in Fig. 3. Figure 4 shows the formed part after
springback. The initial dimension of the blank sheet was 300 roll-
Fig. 3 A schematic view of tools and dimensions for open-
channel drawing „Phase I…
Fig. 2 Source of variation in a typical forming process Fig. 4 Open-channel parts after drawing „Phase I…
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3. Table 1 Experiment conditions „Phase I… for the springback measurement. First, it is assumed that wall
opening angle, flange closing angles, and sidewall curl vary inde-
Grade Material BHP psi Lubricant pendently. Second, the sidewall curl could be approximated by a
piece of circular arc.
DP600 Supplier No. 1 500 No lub
Galvanized, thickness: 1.5 mm Figure 5 also shows the measurements’ placements A, B, C, D,
Supplier No. 2 1250 Lub 1 and E . Two measurements were conducted before springback,
No coating, thickness: 1.2 mm namely, the x and y coordinates of A and B, which is denoted A0
Supplier No. 3 2000 Lub 2 and B0 in this work. They are used to compute the wall angle 0 1
Galvannealed, thickness: 1.0 mm and flange angle 0 before springback. After springback, another
2
five measurements were placed on A, B, C, D, and E, which were
used in the calculation of the wall angle 1 , flange angle 2 ,
Since the focus of this study is the variation of springback not and sidewall curl radius after springback. To estimate the side-
springback itself , we used the above sheet blanks as obtained wall curl radius, a curve fitting technique that employs three
from the material suppliers the existing variations in the blanks points A, B, and C to construct a circular arc is used. Equation
favor variation analysis . Channel drawing experiments were car- 1 lists all the equations needed for the calculation of the 1, 2,
ried out on a 100 ton Minster mechanical press with a stroke rate and .
of 15 rpm, and the total punch stroke depth was 65.2 mm. The ox · A0B0
0
lower die was unsymmetrical; the left-hand die corner radius 1 = arccos
9.5 mm was larger than that of the right-hand die corner ox · A0B0
7.94 mm . Blank holder pressure BHP was controlled by hy-
draulic cylinders. 0 ox · A0B0
2 = arccos
BHP, material supplier, and lubrication friction were chosen ox · A0B0
as design factors. Table 1 summarizes the experimental condi-
tions. Central composite design response surface method RSM ox · AB
with 2-replicate for each observation and 12-center point was used 1 = arccos
ox · AB
for this three-factor and three-level experimental design. The total
numbers of runs were 40. Three levels of BHP were 500 psi, AB · ED
1250 psi, and 2000 psi. The three levels of lubrication are “no 2 = arccos
lubrication,” “Lubricant 1,” and “Lubricant 2.” Both lubricants ED · AB
were supplied by Fuchs Lubricants Co. Lubricant 1 is quite slip- 0
pery due to its low viscosity. Lubricant 2 is very sticky as a result 1 = 1 − 1 1
of its high viscosity. Table 2 presents some detailed information 0
about these lubricants. 2 = 2 − 2
Three measurements, namely, the springback of wall opening
angle 1 , the springback of flange angle 2 , and sidewall curl 2 2 2 2 yA − yB 2
xB + y B − xA − y A − x + y 2 − x2 − y 2
radius shown in Fig. 5, were used to characterize the total yC − yB C C B B
springback considering only the cross-sectional shapes of formed xO =
parts obtained before and after the removal of tools. The spring- yA − yB
2 xB − xA + xC − xB
back in the direction orthogonal to the cross section, such as twist- yC − yB
ing, was not considered since it is negligible is this case. As there
2 2 2 2
is no clear distinction to separate a cross-sectional curve for indi- xA + y A − xB − y B + 2xO xB − xA
vidual measurement of springback angles and sidewall curl, two yO =
2 yA − yB
assumptions deduced from the sample observations are introduced
= xA − xO 2 + y A − y O 2
Table 2 Lubricant information „Phase I… However, since it was impossible to make the measurement with-
out removing the tooling from the channel after forming, we were
Lubricant 1 Lubricant 2 not able to directly measure 0 in the physical experiment. There-
1
Density 7.49 lbs/ gal 7.89 lbs/ gal fore, finite element FE simulation was used to determine 0. The 1
Kinematic viscosity 17.0 cSt of 40° F 87.0 cSt of 40° F channel drawing process was simulated using ABAQUS/STANDARD.
Tooling geometry was exactly the same as in the physical experi-
ments. The material was modeled as an elastic-plastic material
with isotropic elasticity, using the Hill anisotropic yield criterion
for the plasticity. All the material data were from our tensile test
on Supplier No. 2 DP600. The friction coefficient between tools
and the sheet blank was assumed to be constant and 0.1. The sheet
was modeled using solid C3D8R element. The thickness of the
sheet was 1.2 mm. Figure 6 shows the channel after drawing be-
fore springback. Applying Eq. 1 to this part, the 0 was found to
1
be 103.2124 deg on the right-hand side and 101.1821 deg on the
left-hand side note that die corner radii on the right-hand and
left-hand sides are different, see Fig. 3 .
In the physical experiments, the measurements after springback
were conducted on the blade inspection machine BIM . BIM is a
laser beam measurement instrument developed by Engineering
Research Center in the University of Michigan. It has four degrees
of freedom. Accuracy is about 15 m. The repeatability of the
Fig. 5 Illustration of springbacks BIM was tested by conducting seven measurements on a Supplier
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4. Table 4 Repeatability test of the system
Left 1 deg 2 deg mm
1 32.83 −4.06 101.73
2 31.07 −4.82 107.30
3 31.12 −4.85 95.74
4 30.92 −4.91 111.52
5 31.74 −4.69 98.53
6 33.47 −4.70 107.90
7 33.15 −4.43 100.11
Mean 32.04 −4.64 103.26
Stdev 1.08 0.30 5.73
Fig. 6 Deformed shape of the channel before springback
„Phase I… Right 1 deg 2 deg mm
1 31.14 −9.54 94.51
No. 3 DP600 channel. Table 3 summarizes the test results. 2 31.20 −9.23 113.86
The left-hand side and right-hand side of the channel were mea- 3 29.88 −9.68 99.88
sured separately. Due to the asymmetry of the tooling, there was 4 29.84 −10.27 98.88
some twisting that occurred after springback. To eliminate the 5 29.70 −11.27 93.94
influence of twisting on our springback measurement, two mea- 6 32.68 −11.00 95.31
7 31.36 −10.94 103.77
surements were separately conducted on the upper and lower parts
of the channel Fig. 7 and then their average was considered as Mean 30.83 100.02
−10.27
the final springback. In our measurements, the part was carefully Stdev 1.09 0.81 7.03
examined to determine the positioning of Points A and B. As
shown in Fig. 4, there are two narrow zones edges where the
curve changes directions, which were identified as the locations of
A and B. 31. Since these outliers deviate from the normal observations ex-
To evaluate the repeatability of the press, seven channels were cessively, these four experimental results were excluded in the
drawn consecutively under the same process conditions, that is, eventual analysis. The reason for these abnormal observations
1000 psi BHP, 15 rpm stroke rate, no lubrication, and the blank could be mostly due to the irregular contact condition between the
material was DP1000 from Supplier No. 2 in rolling direction. tooling and the blank.
Since BIM was needed to quantify the springback, the results of After Experiments 5, 11, 27, and 31 were taken out of the
this test were actually the repeatability of the whole system, which design of experiments DOE matrix; the statistics of the remain-
includes the repeatability of the press and the BIM. Table 4 shows ing 36 experimental results were computed and shown in Table 6.
the test results. Since the BIM is quite repeatable and its variation Obviously, the standard deviations 1, 2, and at the left-hand
Table 3 is very small when compared to the variation of the and right-hand sides are comparable, which indicates that the
whole system Table 4 , we can reasonably assume that the re- asymmetry in the tooling does not have a distinct influence on the
peatability of the press is equal to that of the whole system. springback variation. On the other hand, all the standard devia-
3.2 Experimental Results. The experimental results are pre- tions in Table 6 are apparently higher than that of Table 4 repeat-
sented in Table 5. As highlighted and underlined in the table, ability of the system , which is reasonable because it proves that
extreme points were observed for Experiment Nos. 5, 11, 27, and the design factors used in the DOE do have impacts on the spring-
back variation. However, the disadvantage is that the difference in
standard deviation between these two tables is not large enough;
Table 3 Repeatability test of the instrument „BIM… consequently, the influence of some factors on the springback
variations might not be distinguishable from the system-level
DP600 1 2 mm noise, which is the limitation of the physical experiments.
1 21.56 −5.30 157.91 3.3 Springback Variation Analysis. To evaluate the effect of
2 21.42 −5.36 155.40 each design factor on the variation of the springback, three meth-
3 21.49 −5.24 151.69 ods Monte Carlo simulation, sensitivity analysis, and Taguchi
4 21.45 −5.43 155.61 approach were used to analyze the effects of the design factors on
5 21.44 −5.32 152.14 the variation of the springback. Finally, it was found that the
6 21.63 −5.15 152.41 springback variation magnitude is too small in most cases and not
7 21.60 −5.26 158.50 distinguishable from the system noise. Therefore, the conclusions
based on Monte Carlo simulation and sensitivity analysis actually
Mean 21.51 −5.29 154.81 do not have any meaning because the springback variations are
Stdev 0.08 0.09 2.80 totally random and uncontrollable in those cases. In the case that
the design factors do have effects on the springback variation, the
conclusions from all three methods agree well with each other.
Hence, only the results obtained from the Taguchi approach are
presented in this paper. MINITAB, a statistical software, was used
and it can automatically extract data standard deviation and
mean from the available experimental observations. The main
effects of each design factor on the standard deviations of the
response are obtained via regression analysis. The significance of
each factor on each springback variation was tested via analysis of
variation ANOVA . p-values p were used to determine which
Fig. 7 Measurement illustration of the effects in the model are statistically significant, which are
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5. Table 5 Experiment-results
Factor Left Right
Run Material BHP psi Lub 1 deg 2 deg mm 1 deg 2 deg mm
1 Supplier No. 2 1250 Lubricant 1 15.6993 −6.1769 187.207 13.5679 −9.6835 181.892
2 Supplier No. 3 2000 No Lub 15.8564 −4.4536 199.364 13.9047 −8.1482 178.042
3 Supplier No. 1 500 Lubricant 2 20.0762 −4.6968 191.231 17.8465 −9.5101 226.61
4 Supplier No. 1 500 Lubricant 2 19.8247 −4.7888 223.729 17.5656 −9.4819 211.965
5 Supplier No. 1 2000 Lubricant 2 14.7198 −3.093 298.683 5.7092 −8.4805 227.958
6 Supplier No. 3 1250 Lubricant 1 14.3697 −6.3344 192.187 13.7932 −9.6151 182.026
7 Supplier No. 3 500 Lubricant 2 22.0333 −6.2993 146.425 19.9358 −10.987 142.669
8 Supplier No. 2 1250 Lubricant 1 16.0359 −5.1992 188.823 14.728 −8.6167 231.36
9 Supplier No. 2 500 Lubricant 1 18.6675 −5.3899 171.615 16.7942 −9.7738 199.705
10 Supplier No. 1 2000 No Lub 13.5222 −3.894 195.915 11.3381 −8.3672 207.213
11 Supplier No. 3 2000 Lubricant 2 4.02918 −5.528 202.971 13.4831 −8.3467 150.288
12 Supplier No. 2 1250 Lubricant 1 15.1855 −4.8622 206.179 13.7077 −9.1401 217.591
13 Supplier No. 2 1250 No Lub 15.3885 −5.5971 187.314 13.8467 −9.5312 193.354
14 Supplier No. 2 1250 Lubricant 2 16.0866 −5.3531 209.682 13.8898 −9.8294 186.178
15 Supplier No. 3 500 Lubricant 2 21.0898 −5.9936 181.657 18.8824 −11.069 152.144
16 Supplier No. 3 2000 Lubricant 2 13.0602 −5.4131 146.089 14.497 −9.0402 161.024
17 Supplier No. 2 1250 Lubricant 1 15.4912 −5.5857 206.575 13.3289 −9.789 176.359
18 Supplier No. 2 1250 Lubricant 2 15.4387 −5.6523 196.978 13.6798 −9.8503 207.245
19 Supplier No. 2 1250 Lubricant 1 15.6228 −5.6279 174.305 13.7202 −9.6174 191.709
20 Supplier No. 1 1250 Lubricant 1 15.2422 −4.0691 270.899 12.8006 −8.7921 270.012
21 Supplier No. 2 2000 Lubricant 1 14.8537 −4.3328 203.675 12.848 −8.92 204.329
22 Supplier No. 3 2000 No Lub 15.0892 −4.6861 188.549 13.0076 −8.5428 185.697
23 Supplier No. 1 2000 Lubricant 2 15.0429 −4.0359 269.258 12.3589 −8.4598 227.267
24 Supplier No. 2 1250 Lubricant 1 15.4417 −5.8915 172.095 13.3375 −10.173 193.501
25 Supplier No. 2 1250 Lubricant 1 14.6597 −6.0415 190.807 13.9982 −9.9468 176.664
26 Supplier No. 2 1250 No Lub 15.7981 −5.4327 210.938 13.8225 −10.06 176.188
27 Supplier No. 3 1250 Lubricant 1 11.679 −6.474 436.318 12.4059 −9.263 295.867
28 Supplier No. 2 1250 Lubricant 1 15.9345 −5.7507 165.792 13.7662 −9.6576 199.585
29 Supplier No. 2 1250 Lubricant 1 15.5115 −5.7496 178.019 13.8443 −9.6322 183.288
30 Supplier No. 2 1250 Lubricant 1 14.9152 −5.2007 175.288 13.5789 −9.7663 180.245
31 Supplier No. 1 2000 No Lub 10.2705 −4.2287 608.726 11.1942 −8.0158 209.471
32 Supplier No. 1 500 No Lub 16.4861 −4.7083 241.233 14.7391 −9.1828 229.581
33 Supplier No. 2 1250 Lubricant 1 16.6876 −4.9928 168.269 13.3051 −10.242 156.751
34 Supplier No. 2 500 Lubricant 1 18.3289 −5.3152 182.175 16.0842 −10.111 195.1
35 Supplier No. 1 500 No Lub 16.1822 −4.3564 256.959 13.9471 −9.1369 262.083
36 Supplier No. 3 500 No Lub 21.3207 −5.7254 150.275 17.9187 −11.398 135.014
37 Supplier No. 2 1250 Lubricant 1 13.9594 −5.6969 178.863 12.2385 −8.9733 238.387
38 Supplier No. 1 1250 Lubricant 1 15.5804 −4.9247 196.13 13.784 −8.8636 253.996
39 Supplier No. 2 2000 Lubricant 1 13.9873 −4.7206 170.913 12.5731 −8.7004 197.008
40 Supplier No. 3 500 No Lub 20.6604 −6.3556 181.094 19.6129 −10.428 158.126
compared with a -level of 0.06 if the p-value is less than or terion is the variation of 1 on the right-hand side highlighted in
equal to , we conclude that the effect is significant; if the p-value Table 7 .
is greater than , we conclude that the effect is not significant . As The main effects of the design factors on the standard devia-
shown in Table 7, in most cases, it was found that the effect of tions of 1 are shown in Fig. 8; the effects of material and lubri-
each factor on the variation is not distinguishable from the cation are significant, but the effect of the BHP is not. According
system-level noise. The only one that could satisfy the F-test cri- to Fig. 8, when we use material from Supplier No. 3, we could
expect more variation in 1, which means that either the material
properties or the thickness of supplier No. 3 have more variation
Table 6 Statistics of the experimental results „sample popula- when compared to other materials. Table 8 is the variation in the
tion: 36, Phase I…
thickness according to data measured for the experiment. It indi-
Left deg deg mm
cates that the thickness variation of the Supplier No. 3 materials is
1 2
not the highest among the three materials used. Therefore, it is
Mean 16.36 −5.26 193.24 evident that Supplier No. 3 materials have more material property
Stdev 2.31 0.68 29.72 variation than others, which is reasonable according to Engel and
Min 13.06 −6.36 146.09 Eckstein’s size effect theory 20 . As Engel and Eckstein reported,
Max 22.03 −3.89 270.90 the material property becomes more scattered when the specimen
size becomes smaller Supplier No. 3 material has the smallest
Right 1 deg 2 deg mm thickness . On the other hand, the surface coating also has an
Mean 14.52 196.39
effect on the variation of 1. One explanation of the less variation
−9.53
Stdev 2.13 0.76 31.88 of Supplier No. 2 material according to Fig. 8 is that coatings of
Min 11.34 −11.40 135.01 Supplier Nos. 1 and 3 materials might have introduced more
Max 19.94 −8.15 270.01 variations in the material property.
The effect of the lubrication is reasonable and in well agree-
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6. Table 7 F-tests for the standard deviation of each springback „Phase I…
p-value
Left Right
Stdev 1 Stdev 2 Stdev Stdev 1 Stdev 2 Stdev
Material 0.153 0.163 0.15 0.019 0.191 0.891
BHP 0.624 0.211 0.43 0.134 0.476 0.485
Lub 0.524 0.208 0.311 0.056 0.18 0.653
ment with previously reported observations 21 . First, the varia- on a different tooling set. Information about the geometry and
tion in 1 decreases when a lubrication is used, which is due to the dimensions of the tooling is presented in Fig. 9. The pad was
fact that the friction distribution is more uniform if a lubricant is spring-loaded and functioned as a blank holder. The initial dimen-
used. Second, Lubricant 2 is much more viscous than Lubricant 1. sion of the blank sheet was 200 rolling direction 62 mm2.
Therefore, when the blank holder pushes down, we would expect Channel drawing experiments were carried out on a 345 ton bliss
that more Lubricant 1 be pressed out when compared to Lubricant straight side mechanical press with a stroke rate of 12 rpm.
2 since Lubricant 1 is easy to flow, which means that the friction Different material batches and lubrication conditions friction
condition is more uniform when Lubricant 2 is applied, hence, were chosen as design factors to construct a design of experiment
less variation in part quality. Overall, the function of lubricant is matrix. Three grades of DP steels supplied by SSAB were inves-
all about its impact on the uniformity of the friction, not the mag- tigated separately. They are DP600, DP800, and DP1000. In each
nitude of friction. case, two batches of the same grade material were used to observe
When examining the range of the standard deviation, it is ob- the effect of material batch difference on the springback variation.
vious that the springback variation introduced by the material fac- The thickness of the blank varied with the material grade, as
tor is more than that of the lubrication factor. Therefore, in the shown in Table 9. The lubrication condition was treated as a three-
case of our experiments, the most important factor on springback level factor. The three levels of lubrication were no lubrication,
variation is material property variation. Lubricant TOWERPRO 7800, and Lubricant KLENEDRAW
To further investigate the effect of BHP on the variation of 1, 4800. Both lubricants were supplied by TOWER OIL & TECH-
the factor effects on 2, and the factor effects on ; at least one of NOLOGY. Table 10 presents detailed information of these lubri-
the following two actions should be carried out: a perform a cants. Considering that the focus of this study is the variation of
system-level adjustment of the press to reduce the part-to-part the springback, a Taguchi L18 orthogonal array design was used,
variation, and therefore, make the springback variation distin- as shown in Table 11. The total numbers of runs were 18. Figure
guishable from the system-level noise; b reduce variations in 10 shows three different grade parts after springback. Apparently,
material properties to a certain level, so that the effect of BHP springback increases as the material strength increases.
becomes more dominant, which is not possible at the present time The same springback measurement method and instrument
as it was very difficult to obtain HSS sheets with the same thick- BIM were used as those used in Phase I. Based on the geometry
ness and coatings from different suppliers. of the tooling, the 0 was assumed to be 90 deg. Four measure-
1
ments two measurements on each side were conducted on each
4 Phase II Experiment channel; the average of them was used as the measured spring-
back value.
4.1 Experimental Condition. In this phase, HSS materials
from a single supplier but from different batches were tested. To 4.2 Experimental Results and Springback Variation
further investigate the effect of variation in material due to the Analysis for DP600. Taguchi analysis was used to analyze the
batch-to-batch difference and lubrication conditions on the springback variation. MINITAB, a statistical software, was used to
springback variation, another set of experiments was conducted analyze the existing experiment results Table 11 . The main ef-
Fig. 8 Main effects of factors on Stdev„ 1…, right
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7. Table 8 The variation in the blank thickness „Phase I…
Supplier No. 1 Supplier No. 2 Supplier No. 3
Stdev thickness 0.019 0.011 0.013
Fig. 10 Parts after springback „Phase II…
fects of each design factor on the standard deviations of the re-
sponse are obtained via regression analysis, and the significance
of these effects was tested via ANOVA and F-tests. p-values p
were used to determine which of the effects in the model are
statistically significant, which are compared with a -level of
0.06. As shown in Table 12, neither material batch difference nor
lubricants have a significant effect on variations of 1, 2, or . In
other words, the variations of the above springbacks could not be
Fig. 9 A schematic view of tools and dimensions for Phase II controlled by the respective design factors.
experiment
4.3 Experimental Results and Springback Variation
Table 9 Summary of the initial blank conditions „Phase II…
Analysis for DP800. The same method was used to analyze the
Supplier Grade Thickness mm Surface existing experimental results Table 13 . As shown in Table 14,
neither material batch difference nor lubricants have a significant
SSAB DP600 1.2 No coating effect on variations of 1, 2, or . In other words, the variations
SSAB DP800 1.45 No coating of the above springbacks could not be controlled by the respective
SSAB DP1000 1.5 No coating design factors.
4.4 Experimental Results and Springback Variation
Table 10 Lubricant information „Phase II… Analysis for DP1000. The same method was used to analyze the
TOWERPRO 7800 KLENEDRAW 4800
existing experimental results Table 15 . As shown in Table 16,
neither material batch difference nor lubricants have a significant
Chemical family Emulsifiable mineral oil Water soluble organics effect on variations of 1, 2, or . In other words, the variations
Viscosity 32 SUS at 100° F 43 SUS at 100 ° F of the above springbacks could not be controlled by the respective
1.14 cSt 5.18 cSt design factors.
Table 11 Experimental results „DP600…
Test Material Lubricant 1 deg 2 deg mm
1 Batch-1 No lubricant 9.72 6.16 172.25
2 Batch-1 No lubricant 9.56 6.41 171.31
3 Batch-1 No lubricant 10.09 6.07 167.44
4 Batch-1 TOWERPRO 7800 9.78 6.09 167.57
5 Batch-1 TOWERPRO 7800 9.74 6.27 165.06
6 Batch-1 TOWERPRO 7800 9.87 6.09 165.76
7 Batch-1 KLENEDRAW 4800 10.19 6.04 163.90
8 Batch-1 KLENEDRAW 4800 10.02 5.97 161.69
9 Batch-1 KLENEDRAW 4800 9.96 6.05 163.89
10 Batch-2 No lubricant 10.75 6.43 154.65
11 Batch-2 No lubricant 10.82 6.22 154.47
12 Batch-2 No lubricant 10.67 6.38 156.79
13 Batch-2 TOWERPRO 7800 10.73 6.58 150.94
14 Batch-2 TOWERPRO 7800 10.77 6.49 152.55
15 Batch-2 TOWERPRO 7800 10.66 5.84 152.73
16 Batch-2 KLENEDRAW 4800 10.65 6.42 154.52
17 Batch-2 KLENEDRAW 4800 10.66 6.33 151.70
18 Batch-2 KLENEDRAW 4800 10.24 6.08 165.64
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8. Table 12 F-tests for the standard deviation of each springback Table 16 F-tests for the standard deviation of each springback
„DP600… „DP1000…
p-value p-value
Stdev 1 Stdev 2 Stdev Stdev 1 Stdev 2 Stdev
Material 0.776 0.36 0.581 Material 0.46 0.25 0.698
Lubricant 0.591 0.595 0.593 Lubricant 0.977 0.936 0.141
Table 13 Experimental results „DP800…
Test Material Lubricant 1 deg 2 deg mm
1 Batch-1 No Lubricant 11.35 6.79 148.91
2 Batch-1 No Lubricant 11.73 5.74 150.72
3 Batch-1 No Lubricant 11.24 6.04 147.23
4 Batch-1 TOWERPRO 7800 10.90 6.57 150.89
5 Batch-1 TOWERPRO 7800 10.57 6.91 152.41
6 Batch-1 TOWERPRO 7800 10.64 6.94 153.69
7 Batch-1 KLENEDRAW 4800 10.68 6.76 151.67
8 Batch-1 KLENEDRAW 4800 10.95 6.85 148.60
9 Batch-1 KLENEDRAW 4800 10.92 6.64 148.92
10 Batch-2 No Lubricant 10.59 5.74 156.98
11 Batch-2 No Lubricant 10.81 5.73 159.10
12 Batch-2 No Lubricant 10.49 5.76 158.92
13 Batch-2 TOWERPRO 7800 10.30 6.04 159.14
14 Batch-2 TOWERPRO 7800 10.84 5.80 156.15
15 Batch-2 TOWERPRO 7800 10.66 5.97 152.34
16 Batch-2 KLENEDRAW 4800 11.21 5.75 153.63
17 Batch-2 KLENEDRAW 4800 10.66 5.79 159.48
18 Batch-2 KLENEDRAW 4800 10.94 5.59 156.09
Table 14 F-tests for the standard deviation of each springback
„DP800… significant effect on the springback variation. According to our
material tests, this is because two batches of material have a very
p-value close magnitude of material variations. It has been observed in
practice that coil-to-coil variation of incoming steels is much
Stdev 1 Stdev 2 Stdev
greater than batch-to-batch because of variations in heat treat-
Material 0.584 0.335 0.361 ments, which explains why no significance was found for batch-
Lubricant 0.981 0.724 0.618 to-batch materials. Lubricants used in this study have a negligible
effect on the springback variation, which is due to their low vis-
cosity when compared to the lubricants used in Phase I experi-
ments. According to the investigations in Phase I, lubricants with
4.5 Discussion. In all the cases DP600, DP800, and DP1000 a high viscosity of more than 87.0 cSt at 40° F are preferred for
steels , change of materials from batch to batch did not show a the reduction of springback variation.
Table 15 Experimental results „DP1000…
Test Material Lubricant 1 deg 2 deg mm
1 Batch-1 No Lubricant 13.83 8.85 116.42
2 Batch-1 No Lubricant 13.69 8.76 116.26
3 Batch-1 No Lubricant 13.94 8.56 113.63
4 Batch-1 TOWERPRO 7800 14.00 8.74 119.75
5 Batch-1 TOWERPRO 7800 13.77 8.47 118.26
6 Batch-1 TOWERPRO 7800 13.50 8.65 121.36
7 Batch-1 KLENEDRAW 4800 14.24 8.87 118.61
8 Batch-1 KLENEDRAW 4800 14.51 8.96 116.23
9 Batch-1 KLENEDRAW 4800 13.86 9.25 119.89
10 Batch-2 No Lubricant 13.84 9.59 107.72
11 Batch-2 No Lubricant 13.95 9.57 106.28
12 Batch-2 No Lubricant 14.33 9.41 109.38
13 Batch-2 TOWERPRO 7800 14.13 9.67 111.09
14 Batch-2 TOWERPRO 7800 14.17 9.59 108.60
15 Batch-2 TOWERPRO 7800 14.04 9.85 109.52
16 Batch-2 KLENEDRAW 4800 14.69 9.58 111.04
17 Batch-2 KLENEDRAW 4800 14.60 9.51 113.76
18 Batch-2 KLENEDRAW 4800 14.67 9.43 109.88
041006-8 / Vol. 130, AUGUST 2008 Transactions of the ASME
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9. 5 Discussion and Conclusions Properties on the Springback Behavior of 2D-Draw Bending Parts,” Automo-
tive Stamping Technology, SAE, Warrendale, PA, pp. 11–18.
In this study, the springback variation in the forming of HSS 4 Geng, L. M., and Wagoner, R. H., 2002, “Role of Plastic Anisotropy and Its
was characterized by investigating the effect of different factors Evolution on Springback,” Int. J. Mech. Sci., 44 1 , pp. 123–148.
5 Mattiasson, K., Strange, A., Thilderkvist, and P., Samuelsson, A., 1995,
on the variation of springbacks. The investigated factors were ma- “Simulation of Springback in Sheet Metal Forming,” Fifth International Con-
terial property within batch difference and batch-to-batch differ- ference on Numerical Methods in Industrial Forming Process, New York, pp.
ence , BHP, and lubrication. The following sheet metal materials 115–124.
were studied: DP 600 supplied by SSAB, USS, and Dofasco , DP 6 Wagoner, R. H., Carden, W. D., Carden, W. P., and Matlock, D. K., 1997,
800 supplied by SSAB , and DP 1000 supplied by SSAB . Other “Springback After Drawing and Bending of Metal Sheets,” Proceedings of the
IPMM ’97—Intelligent Processing and Manufacturing of Materials, Vol. 1, pp.
factors that might affect the springback and springback variation 1–10.
are related to the tooling such as die clearance, tool surface, etc.; 7 Li, K. P., Geng, L. M., and Wagoner, R. H., 1999, “Simulation of Springback
their significance on springback variation should be also quanti- With the Draw/Bend Test,” IPMM ’99, IEEE, Vancouver, BC, Canada, pp. 1.
fied to see if they can be used to minimize the springback varia- 8 Lee, S. W., and Yang, D. Y., 1998, “An Assessment of Numerical Parameters
tion, which will be the future work of this study. On the basis of Influencing Springback in Explicit Finite Element Analysis of Sheet Metal
Forming Process,” J. Mater. Process. Technol., 80-81, pp. 60–67.
the quantitative and qualitative analysis made herein, the follow- 9 Lee, M. G., Kim, D. Y., Kim, C. M., Wenner, M. L., and Chung, K. S., 2004,
ing conclusions could be drawn: “Spring-Back Evaluation of Automotive Sheets Based on Isotropic-Kinematic
Hardening Laws and Non-Quadratic Anisotropic Yield Functions, Part III: Ap-
1. Material property has the most influence on the springback plications,” Int. J. Plast., 21 5 , pp. 915–953.
variation in this study. 10 Tekiner, Z., 2004, “An Experimental Study on the Examination of Springback
2. In Phase I experiments, the influence of material property on of Sheet Metals With Several Thicknesses and Properties in Bending Dies,” J.
Mater. Process. Technol., 145, pp. 109–117.
the springback variation Stdev 1 is mainly due to the
11 Cleveland, R. M., and Ghosh, A. K., 2002, “Inelastic Effects on Springback in
material property variations. In summary, the thicker the Metals,” Int. J. Plast., 18, pp. 769–785.
blank is, the less springback variation, which could be an 12 Cao, J., Kinsey, B., and Solla, S. A., 2000, “Consistent and Minimal Spring-
indication of size effect. On the other hand, blanks without a back Using a Stepped Binder Force Trajectory and Neural Network Control,”
coating show less springback variation. ASME J. Eng. Mater. Technol., 122, pp. 113–118.
13 Ho, K. C., Lin, J., and Dean, T. A., 2004, “Modelling of Springback in Creep
3. The application of lubricant helps us to reduce springback Forming Thick Aluminum Sheets,” Int. J. Plast., 20, pp. 733–751.
variation Stdev 1 , though it actually increases the 14 Liu, S. C., and Hu, S. J., 1997, “Variation Simulation for Deformable Sheet
springback itself. The more uniform the friction condition, Metal Assemblies Using Finite Element Methods,” ASME J. Manuf. Sci. Eng.,
the less the springback variation. The function of lubricant is 119 3 , pp. 368–374.
15 Button, S. D., 1999, “Determinant Assembled Stowage Bins—A Case Study,”
all about its impact on the uniformity of the friction, not the Polym. Compos., 20 1 , pp. 86–97.
magnitude of friction. Lubricants with a high viscosity of 16 Liu, S. C., and Hu, S. J., 1995, “An Offset Finite-Element Model and Its
more than 87.0 cSt at 40° F are preferred for the reduction of Applications in Predicting Sheet-Metal Assembly Variation,” Int. J. Mach.
springback variation. Tools Manuf., 35 11 , pp. 1545–1557.
17 Swanstrom, F. M., and Hawke, T., 2000, “Design for Manufacturing and As-
4. The effect of BHP on the springback variation is relatively sembly: A Case Study in Cost Reduction for Composite Wing Tip Structures,”
small, not distinguishable from the system-level noise in this SAMPE J., 36 3 , pp. 9–16.
study. 18 Eggert, R. J., 1995, “Design Variation Simulation of Thick-Walled Cylinders,”
ASME J. Mech. Des., 117 2 , pp. 221–228.
19 Majeske, K. D., and Hammett, P. C., 2003, “Identifying Sources of Variation in
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Journal of Manufacturing Science and Engineering AUGUST 2008, Vol. 130 / 041006-9
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