Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
ISSN 2580-0817
Simulation-based Methodology to Investigate the Impact of Material Type and Compressive Speed Variation on Effective Strain Rate and Springback Radhi Nurvian Amrullah*.
Syamsul Hadi.
Muhammad Akhlis Rizza Department of Mechanical Engineering.
Malang State Polytechnic.
Jl.
Soekarno Hatta No.
Malang, 65141.
Indonesia *Corresponding author: radhinurvian.
rn@gmail.
Article history:
Received: 10 July 2024 / Received in revised form: 5 August 2024 / Accepted: 25 August 2024
Available online 1 September 2024
ABSTRACT
To obtain the desired results in the manufacturing process, especially the bending process, the occurrence of springback must be reduced.
The effective strain rate must be increased to predict the increase in material.
This study uses a simulation method to determine the influence of material type and compressive speed variation on spring back and effective strain rate.
This study uses 3 kinds of materials: JIS SPHD.
JIS A1100 BE, and JIS SN400A, and speed variations, namely: 90 mm/s, 105 mm/s, and 120 mm/s.
This study shows that JIS SN400A material has the smallest springback value compared to JIS A1100 BE and JIS SPHD materials because the nitrogen content in JIS SN400A makes it more plastic.
At a compressive speed of 105 mm/s, springbacks tend to decrease in JIS SN400A.
JIS SPHD, and JIS A1100 BE materials caused by residual stress.
The average effective strain in JIS SN400A material increases in line with the increase in compressive speed, because JIS SN400A material has the highest melting temperature compared to JIS SPHD and JIS A1100 BE materials to reduce the risk of residual stress, the nitrogen content in JIS SN400A material also plays a role in increasing the effective strain value.
Copyright A 2024.
Journal of Mechanical Engineering Science and Technology.
Keywords: Effective strain rate, material, simulation, springback.
Introduction In the manufacturing process, especially in the bending process, to get the results that suit the needs is a hope for engineers.
In the bending process itself, we recognize the existence of springback.
Springback is a common phenomenon in sheet metal formation where elastic recovery causes deviations from the intended geometry after load release.
This affects the precision and quality of the product, posing challenges in the manufacturing process .
In addition, to predict the properties of the material is also important, some possible ways to do it are to know the effective strain rate on the material.
The effective strain rate significantly affects the behavior of maintaining material in various materials.
In AlN ceramics, the higher scratch speed leads to a finer penetration depth and fewer cracks, encouraging the occurrence of plasticity .
For plates, strain rate sensitivity and strain hardening affect the saturation impulse, with displacement inversely proportional to the stiffening factor .
In Fe-30Mn-8Al-1.
0C austenitic steels, an increase in the strain rate from 10-4 to 10-1 s-1 increases the yield strength, with the optimal strength-ductility combination achieved at 10-3 s-1 due to the twin-induced microband and plasticity .
For A356-T7 cast aluminum alloy, the higher strain rate .
% s-1 vs 1% s-.
results in increased DOI: 10.
17977/um016v8i22024p229 Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
ISSN 2580-0817
isotropic hardening and softening rates, and more failure cycles.
Strain rate also had a significant effect on the development of average stress at room temperature.
These findings highlight the importance of considering the effects of strain rate in material design and processing .
The parameters that are suspected to influence the occurrence of springback and effective strain rate are the type of material to be used and the compression speed.
validate this, simulation methods can be used.
Simulation methods are increasingly used in materials testing because of their ability to produce results comparable to physical Studies have shown that computer simulations of tensile tests on polymer composites can achieve results within 7% of the actual test .
Similarly, finite element modeling on shot peening can produce residual stresses equivalent to experimental processes .
The digital image correlation method (DICM) has been successfully applied to similar material simulation experiments for rock-like materials, providing a full-field deformation and strain analysis that is perfectly matched to physical tests .
In estimating the fatigue life of the cardan shaft components, numerical simulations combining the material-specific stress life curve and surface roughness factors have shown good agreement with the results of physical testing.
These studies highlight the effectiveness of simulation methods in materials testing, offering a cost-effective and time-efficient alternative to traditional experimental approaches .
Car bodies are generally made of steel and aluminum with a manufacturing process in the form of bending, therefore the author took the initiative to conduct research effect of material type and pressing speed on springback using a simulation method on the bending II.
Material and Methods This study uses a simulation method with several parameters, as shown in Table 1.
Table 1.
Parameter of simulation Parameter Value Specimen size
Material of punch
Material of dies Punch angle Dies angle Radius punch
Radius dies Temperature punch
Temperature dies Material temperature Material Type
Press speed
2 x 19 x 200 mm S45C
S45C
5 mm 1 mm JIS SPHD.
JIS A1100 BE.
JIS SN400A 90 mm/s, 105 mm/s, 120 mm/s This study uses a constant compressive speed variation using hydraulic presses, namely 90 mm/s, 105 mm/s, and 120 mm/s, and uses 3 different types of materials, namely JIS Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
ISSN: 2580-0817 Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
SPHD.
JIS A1100 BE, and JIS SN400A, the following is the material chemical composition used as shown in Table 2.
Table 2.
Chemical composition of materials Element
Chemical Composition (%) JIS SPHD
JIS A1100 BE
JIS SN400A
This research process begins by determining the case in the metal forming process, then determining the parameters related to the process, then carrying out the design and simulation process using computer-aided design (CAD) software namely Simufact version 15 in 2018, then the process of taking and analyzing data using Microsoft excel software and finally concluding from the analysis results.
This study uses three components, namely punch, sample, and dies, whose size designs are depicted in Figure 1.
Fig 1.
Punch, specimen, and dies sizes Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
ISSN 2580-0817
The mechanical properties of the materials used in the simulation software are already available for the materials used in this study, as shown in Table 3.
Table 3.
Mechanical properties of the material in a CAD software database Mechanical properties of material JIS SPHD JIS A1100 BE JIS SN400A Tensile strength (MP.
Yield strength (MP.
S45C For this study, the mesh used using the automatic method of the software was 0.
mm in size, as shown in Figure 2.
Fig 2.
Mesh size The following simulation modeling is shown in Figure 3.
Fig.
Simulation modeling steps : .
The punch is moved towards the specimen, .
The punch presses the specimen, and .
The punch returns to its original position.
In the simulation process, several parameters such as effective strain rate are generally available in CAD software, but for springback, there is still no springback, so to find out the springback, image analysis software is used.
The hydraulic punch is moved downward at a constant speed to start the simulation process .
, next, the punch presses the specimen to form an angle based on the dies' shape.
from this simulation step, the effective strain rate Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
ISSN: 2580-0817 Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
parameter data is obtained .
, finally, the punch returns to its original position after pressing the specimen, causing springback in the specimen .
, as depicted in Figure 3.
The process of determining the springback begins by inputting the simulation image and then inputting it into the software, then the springback data is taken 3 repetitions and taken on average from the springback.
Then the result is reduced by the size of the die angle, in this study, the size of the die angle is 90o so that the springback size is obtained.
Figure 4 shows the springback data collection was carried out in 3 iterations because the images produced were not of good quality, so it is hoped that the data collection of 3 iterations can validate the results that are closest to the actual situation.
The steps are to add a line to the bottom of the specimen as an auxiliary line .
, this line does not have a standard length because it only functions as an auxiliary line, then make an angle from any point along the auxiliary line so that the angle size of the specimen is obtained .
The software does not currently have a facility to calculate the duration of the simulation, so the approximate 4-minute simulation time was determined by hand calculations.
Fig.
Springback information recovery process : .
The auxiliary line added to the bottom of the specimen, and .
The resulting bending angle formed from the auxiliary line.
Results and Discussions The simulation process is carried out 9 times based on the parameters determined in Table 1 and the simulation results are shown in Table 4.
Based on Table 4, it can be seen that the highest springback value of 0.
265A occurs in JIS SN400A material with a compressive speed of 90 mm/s, and the lowest of -0.
015A occurs in JIS SPHD material with a compressive speed of 90 mm/s.
This shows that the most effective parameter in reducing the occurrence of springback is JIS SN400A material and the compressive speed is 105 mm/s because it has the smallest springback value.
Whereas a negative spring back value indicates that the specimen cannot return to its original form .
he angle curve result is equal to or smaller than the angle size of die.
and that the specimen is more plastic than those with a positive springback value.
A positive springback value indicates that the specimen has a spring back to the re-form .
ngle curvature greater than the angle size of the die.
Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
ISSN 2580-0817
Table 4.
Result of springback simulation Material JIS SPHD
JIS A1100 BE
JIS SN400A
Press .
i Angle .
Springback .
Mean Mean i Based on Figure 5, the dominant decrease in springback value occurs at a compressive speed of 105 mm/s, this is due to the occurrence of residual stress due to an increase in temperature at a compressive speed of 105 mm/s .
enerally the compressive speed on the test machine is 0.
08 mm/.
to affect the resulting product .
JIS A1100 BE material has the highest average springback value, while JIS SN400A material has the lowest average springback value, this is because aluminum has better elastic properties than steel and the nitrogen content in JIS SN400A material causes its mechanical properties to be more plastic as shown in Table 2 .
As Table 5 shows, the traction strength of the AISI 304 L steel increases with the level of nitrogen.
Fig.
Graph of springback simulation results Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
ISSN: 2580-0817 Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
Table 5.
Chemical composition and tensile strength of AISI 304L .
Grade Chemical composition, wt.
03Cr18Ni11
(AISI 304L)
Prototype 04Cr18Ni11 Mn1N0.
03Cr18Ni11 Mn1N0.
05Cr19Ni9 Mn3N0.
03Cr20Ni9 Mn3N0.
06Cr19Ni9 Mn3N0.
03Cr20Ni9 Mn3N0.
Tensile strength (MP.
after heat Quenching,30 min water 1050oC 1100oC Table 6 shows that JIS SN400A material has the highest effective strain rate value of 22 1/s with a compressive velocity of 120 mm/s, and JIS SPHD material has the lowest effective strain rate value of 238.
33 1/s with a compressive speed of 105 mm/s.
This shows that, because it has the highest effective strain rate value, the JIS SN400A material is the most effective for producing more strength .
Table 6.
Result of effective strain rate simulation Material Press speed .
Effective strain rate .
JIS SPHD
JIS A1100 BE
JIS SN400A
Based on Figure 6, the effective strain rate value increases in line with the increase in the compressive speed of JIS SN400A material, this material has the highest effective strain rate value compared to JIS SPHD and JIS A1100 BE materials, this is because JIS SN400A material has the highest melting point .
0A C) compared to JIS SPHD .
0A C) and JIS A1100 BE .
A C) materials.
As the table 7 shows, the higher the material temperature, the more the effective strain rate value increases .
The nitrogen content in JIS SN400A Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
ISSN 2580-0817
material as shown in Table 2, also plays a role in increasing the effective strain rate value .
Fig.
Graph of effective strain rate simulation results Table 7.
Effective Strain Rate at different temperatures .
Test Test 1 Test 2 Test 3 Test 4 Test 5 Test 6 Material Temperature Molybdenum-L Effective Strain Rate .
IV.
Conclusions This study aims to determine the effect of material type and compression speed on springback and effective strain value.
This study shows that JIS SN400A material has the smallest springback value compared to JIS A1100 BE and JIS SPHD materials, because the nitrogen content in JIS SN400A makes it more plastic, and at a compression speed of 105 mm/s, springback tends to decrease in JIS SN400A.
JIS SPHD, and JIS A1100 BE materials caused by residual stress.
The average effective strain in JIS SN400A material increases with increasing compression speed because JIS SN400A material has the highest melting Amrullah et al.
(The Impact of Material Type and Compressive Speed on Strain Rate and Springbac.
ISSN: 2580-0817 Journal of Mechanical Engineering Science and Technology Vol.
No.
November 2024, pp.
temperature compared to JIS SPHD and JIS A1100 BE materials, the nitrogen content in JIS SN400A material also plays a role in increasing the effective strain value.
In future prospects, the results of this study can be used to reduce the occurrence of springback in the bending process, with the bending speed specification must be constant and determined during the manufacturing process.
Acknowledgment The author is grateful for the assistance in financing DIPA funds by the Malang State Polytechnic.
References