In this research, numerical analysis, response surface method (RSM) and experiments are used to investigate and verify the hot forging process for manufacturing aluminum crown forgings for shock absorber assembly. First, establish the computer aided design (CAD) model of the die and the billet, and simulate it from the finite element method (FEM). Second, a new preforming die was designed with a preformed dressing of controllable deformation zone (CDZ) by the CAD software. Third, numerical simulation was combined with RSM to optimize the processing parameters with the aim of minimizing the die wear while the integrity of forgings should be prioritized preserved. According to RSM, the billet size and preformed dressing of CDZ are important factors affecting the distance between die and workpiece (C). The optimal design factor of the preforming die: billet diameter (D), billet length (L) and flash design (F) are 40 mm, 205 mm and CDZ 1, respectively. Through the results of FEM, this study describes the distribution of microscopic grain flow lines are highly related to forming, stress, strain, and temperature as well as die design such as CDZ in preformed dressing. In order to accurately verify that the parameters analyzed by the RSM, both numerical analysis and physical experiments are carried out and optimal scheme exhibit reasonable consistency.
Research Article
Optimization of Controllable Deformation Zone And Die Wear of Aluminum Crown Forgings For Shock Absorber Assembly
https://doi.org/10.21203/rs.3.rs-888637/v1
This work is licensed under a CC BY 4.0 License
Version 1
posted 21 Sep, 2021
You are reading this latest preprint version
Controllable deformation zone
Crown for shock absorber assembly
Finite element method
Response surface method
Wear depth
The CDZ study of the hot forging die shows that the material loss and the change of the geometric shape indicate the effectiveness of the hot forging die and whether there are defects in the forging die [1–4]. Tool life has a significant influence on material costs, forging process and post-processing. Several studies show the analysis of the failure and damage of forging tools [5–6]. The molding equipment in the hot forging process will be due to friction and wear, thermal fatigue, plastic deformation and brittle cracks of the mold [1]. If the forging die is deformed, its surface combination and density will change [7–9]. The pressure per unit area and the friction of the contact surface, the hardness of the material and the quality of the forging will all affect the mechanical load of the forging. The die forging process mainly involves expanding its effectiveness to reduce the life of forging tools [10–12]. The most effective way to increase the life of forging tools is to surface treatment for forging dies [13–17].
Besides, combining finite element analysis (FEA) is a method to enhance rationality and research efficiency. The finite element method (FEM) estimates mold wear and compares finite element modeling results with experimental data to ensure the reliability of this model [18]. The Archard abrasive application model is usually used to simulate the forging process and adjudge the qualitative and quantitative changes in the geometry of forging tools [19–20]. A number of studies have shown that trying to adjust the wear described by the Archard model to a practical mechanism without considering the applicable wear mechanism [21–23]. For radial forging of shafts or pipes, FEM can be used to analyze the influence of the mold joint on the deformed cross-section [24]. The mold design that increases the fillet groove or the draft angle can improve the life of the mold and the filling of the forging [25]. By designing a movable flash gap on the forging die, experiments and FEA confirmed that the movable flash gap significantly affects the material flow [26]. So as to improve the precision of hot forged gears, a forging die shrink-fit design can be used. This method has been verified by experiments and FEM realization [27]. Optimized the die structure and process parameters for beam forming and provide a lot of support; the results show that the filling performance of half-wall die forgings has been significantly improved [28]. A method for optimizing the blank and forging die is proposed, eliminating the groove defects and describing the shortcomings of forging, such as insufficient filling, hide laps or stress, etc. [29]. It is shown that the deficiency is highly correlated with the contact area between the tube and the two molds [30]. The preforming die and hot forging process can be adjusted and optimized through the Marc software, and the die set with the best performance has been obtained [31]. Multiple rows of sprockets are produced using a semi-precision die, and then the influence of speed on cavity filling is analyzed [32]. The new closure proposed to eliminate the existing steering knuckle forming process is the extrusion forging die [33]. The most severe cause of mold failure mechanism is thermomechanical fatigue [34].
There have been many experimental cases using design of experiment (DOE) methods to optimize processing parameters, for instance, full factorial design [35–37], Taguchi method [38–40], Analysis of variance (ANOVA) [41–42], and fuzzy logic [43–44]. According to previous studies, the most effective way to improve material flow and increase die filling is to optimize the forging die geometry. The influence on the internal quality of cast SAE305 alloy parts is analyzed by the DOE method, and the best process parameters have been obtained [45]. The Taguchi method utilizes to study the effect of forming parameters on density castings, and the optimized parameters were confirmed [46]. Taguchi and FEM are used for forging molds of large and complex straight bevel gears to improve cavity filling and improve mold replacement [47]. Using the Taguchi method to improve the plastic injection molding process parameters, and the mixed use of GA-PSO and RSM can reduce time and cost, and obtain high-quality parts [48]. Utilize Taguchi method to combine CAD technology to optimize the drawing die with multiple objectives, and the structure of the lower die was increased [49].
In this paper, FEM and RSM are collocated to optimizing the forging of crown for shock absorber assembly. This method is legitimate arithmetic to increase the accuracy and efficiency of the experiment. Research and industry often use DOE to optimize the process and reduce the actual operation cost and time. The numerical simulation includes the filling rate of forgings, material flow, effective stress, strain, etc., for analysis and verification of its rationality. Thence, a preformed dressing is presented to increase the accuracy of the crown for shock absorber assembly in this research.
3.1 Original die design
In order to improve the efficiency and reduce the time effective method, according to the forging die, the forging die is designed by combining the shape and size of the part with CAD/CAE technology.
According to the requirements of the forging process, designing the forging die as a combination of CAD technology and the geometry and size of the forging, which is an effective method to reduce the time and enhance the efficiency. The steps of forging a crown forging are as follows. First, preforming and finishing according to the relevant parameters of the crown forging. Second, determine the hot forging sequence to distribute the billet. Third, determine the cavity parameters. As shown in Fig. 1a, the geometric dimension of forging in transverse, longitudinal, and thickness directions (A, B, C) are in the range of 180–200 mm, 60–65 mm, and 70–75 mm, respectively. The cross-section view of crown forging is shown in Fig. 1b.
The diagram in Fig. 1c shows a CAD schematic diagram of the billet used for the crown forging. The billet diameter is 40mm, the billet length is 205mm, and the billet volume is 257141mm3. The crown forging is made of aluminum alloy 6061 and the weight is about 708g. However, the volume of the crown forging is 208613mm3. Generally, the volume of flash accounts for 18.87% of the volume of the billet.
Figure 2 shows the geometry characteristics of the finishing die and the flash design of the top die. As shown in Fig. 2a, the flash design value of B1 is 8mm, which is deliberately specified equal-spaced around the circumferential of the forgings. Another flash design value of B1-1 is 20mm, which is deliberately designated as a damping wall (L1 = 8mm, W1 = 3mm, T1 = 4.5mm) is shown in Fig. 2c, d. In order to limit the outflow of the axial metal on the left and right sides of the crown forging cavity. When the forging material flows, the flash design prevent metal from flowing too fast and allows the excess metal to be confined in the cavity. As shown in Fig. 2b, the bottom of finishing die differs from preforming die for the geometric feature of a small bump.
Figure 3 describes that the design of the die needs to combine the shape and size of the parts with CAD/CAE technology, and then reduce the depth of the cavity, increase the length of the cavity, which improve the filling of the cavity. Then, damping walls are designed on both sides of the crown forging cavity. The damping walls are used to inhibit the outflow of metal, which enhances the filling rate of the forgings. As shown in Fig. 3a, the flash design value of B2 is 16mm, which is deliberately specified equal-spaced around the circumferential of the forgings. Compared with the finishing die when the forging material flows, the flash design is longer to confine the excess metal in the cavity and impede the metal from flowing out of the cavity quickly and generating too much waste. As shown in Fig. 3b, on the left and right sides of the crown forging cavity with damping walls are designed to restrain metal from flowing out. The dimensional characteristics of the damping walls are L = 142mm, W = 2mm, T = 3mm, shown in the enlarged drawing of the bottom die in Fig. 3c, d.
3.2 Original scheme analysis of FEM
As shown in Fig. 4a, (i) forging a round bar crown billet with a diameter of Ø40mm into a shaped billet to obtain a preliminary volume distribution; (ii) bending the billet into a prefabricated shape for preforming forging; (iii) The finishing billet is formed into a preforming part with the required metal distribution through the finishing forging; (iv) The step of completing the preforming shape is a forging operation completed on a 1000 tons mechanical forging press of crank type. In this step, the finishing forging is completed. (v) Trimming the finishing forging is the final forged product. The actual forging is shown in Fig. 4b.
Figure 5a shows the schematic diagram of the top die and the bottom die assembled on the Chin Fong WF2-1000 mechanical crank forging press with a total capacity of 1000 tons. The heating device directly heats up the die with a gas torch. The die is made of heat-treated JIS SKD61 tool steel. The die has been heat-treated to strengthen the die and increase the life of tool. Figure 5b shows a schematic diagram of the Qform simulation of the preforming die.
|
Parameters |
Unite |
Value |
|---|---|---|
|
Billet temperature |
°C |
480 |
|
Die temperature |
°C |
130 |
|
Material of billet |
/ |
AISI Aluminum alloy 6061 |
|
Material of die |
/ |
JIS SKD61 |
|
Heat transfer coefficient (billet to die) |
kw/m2 °C |
3 |
|
Friction factor |
/ |
0.3 |
|
Velocity of top die |
Stroke/minute |
90 |
|
Element style |
/ |
Tetrahedron |
|
Mesh size of billet |
mm |
1 |
|
Mesh size of dies |
mm |
1–16 |
|
Mesh number |
100,000-200,000 |
Table 1 lists the simulation parameters of the hot forging process in FEM setting. The mechanical forging press of crank type 10MN was modeled in the Qform software database. The billet uses the flow stress of AISI aluminum alloy 6061 in the Qform database. The temperature of initial billet is set at 480°C. The material of forging die is set to JIS SKD61. The temperature of the forging die is set at 130°C. The coefficient of friction between the forging die and the workpiece is 0.3. The heat transfer coefficient (die to die) is set to 3 kW / m2°C.
Equilibrium equation:
σij,j = 0 (1)
Constitutive equation:
(2)where σ ̅ is the equivalent stress and 
is the effective strain rate.
Shear friction model equation:
τf = mk (3)
Where τf is the friction stress, m is the friction factor, and k is the shear yield stress limit.
Archard wear model equation:
(4)where P is the normal pressure of the contact surface, V is the wear volume, H is the hardness of die(53HRC), and K is the friction coefficient (0.3), while a, b and c are material dependent constant
As shown in Fig. 6, the original geometric dimensions of the billet diameter and length is 38mm and 193mm, respectively. Similar geometric dimensions of the billet are consistent for Figs. 8 and 9. The maximum load of the preforming is 2.21MN, and the finishing maximum load is 1.74MN. The large preforming load is due to the uneven flow of the metal formed by the billet, so a large load is generated during the forming.
As shown in Fig. 7a, the diameter of the billet used is 40mm and the length is 193mm. The experimental result is that the forging is completely filled except for the right and left sides, which is marked with dotted red square. Figure 7b shows that the used billet has a diameter of 40mm and a length of 205mm. The preforming forging shows that the crown forging is completely filled (dotted cyan square), which is the best formability forging.
Figure 8 shows that the wear of the preforming is homogeneous. As shown in Fig. 8a, the mean wear depth of top die is 4.43E-5mm per forging step. The bottom die mean wear depth is 5.31E-5 mm per forging step, as shown in Fig. 8b. The geometric change of the billet in the bottom die is relatively large, which results in a comparatively high die wear.
As shown in Fig. 9, when the finishing, a large geometric change occurs on the top die, which causes a higher value of die wear to progress on the top die. The die mean wear value of top die is 1.05E-5 mm per forging step, and the die mean wear value of bottom die is 9.33E-6 mm per forging step.
As shown in Fig. 10a, the diameter of the billet used is 40mm and the length is 200mm. The simulation result is that the crown is completely filled except for the right and left sides, which is marked with dotted red square. Figure 10b shows the crown is absolutely filled. The diameter of the billet used is 40mm and the length is 205mm. Consequently, except for the different size of the billets, the other setting conditions are the same as the previous analysis conditions, so as to find the best analysis conditions.
3.3 The preforming die design with controllable deformation zone of damping walls
The cross-sectional view of the die design with controllable deformation zone is shown in Fig. 11a. The FEA results show that the initial die design makes the left and right crowns for shock absorber assembly not completely filled is shown in Fig. 11b. As shown in Fig. 11c, d, in order to ensure the high precision of the crown forging, two relating designs of controllable deformation zone with preformed dressing of CDZ 1 and CDZ 2, respectively. The value of L1 in the die design of CDZ 1 is 22 mm, and the value of L2 in the die design of CDZ 2 is 25 mm. The variable of flash design will be described in Sect. 4.
Since production experience is usually used to design crown forging die, the accuracy of the die cannot be guaranteed. Therefore, this research combines production experience, mathematical methods, and FEM technology to design and optimize crown forging preforming die design.
As show in Fig. 11 for the new preforming die scheme, the variables are the executed billet diameter (D), billet length (L) and flash design (F). However, the corresponding target is the distance between the preforming die and the workpiece (C). Table 2 lists the value range of each variable. In addition, flash design (F) variables include three cases of initial design without damping wall and two relating designs of controllable deformation zone with preformed dressing of CDZ 1 and CDZ 2, respectively. The reason for three level of flash design (F) value in Table 2 is primarily attributed to the design consideration practical application. In reality, flash design (F) is very complex phenomena and highly depending on experience, several modification steps are essentially inevitable after mold tryout. The proposed one level of flash design (F) value of “damping wall” is the potentially implemented way to enhance the material filling. Other complicated process involves the whole mold refurbish was not considered in this paper.
|
Variable |
Unit |
Lower-line |
Median-line |
Upper-line |
|---|---|---|---|---|
|
Diameter (D) |
mm |
40.0 |
40.5 |
41.0 |
|
Length (L) |
mm |
205 |
206 |
207 |
|
Flash design (F) |
/ |
NO-CDZ |
CDZ 1 |
CDZ 2 |
|
Scheme |
Factor 1 Billet diameter (D) mm |
Factor 2 Billet length (L) mm |
Factor 3 Flash design (F) |
Target Distance between die and workpiece (C) mm |
|---|---|---|---|---|
|
1 |
40.0 |
206 |
CDZ 2 |
0.2084 |
|
2 |
41.0 |
206 |
CDZ 2 |
0.3230 |
|
3 |
41.0 |
205 |
CDZ 1 |
0.3154 |
|
4 |
40.5 |
205 |
NO-CDZ |
0.2757 |
|
5 |
40.0 |
207 |
CDZ 1 |
0.2206 |
|
6 |
41.0 |
207 |
CDZ 1 |
0.3484 |
|
7 |
40.5 |
207 |
NO-CDZ |
0.2944 |
|
8 |
40.0 |
206 |
NO-CDZ |
0.2156 |
|
9 |
41.0 |
206 |
NO-CDZ |
0.3407 |
|
10 |
40.5 |
206 |
CDZ 1 |
0.2609 |
|
11 |
40.5 |
206 |
CDZ 1 |
0.2618 |
|
12 |
40.5 |
206 |
CDZ 1 |
0.2613 |
|
13 |
40.0 |
205 |
CDZ 1 |
0.1966 |
|
14 |
40.5 |
207 |
CDZ 2 |
0.2814 |
|
15 |
40.5 |
205 |
CDZ 2 |
0.2495 |
In order to obtain the best target response results, 15 groups were established through the Box-Behnken design. Qform is used to simulate each scheme and additionally, the mean values of distance between die and workpiece (C) were statistically chosen as shown in Table 3.
According to the least square method and simulation results, the equation is obtained by RSM using the fitting function between the factors (D, L, F) and the target (C). Eq. (5) can predict the distance between die and workpiece.
Distance between preforming die and workpiece equation:
C = 308.7–1.706 D − 2.694 L − 0.491 F + 0.01118 D2 + 0.00612 L2 + 0.00780 F2 + 0.00450 DL − 0.00525 DF + 0.00330 LF (7)
|
Factor |
Sum of square |
Freedom |
Mean squares |
F-value |
P-value |
|
|---|---|---|---|---|---|---|
|
Model |
0.031963 |
9 |
0.003551 |
479.42 |
< 0.001 |
Significant |
|
D |
0.029561 |
1 |
0.029561 |
3990.50 |
< 0.001 |
|
|
L |
0.001447 |
1 |
0.001447 |
195.36 |
< 0.001 |
|
|
F |
0.000514 |
1 |
0.000514 |
69.33 |
< 0.001 |
|
|
DL |
0.000020 |
1 |
0.000020 |
2.73 |
0.159 |
|
|
DF |
0.000028 |
1 |
0.000028 |
3.72 |
0.112 |
|
|
LF |
0.000044 |
1 |
0.000044 |
5.88 |
0.060 |
|
|
D2 |
0.000029 |
1 |
0.000029 |
3.90 |
0.105 |
|
|
L2 |
0.000138 |
1 |
0.000138 |
18.7 |
0.008 |
|
|
F2 |
0.000224 |
1 |
0.000224 |
30.29 |
0.003 |
|
|
Residual error |
0.000037 |
5 |
0.000007 |
|||
|
Correlation coefficient |
R2 = 0.9968 |
|||||
The variance analysis of the distance between the preforming die and the workpiece is shown in Table 4. Based on RSM, the influence of this factor is significant, and the P-value must be less than 0.05. Through model variable analysis (distance between die and workpiece), the P value is less than 0.01. However, this model is significant and effective. The factors D, L, F, L2, and F2 in the model have a significant effect on the distance between the preforming die and the workpiece. Table 4 lists the correlation coefficient of 0.9968, indicating that the distance between the preforming die and the workpiece model has accuracy and good fit.
Fig.12 shows the important factors in constructing the statistical significance derived from the statistical analysis of the 3D response surface graph. In these three factors (process parameters): billet diameter, billet length and flash design, when one parameter is constant, the function of the other two factors is studied.
Figure 13 illustrates the main effects plot (MEP) of the three factors on the response variable of distance between preforming die and workpiece. The vertical axis represents the average value of C in micrometers, and the horizontal axis is divided into three parts for each factor, and each level of the factor is shown in its own unit. However, when the D is 40mm, the average value of C is 0.203mm; when the L is 205mm, the average value of C is 0.258mm; when the F is CDZ 1, the average value of C is 0.262mm. In order to obtain the optimized factor, the minimum distance between the preforming die and the workpiece should be selected. From the above, the optimized factor is D: 40mm, L: 205mm, F: CDZ 1.
|
Variable |
Value |
|---|---|
|
D |
40mm |
|
L |
205mm |
|
F |
CDZ 1 |
First of all, the target to be achieved is that the forging must be completely filled. The optimized scheme described in Sect. 4 is that the billet diameter is 40mm, the billet length is 205mm, and the flash design as CDZ 1, as shown in Table 5. The distance between die and workpiece is zero, which is equivalent to a fully filled forging.
As shown in Fig. 14 of contact ratio (100% corresponds to the distance between die and workpiece is zero), the cavity of the crown forging is well filled. In order to conform the filling conditions of the left and right sides of the crown marked with red circles, the cavities filled with different forging steps are shown in Fig. 14. It is recognized that the left and right sides of the crown are fully filled in step 253 with contact ratio of 100%.
The diagrams in Fig. 15 illustrates the maximum loads of the preforming and finishing are 5.59 MN and 3.41 MN, respectively. Compared with the original design (as shown in Fig. 6), the optimized design increases the forging load by 60.47%, while the finishing load increases by 48.97%. Due to the increase in the diameter and length of the billet, the forming load becomes larger, but it improves the problem of filling defects, which are very important to the forging quality.
Figure 16 shows the optimized preforming dies mean wear depth of the crown forging. The preforming die mean wear depth per stroke is 6.64E-5 mm is shown in Fig. 16b. The severely worn area is located in the middle of the bottom die. Consequently, the flash design increases the mean wear depth of the die per stroke, which is in good agreement with the RSM analysis of Fig. 12. In comparing with the original design of the wear depth of each die and the size of the billet, due to the increase in the diameter and length of the billet, the average wear depth of each die of the upper and lower dies increased by 36.74% and 25.05%, respectively.
The diagram in Fig. 17 shows that the wear depth of the finishing die is uniform, and the wear is distributed around the forging die cavity. The average wear depth per stroke of the finishing top die is 1.62E-5 mm is shown in Fig. 17a. Compared with the wear depth of the initial finishing die, the average wear depth per stroke depth of the finishing top and bottom die increased by 35.19% and 49.98%, respectively. Therefore, the optimization of the preforming has a significant impact on the mean wear depth per stroke of the finishing die.
Figure 18 illustrates the color nephograms of the finishing forging of a crown forging including damage, plastic strain, effective stress and temperature. The damage indicates the location where the forging is prone to defects, as shown in Fig. 18. The diagrams in Fig. 18a shows the damage of the billet is uniformly transformed, and severe areas of damage appear in the flash, which is difficult to produce defects on the crown forging. Plastic strain denotes the degree of deformation in the deformation process of the billet. Figure 18b shows that the area of plastic strain is particularly increased from the junction of the crown forging and flash, which results in effective strain accumulation due to the greater resistance to metal flow in the flash area in the cavity. Therefore, in order to ensure the filling of the cavity, generally increasing the damping walls is an effective method. In Fig. 18c, the maximum effective stress region is in the junction of the crown forging and the flashlight. Consequently, the right and left sides of the crown are not easy to deform, and the CDZ is conducive to the filling of the cavity on both sides of the crown. Figure 18d shows that the maximum temperature reaches approximately 508℃. Since the material is concentrated on the corners, the highest temperature appears at the junction of the crown forging and the flashlight. Figure 18b verifies this in reverse. The temperature of the workpiece rises due to the heat generated during forging. In Fig. 18e, the velocity is uniformly distributed in the crown forging, and the maximum velocity occurred in the flash area. The diagrams in Fig. 18f illustrates the displacement is uniform, and the maximum displacement occurs in the cavities on both sides of the crown forging and flash.
Figure 19 demonstrates that the discussion of the effect of preformed dressing on the crown forging, the points tracking of the right crowns for shock absorber assembly. Figure 19a shows the cross-sectional view of the left and right crowns of the shock absorber assembly is red circled in Fig. 14. Because of insufficient filling of the left and right crowns of the shock absorber assembly (as shown in Fig. 10), six points are marked to investigate the effect of the damping wall in CDZ. In Fig. 19b, c, the effective stress point trend tracking and plastic strain point trend tracking are different according to the amount of change of the forging. The greater the amount of change of the forging, the greater the effective stress. However, the effective stresses of P4 and P5 are greater than other effective stresses. Figure 19d shows the velocity point tracking is periodic fall and rise; Thus, the tendency has been consistently justified. Figure 19e states that the temperature tracking trend is regular before the die stroke 20mm, but the temperature tracking trend at P4 and P5 is lower than other temperatures after the die stroke 20mm. Due to P4 and P5 are the fastest to contact the die cavity, and the die temperature is lower than that of the billet material, so P4 and P5 will experience the steepest temperature gradient as contrasted with other points. The temperature induced effect will inevitably inhibit the metal flow due to higher interfacial friction so the forming load will be higher, as well as the effective stress and plastic strain of the material will increase.
The production equipment for crown forging is shown in Fig. 20. The bending equipment is shown in Fig. 20a, it is 110 tons C-frame single crank power presses. Figure 20b illustrates the use of a high-frequency induction heated the billet after bending to the preforming equipment. The huge crank press is used to forge crown forging, which can provide 1000 tons of pressure, preforming and finishing forging as shown in Fig. 20c-d. Figure 20e shows a 60-ton C-frame single-crank power press, which is used to trim the flash of forging.
Eventually, through the air-cooled, the crown forging is shown in Fig. 21a. The diagram in Fig. 21b shows the actual bottom die is designed with RSM optimized damping walls (L = 142mm, W = 2mm) on the left and right sides of the crown forging cavity to increase the filling effectiveness of the forging and prevent excess metal from flowing out. Figure 21c shows the finite element simulation results (left) and experimental results (right) of the grain flow lines distribution after forging. As shown in Fig. 21d and Fig. 21e, a partially enlarged view shows the left side of the actual forging (blue square), in which the crystal grain streamlines of the forging are densely and orderly distributed. The grain flow lines at the bottom of the trench gradually form uniform flow lines along the edge of the trench, which is consistent with the finite element simulation result (orange square). Therefore, experimental grain flow lines distribution shows smooth and non-intersecting dense flow lines which is consistent with the simulation counterparts.
In this article, insufficient filling often occurs in the crown forging with the critical focus on deformation mechanism of controllable deformation zone and die wear of Aluminum Alloy forgings. The three-dimensional finite element model of the optimized performed dressing of damping wall is analyzed by using commercially available FEM software Qform 3D to establish and design of experiment. RSM can explore and explain that complex variables will affect the target response variable to obtain the best response target, and then use three-dimensional finite element to provide detailed information about die wear, forming load, and whether the forging is completely filled. This information is incorporated into the process design. Draw the following conclusions from the final results:
(1) First of all, the requirement is high-precision forgings, and we use experimental design methods to design three billet diameters and three billet lengths. The FEM verified that the optimal size was Ø40 mm, 205 mm, which can make the forging complete filling, and it is actually verified that this billet size can completely filled the forging.
(2) In RSM, the P value of the contact distance model between the mold and the workpiece is less than 0.05, and the correlation coefficient (R-sq) is, which is a highly significant model. Among the three factors, the P values of D, L, and F are less than 0.05, indicating that these three factors have a significant impact on the model.
(3) Compared with the original die design, the other two related designs of controllable deformation zone with preformed dressing of CDZ 1 and CDZ 2, respectively. Based on the response surface method and experimental verification, it is shown that CDZ 1 can effectively improve the filling of crown forgings. It can be seen that the preforming die to be repaired has an important influence on the accuracy of crown forgings.
(4) The FEM simulation results show that the integrated billet diameter is 40mm, the billet length is 205mm and the flash design as CDZ 1. The plastic deformation is evenly distributed, which can significantly improve the formability and filling rate.
Ethical approval
Since the study is performed at a relevant lab, there is no need for ethical approval. Additionally, the paper's main data is not published elsewhere.
Consent to participate
All authors declare that have agreed for authorship, have read and approved the manuscript, and have given the consent for submission and subsequent publication of the manuscript.
Consent to publish
All authors are consenting to publish this article with its included data in The International Journal of Advanced Manufacturing Technology and approve its final version.
Authors’ contributions
All authors contributed equally to the generation and analysis of experimental data, and the development of the manuscript.
Funding
This work was financially funded by Global Tek.
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
The authors confirm that the data supporting the findings of this study are available within the article.
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