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ARTICLE INFOArticle ID: 05-11-03-0023Copyright © 2018 SAE Internationaldoi:10.4271/05-11-03-0023

HistoryReceived: 08 Mar 2018Revised: 28 Jun 2018Accepted: 23 Jul 2018e-Available: 17 Sep 2018

KeywordsMetal forming, Abrasive water jet, Blanking, Hole expansion test, Advanced high-strength steel

CitationBehrens, B., Diaz-Infante, D., Altan, T. Yilkiran, D. et al., “Improving Hole Expansion Ratio by Parameter Adjustment in Abrasive Water Jet Operations for DP800,” SAE Int. J. Mater. Manuf. 11(3):2018,doi:10.4271/05-11-03-0023.

ISSN: 1946-3979e-ISSN: 1946-3987

Improving Hole Expansion Ratio by Parameter Adjustment in Abrasive Water Jet Operations for DP800

Bernd-Arno Behrens, Gottfried Wilhelm Leibniz Universität HannoverDavid Diaz-Infante and Taylan Altan, The Ohio State UniversityDeniz Yilkiran, Kai Wölki, and Sven Hübner, Gottfried Wilhelm Leibniz Universität Hannover

AbstractThe use of Abrasive Water Jet (AWJ) cutting technology can improve the edge stretchability in sheet metal forming. The advances in technology have allowed significant increases in working speeds and pressures, reducing the AWJ operation cost. The main objective of this work was to determine the effect of selected AWJ cutting parameters on the Hole Expansion Ratio (HER) for a DP800 (Dual-Phase) Advanced High-Strength Steel (AHSS) with s0 = 1.2 mm by using a fractional factorial design of experiments for the Hole Expansion Tests (HET). Additionally, the surface rough-ness and residual stresses were measured on the holes looking for a possible relation between them and the measured HER. A deep drawing quality steel DC06 with s0 = 1.0 mm was used for reference. The fracture occurrence was captured by high-speed cameras and by Acoustic Emissions (AE) in order to compare both methods. Results indicated that using, regardless of the material, a small standoff distance, high water pressure, and slow traverse speed and cutting the sample underwater will delay the fracture in a hole expansion operation. Furthermore, the AE have proven to be adequate to measure cracks when optical methods are not feasible. In conclusion, based on the impact of the aforementioned parameters, it is possible to select, appropriately, the AWJ operation parameters to achieve the edge stretchability required for each forming process.

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1. Introduction

Edge cracking is a common problem in sheet metal forming, mainly for Advanced High-Strength Steels (AHSS). The noticeable increase of AHSS in the auto-motive sector, due to the Corporate Average Fuel Economy (CAFE) regulations, makes this fact an interesting problem. The relatively low formability of the AHSS and the damage from previous operations on the edge of the material may lead to splits starting on the edges, mainly due to the tensile stresses in these areas during the forming process [1]. It is well known [2, 3, 4, 5, 6, 7] that the edge stretchability strongly depends on the cutting method (i.e., blanking or laser cutting). However, some materials are more sensitive to the cutting method than others [8]. A more complex way to avoid edge cracking is by manufacturing a material with localized strengthened areas [9]; this could help to reduce the damage at the edge while keeping the rest of the material as strong as required.

Various researchers evaluated different cutting methods [3, 10, 11], consistently blanking provided samples with the lowest edge stretchability, while Abrasive Water Jet (AWJ), laser cutting, or Electrical Discharge Machining (EDM) generated better edges. However, blanking is the most commonly used due to its relatively low cost compared to other methods. With advances in cutting technology, methods such as laser or AWJ cut become more popular based on an increase in the cutting speed and a reduction in the mainte-nance costs; therefore, these methods may be used in low volume production where the cost is justified.

Several studies [12, 13, 14] deal with the optimization of the blanking process evaluated by means of the Hole Expansion Test (HET). Some of them [1, 15, 16] state the importance of the tool wear and the uniform punch/die clear-ance in this operation, between 10% and 20% for AHSS [4, 17]. Regarding the laser cutting technology, some researchers [18, 19] have analyzed the effect of gas pressure, pulse width and frequency, power, focus position, and cutting speed on the kerf characteristics, similar to the ones observed in AWJ operations, such as kerf width, angle, burr height, or produced surface roughness (Figure 1). Thomas [20] used the HET rather than the kerf characteristics to evaluate the effect of the laser cutting parameters on the edge stretchability. Moreover, these results were compared with the ones obtained from the HET for mechanically blanked holes. The compar-ison showed that depending on the input parameters for the laser cutting, it is also possible to produce an edge with lower Hole Expansion Ratio (HER) than the one for a blanked hole.

It has been observed that the use of AWJ technology may lead, in some cases, to better edge stretchability than laser cuts [21]. Furthermore, the AWJ eliminates the problem of thermal distortion or reflectivity due to the material coatings. Nevertheless, there are limitations to the AWJ, mainly because of the blank length that can be cut/placed on the work table.

Just as for the laser cutting technology, there are some studies about the parametric optimization in an AWJ opera-tion. Several researchers have determined that parameters

such as water pressure, traverse speed, standoff distance, material thickness, or nozzle diameter have an impact on the quality of the edge [21, 22, 23, 24]. The most common param-eters involved in AWJ were listed by Kechagias et al. [23] as shown in Figure 2. Table 1 shows the results obtained from Wang et al. [21] who used hot-dipped aluminum/zinc alloy-coated structural steel, s0 = 1 mm thick, in their experiments. Focusing on AHSS, Kechagias et al. [23] applied the AWJ to TRIP700 with s0 = 0.9 mm and TRIP800 with s0 = 1.25 mm steels. With similar findings, TRIP steels were also used by Vaxevanidis et al. [24]. Hascalik et al. [25] only observed the effect of the traverse speed on AWJ of Ti-6Al-4V alloy with s0 = 4.87 mm.

However, these investigations, for the AWJ method, evaluate the edge quality by means of the kerf characteristics rather than by its capability to be stretched without cracks. Therefore, the relation between the parameters used in AWJ and the edge cracking, in sheet metal forming, is missing.

FIGURE 1 Schematic of kerf characteristics in AWJ cutting according to Wang et al. [21].

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l FIGURE 2 Parameters involved in AWJ according to Kechagias et al. [23].

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Behrens et al. / SAE Int. J. Mater. Manuf. / Volume 11, Issue 3, 2018 3


The present study aims to determine, in a water jet opera-tion, the effect of the cutting parameters on the edge stretch-ability evaluated by means of an HET (Figure 3).

Additionally, a possible relation between the surface roughness of the cut hole and the edge stretchability was i nvestigated. The same action was taken for the measured residual stresses. It has been observed that increasing the compressive residual stresses while shearing the material delays the fracture on the blank edge [26], while the tension stresses promote the microcrack generation leading to earlier fracture. For this study, it was hypothesized that the edge stretchability increases for low surface roughness and high compressive residual stresses.

Parallel to the aforementioned objectives, and aiming for the trends of the so-called Industry 4.0, the feasibility of the Acoustic Emissions (AE) to measure cracks in the material is tested and compared with the results obtained by high-speed cameras. [27, 28, 29, 30] have investigated the AE applied to material process monitoring. Other optical measurement methods are also available such as a fiberscopic fringe projec-tion system used by [31].

The authors are aware of the, initially, low practicality of using AWJ cutting technology in mass production. Nevertheless, it must be mentioned that, for specific applica-tions where a high edge stretchability must be assured to produce successfully a part, operations such as the laser or AWJ cut may be the most feasible solution.

2. Experimental Procedure of the HET with Conical Punch

2.1. Input and Output Parameters

Based on the reviewed literature and technical experience, water pressure, traverse speed, standoff distance, abrasive flow ratio, and sample location were the parameters selected for this study (Table 2).

The effects of the five parameters on the HER, the residual stresses, and the surface roughness (Ra) were analyzed by means of a Design of Experiments. The param-eters are varied in two levels, each of them making possible 32 combinations. In the interest of only main effects of the input parameters, a half factorial design was considered adequate for this purpose. Therefore, the 16 experimental combinations shown in Table 3, with 5 replicates for each of them, were analyzed for each material. From the data collected the highest and lowest value from each case were disregarded in order to avoid possible outliers in the experi-ments. It means that only three samples were effectively taken into account for each parameter combination.

2.2. MaterialsThe materials used in this set of experiments were DP800 AHSS with s0 = 1.2 mm and a deep drawing quality steel DC06 with s0 = 1.0 mm. Their chemical and mechanical properties are listed in Tables 4 and 5, respectively.

2.3. Equipment and SamplesAn Erichsen machine was used to conduct the experiments. In accordance to the ISO16630 standard [34], a 60° conical punch, with a 59.7 mm diameter, was used. The punch moved upwards at 1 mm/s to expand the water jet cut hole. Nevertheless, the 10 mm hole described in the ISO16630 was modified intentionally to 20 mm in order to be able to see larger differences between the different cutting parameters [35]. A larger hole size was discarded because, for DC06 with s0 = 1.0 mm, there was a high possibility that the expanded hole would not crack for the given hole/punch ratio [36].

TABLE 1 Effect of AWJ parameters on kerf characteristics according to Wang et al. [21].

Water pressure

Standoff distance

Abrasive flow rate

Traverse speed

Kerf width Increase Increase Not significant

Decrease

Kerf taper Not significant

Increase Not significant

Increase

Surface roughness

With a minimum

Increase Decrease Increase

Burr height Decrease Increase Not significant

Increase

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FIGURE 3 Schematic of the HET.

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TABLE 2 Input parameters to the AWJ operation.

Input parameter “Low value” “High value”Water pressure 200 MPa 400 MPa

Traverse speed 11.1 mm/s 5.55 mm/s

Standoff distance 4.0 mm 2.0 mm

Abrasive flow ratio 0.15 kg/min 0.3 kg/min

Sample location Above water Underwater© SA

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The 20 mm holes cut by water jet were centered in square 130 mm × 130 mm blanks created by shearing. The experi-mental equipment is shown in Figure 4. All the samples were placed burr side up; it means avoiding contact between the burr and the punch.

A 20 mm diameter centering device, located on the top of the punch, was tightly fitted into the holes to assure the concentricity during the experiments, as shown in Figure 5. This device was only removed after the blanks were fully clamped using a 300 kN force, therefore eliminating any off-centering possibility.

High-speed cameras were installed in order to detect the fracture as it is explained later. Additionally, in order to

determine the feasibility of the use of AE to detect fractures, two sensors were fixed on top of the die to measure the AE during the experiments.

2.4. Crack DetectionA significant scattering has been observed by Atzema et al. [37] in HET when using the ISO16630. One of the multiple possible causes for this scatter is the method used to detect the crack occurrence. According to the ISO16630 the crack must go through the thickness of the material before stopping the punch movement. However, nowadays, it is well known that depending on the skills of the technician running the experiment and the method used to detect the crack, there are several delays between the crack occurrence, the crack detection, and the press stop.

2.4.1. Crack Detection by Camera Following the recent trends in the field, the authors decided to use two

TABLE 3 Half factorial design for five parameters and two levels.

CaseStandoff distance

Traverse speed

Abrasive flow ratio

Water pressure

Sample location

1 2.0 mm 11.1 mm/s 0.15 kg/min 200 MPa Above water

2 4.0 mm 11.1 mm/s 0.15 kg/min 200 MPa Underwater











13 2.0 mm 11.1 mm/s 0.30 kg/min

400 MPa Above water

14 4.0 mm 11.1 mm/s 0.30 kg/min

400 MPa Underwater

15 2.0 mm 5.55 mm/s 0.30 kg/min

400 MPa Underwater

16 4.0 mm 5.55 mm/s 0.30 kg/min

400 MPa Above water ©

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TABLE 4 Chemical composition for the examined steel materials. Values provided in mass percentages [32, 33].

Material DC06, s0 = 1.0 mm DP800, s0 = 1.2 mmC 0.02 0.15

Si - 0.42

Mn 0.25 2.06

P 0.02 0.008

S 0.02 0.002

Ti + Nb 0.3 -

Cr + Mo - 0.408

Al - 0.57 © SA

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TABLE 5 Mechanical properties obtained from the tensile test for the examined steel materials [32, 33].

MaterialDC06, s0 = 1.0 mm

DP800, s0 = 1.2 mm

Tensile strength [MPa] 270-350 450-550

Minimum yield strength [MPa] 170-180 780-900

Min total elongation [%] 41 18 © SA

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FIGURE 4 Experimental setup. Top, equipment for the HET. Bottom, equipment for Acoustic Emission detection.

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high-speed cameras from an ARAMIS system, eight pictures/ second, to detect the fracture within an accuracy of ±0.125 mm. The cameras were not located exactly on the top of the center of the experiment but on the right and left side; nevertheless, using this configuration, it is also possible to observe the cracks as well as to measure the hole diameter from the pictures. An example of such optical crack detection is shown in Figure 6.

2.4.2. Crack Detection by AE The AE were recorded threshold-based and evaluated with the AE measuring system AMSY-6 from the manufacturer Vallen Systeme GmbH. During the experiments the following settings were used: threshold 30 dB (sensor 1), threshold 45 dB (sensor 2), rearm time 100 μs, and duration discrimination time 100 μs. Two AE sensors, presented in Figure 7, with different characteris-tics were placed on the tool. Sensor 1 was a broadband sensor mounted with modelling clay with a frequency range of 200-2500 kHz and sensor 2 was a resonant sensor (peak frequency

of about 375 kHz) fastened using glue with a frequency range of 250-700 kHz. To eliminate noise signals sensor-matched digital filters were applied to the sensors: 230-2200 kHz (sen-sor 1) and 95-800 kHz (sensor 2).

The AE were measured with a sampling rate of 5 MHz and the stroke was measured synchronously with a sampling rate of 20 kHz. Furthermore, preamplifiers (type AEP4) which amplify small input signals with 34 dB were used. An example of crack detection using AE is shown in Figure 8.

FIGURE 5 Schematic of the HET tooling.

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FIGURE 6 Crack detection by high-speed camera.

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l FIGURE 7 Used acoustic sensors.

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FIGURE 8 Example of crack detection by acoustic sensors.

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2.5. Evaluation of Edge Stretchability

The high-speed cameras as well as the acoustic sensors were manually synchronized, each one of them individually, with the punch stroke sensor. It is proposed to evaluate the edge stretchability by the punch stroke at crack as well as the HER, two methods which are directly related by geometrical conditions.

In order to evaluate the HER, finite element (FE) simu-lations were conducted using PAM-STAMP. The hole diameter obtained in simulation for the stroke at crack measured in experiments was used to calculate the HER. Additionally, the hole diameter at crack was verified by pictures. Since the real diameter is known for the initial and final stage of the expanded hole, as well as the number of pixels in the pictures of the initial, final, and crack occur-rence stage, a linear interpolation was used to calculate the hole diameter at crack. The sequence of pictures aforemen-tioned is shown in Figure 9. The comparison between both methods showed an error of about ±0.3 mm in the calcu-lated hole expanded diameter. Therefore, calculating the hole diameter at crack by pictures is a feasible method when FE simulations are not available.

For each sample, the location where the water jet path completes the circumference was marked as a reference since it was assumed that this might be the weakest point of the hole.

2.6. Surface Roughness and Residual Stress Measurements

Using a 3D microscope (Keyence VR-3200), the surface rough-ness (Ra) of a sample was determined as the average value of three consistent measurements in the same 1 mm2 spot of the cut edge (Section A in Figure 10). Three samples were measured per case tested.

Following a similar calculation method, the residual stresses on the cut holes were measured using X-ray diffraction method. Tables with the findings are presented in the following section.

3. Results

3.1. Crack LocationWhile selecting the water jet path, it was intended to avoid the initial jet on a point over the circumference to avoid a direct damage to the edge of interest; therefore, it was decided to start the cutting process from the center of the hole. Nevertheless, as expected, a slightly visible notch appears where the water jet path ends. This notch is more visible for the AWJ parameter combinations that match with the worst edge stretchability (Figure 11). This point is considered as the weakest point of the hole. The edge fracture occurred at that location for 158 parts out of 160 tested. This suggests that either this weak point should be intentionally located where no high tensile stresses are expected unless a “smoother” water jet path is selected.

FIGURE 9 Pictures from the blank before, at, and after crack occurrence. Initial diameter was 20 mm.

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FIGURE 10 Surface roughness measurements using a 3D microscope Keyence VR-3200.

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FIGURE 11 Crack location at the weakest point of the cut hole.

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3.2. Edge Stretchability, Extrusion Height and HER

From Figures 12 and 13 below, it can be seen that, regardless of the material used, the parameters that produce a better edge stretchability are consistent; the same is observed on the left side, worst cases, of the tables. These figures also show that there was a difference of about 10 mm in the punch stroke between the best and the worst case for the DC06 with s0 = 1.0 mm steel. This difference was about 5 mm for the DP800 with s0 = 1.2 mm AHSS. These results are translated to HER by using FE simula-tion, illustrated in Figures 14 and 15, to have a better under-standing of the hole diameters that can be achieved for the aforementioned punch strokes. It clearly shows the big differ-ence between the HER for a mild steel and an AHSS.

For DC06 with s0 = 1.0 mm, the difference in the HER between the worst and the best case was about 50%. An increase of about 15% of the HER was observed when using the best AWJ parameter combination for DP800 with s0 = 1.2 mm. Therefore, it is seen that the parameters used in

the process must be also specified when evaluating the HER of AWJ cut samples.

In Figures 14 and 15, Case 15, which is formed by a short standoff distance, a slow traverse speed, a high water pressure, and a sample cut underwater, lead to the highest edge stretch-ability, regardless of the amount of abrasive material used. Case 6 was in the opposite side; as it can be inferred, high standoff distance, fast traverse speed, low water pressure, and sample cut out of the water lead to the lowest edge stretch-ability (Table 6).

3.3. Effect of Input AWJ Parameters on the HER

The data collected from the HET was analyzed using Minitab. Only the main effects were analyzed in this study. Regardless of the material, the parameters resulted ranked in the same order. The traverse speed resulted to be the parameter with the highest impact on the edge stretchability; the lower the speed the better the edge stretchability. Unfortunately, this is a weakness of the AWJ method, since a fast speed is required for mass production.

FIGURE 12 Effect of AWJ parameters on stroke at crack for DC06 with s0 = 1.0 mm. See also Table 3.

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FIGURE 13 Effect of AWJ parameters on stroke at crack for DP800 with s0 = 1.2 mm. See also Table 3.

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l FIGURE 14 Effect of AWJ parameters on the HER for DC06 with s0 = 1.0 mm. See also Table 3.

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FIGURE 15 Effect of AWJ parameters on the HER for DP800 with s0 = 1.2 mm. See also Table 3.

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Using a mechanical press, very often, more than 25 holes a minute can be punched; a maximum of 10 holes in a minute would be cut using the largest speed considered in this study. However, as mentioned earlier, the AWJ is more focused on prototyping, for example, or special operations which do not require a large number of parts but high edge stretchability.

The standoff distance should be kept as short as possible and the water pressure in a high value in order to improve the cut edge. The standoff distance is a simple parameter and it is costless to manipulate it, but it can significantly affect the process. On the other hand, the water pressure is directly related to the electric energy consumption; therefore, this parameter should be adequate according to the user edge requirements. It was observed that when the sample is cut underwater, not only the edge stretchability increases but also the cleanliness of the work place while the noise reduces signifi-cantly creating a less stressful environment. It is hypothesized that cutting underwater may reduce slightly the pressure of the water jet; however, it also focuses better the abrasive parti-cles creating a better cut while avoiding these particles that make the workplace dirty. A very interesting finding was that the abrasive flow ratio did not make a significant difference in the edge stretchability. This may lead to a significant reduction of the cost of the process when the minimum amount of abrasive material is used. A graph with the individual effects for each parameter tested is shown in Figure 16. The larger the

slope of the lines presented, the bigger the effect of the param-eter on the edge stretchability.

3.4. Effect of Surface Roughness on HER

The surface roughness measurements show a very small differ-ence of about 1 micron, for both materials, between the “smoothest” and the “roughest” surface as shown in Figures 17 and 18. These results indicated that the surface roughness is not strongly related to the edge stretchability in AWJ opera-tions. This idea backs up the result which indicated that the abrasive flow ratio has not a significant impact on the edge stretchability, since it is well known that a higher amount of abrasive material will decrease the surface roughness.

3.5. Effect of Residual Stresses on HER

The measured residual stresses, as described in Section 2.6, were in compression and slightly higher, about 20 MPa, for the best than for the worst case, 15 and 6, respectively, when measured for the DC06 with s0 = 1.0 mm material. Due to the sensitivity of the X-ray diffraction method, a lot of scatter was observed when measuring the residual stresses for the DP800 with s0 = 1.2 mm. It is hypothesized that these observations are mainly due to the two phases of the material; it is possible that the same phase was not consistently measured during each attempt. Two samples were measured per case, best and worst, without any success for DP800. The measurements for the same sample, at apparently the same point, using the same machine configuration delivered totally different results. Since the X-ray diffraction was the only measuring method available at the moment of the study, it was not possible to obtain reliable measurements of the residual stresses of DP800; however, the same trend is expected, higher compression stresses could be related to higher edge stretchability. The residual stresses of DC06 with s0 = 1.0 mm are shown in Figure 19.

TABLE 6 Best and worst AWJ parameter combination tested.

CaseStandoff distance

Traverse speed

Abrasive flow ratio

Water pressure

Sample location

6 4.0 mm 11.1 mm/s 0.30 kg/min

200 MPa Above water

15 2.0 mm 5.55 mm/s 0.30 kg/min

400 MPa Underwater

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FIGURE 16 Individual effects of AWJ parameters on edge stretchability.

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FIGURE 17 Effect of AWJ parameters on surface roughness for DC06 with s0 = 1.0 mm before forming. See also Table 3.

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3.6. Crack Detection Using AE

The acoustic signals were acquired for all the HET conducted. In most of the cases the signals were in good correlation with the fracture observed by the cameras. The two more significant cases, 6 and 15, for both materials are illustrated in this article.

As it can be seen in Figure 20, both methods, camera and AE, evaluated Case 15 as the one with the largest edge stretch-ability. The results indicated about the same values at crack for DC06. However, for DP800 the results are off by about 2 mm. In both cases, the AE were delayed in comparison with the visual measurements. It was expected from the previous author’s experience that the AE could recognize a fracture faster than a camera. Therefore, this delay is attributed to an offset error during the synchronization with the punch stroke for one of the crack detection methods since they were set individually. For future experiments, it is suggested that the systems have to be coupled/synchronized. Another possibility is that the points determined as a fracture occurrence using

the AE are not the crack but the crack propagation. In this case, further analysis should be conducted.

It should be mentioned that using AE requires a lot of user expertise to interpret the signals and isolate them from the noise in the surroundings. Extensive work is being conducted at the Institute of Forming Technology and Machines (IFUM) in Germany about the use of AE not only to detect cracks but also to prevent them by finding microcracks.

4. ConclusionsIn this study, the effect of selected AWJ cutting parameters on the edge stretchability, evaluated by means of an HET, was determined. Additionally, the effect on the HET of the surface roughness and residual stresses produced by these cutting parameters was analyzed. The principal conclusions of this study are listed as follows:

• In order to avoid a large scattering in the results, sensors to measure the punch stroke and high-speed cameras to detect the crack start should be used. The stroke at crack may substitute the HER as an edge stretchability parameter due to the savings on measurement time. In any case it is possible to estimate approximately the HER using FE simulations or pictures from the hole within a reasonable error as shown previously.

• The HER can be varied within a certain range by adjusting the AWJ parameters. This can help to optimize the costs of the operation by cutting edges with the quality required for the forming process.

• The crack at the edge tends to occur where the water jet finishes its path. It is recommended to select this point where low tensile stresses are expected in the forming operation.

• The stroke at crack, used as an edge stretchability parameter, increases when increasing the water jet

FIGURE 18 Effect of AWJ parameters on surface roughness for DP800 with s0 = 1.2 mm before forming. See also Table 3.

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l FIGURE 20 Crack detection using AE vs high-speed camera (1 picture/0.125 mm) for DC06 with s0 = 1.0 mm (left) and DP800 with s0 = 1.2 mm (right).

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FIGURE 19 Residual stresses in compression for DC06 with s0 = 1.0 mm.

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pressure and decreasing the traverse speed and the standoff distance.

• The abrasive flow ratio is not cost effective; therefore, it can be minimized to improve operational costs.

• The location of the sample, under or above water, has a small effect. Nevertheless, the noise is reduced and the edge stretchability and the cleanliness of the work space are improved by cutting underwater.

• The traverse speed has the biggest impact. The slower the motion the better the edge stretchability. This represents a disadvantage of the AWJ operation when compared with mechanical punching.

• The surface roughness (Ra) has not a significant relation to the edge stretchability within the parameters tested.

• The residual stresses measured in DC06 with s0 = 1.0 mm suggest that higher compressive stresses help to delay the crack start. This is in agreement with findings from other researchers. Due to the large scatter on the measurements for DP800 with s0 = 1.2 mm no conclusion is obtained for this material.

• The AE seem to be able to detect macrocracks. However, the signal evaluation requires a lot of user expertise. A criterion for crack detection using AE is desirable. Further analysis must be done in this regard.

AcknowledgmentsThe presented work is a result of the project “Acoustic emission analysis for online monitoring in sheet metal forming,” project number BE 1691/183-1, granted by the German Research Foundation (DFG). The authors are thankful for the financial support. Additionally, the authors would like to thank to the Institute of Forming Technology and Machines (IFUM), Leibniz Universität Hannover, for hosting a guest researcher and allowing him to conduct the experiments at their facilities during a scientific exchange as an international collaboration with the Center for Precision Forming at The Ohio State University.

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http://dx.doi.org/10.4271/2015-01-0529https://www.sae.org/publications/technical-papers/content/2014-01-0994https://www.sae.org/publications/technical-papers/content/2014-01-0994http://dx.doi.org/10.4271/2014-01-0994https://www.sae.org/publications/technical-papers/content/2007-01-0340http://dx.doi.org/10.4271/2007-01-0340http://dx.doi.org/10.4271/2007-01-0340https://www.sae.org/publications/technical-papers/content/2010-01-0986


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10.4271/05-11-03-0023: Improving Hole Expansion Ratio by Parameter Adjustment in Abrasive Water Jet Operations for DP80010.4271/05-11-03-0023: Abstract10.4271/05-11-03-0023: Keywords1 Introduction2 Experimental Procedure of the HET with Conical Punch2.1 Input and Output Parameters2.2 Materials2.3 Equipment and Samples2.4 Crack Detection2.4.1 Crack Detection by Camera2.4.2 Crack Detection by AE2.5 Evaluation of Edge Stretchability2.6 Surface Roughness and Residual Stress Measurements

3 Results3.1 Crack Location3.2 Edge Stretchability, Extrusion Height and HER3.3 Effect of Input AWJ Parameters on the HER3.4 Effect of Surface Roughness on HER3.5 Effect of Residual Stresses on HER3.6 Crack Detection Using AE

4 Conclusions

AcknowledgmentsReferences

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