two main objectives: first, to evaluate the impact of different hammering strategies, with an emphasis on the peening angles and directions, on the surface integrity of the gear analogue shafts; second, to establish a basis for the application of MHP to spur gears, necessitated by their complex geometry which requires non-orthogonal MHP approaches. This comprehensive investigation of diverse MHP strategies aims to provide a deeper understanding of the influence MHP on the mechanical properties of gears. The results of this study make a substantial contribution to the field of gear technology by not only establishing foundational methods for implementing MHP in gear manufacturing but also by assessing the service life of gears after MHP treatment. This approach ensures a holistic understanding of the effects of MHP, from process parameters to practical applications in enhancing gear longevity.

## Experimental Setup

This study employs an experimental approach to investigate the effects of various angle settings and machining directions in MHP on the surface structure and edge zone properties of case-hardened 16MnCr5 gear analogue specimens. The specimens are produced through a comprehensive manufacturing process chain that includes pre-turning, stress-relief annealing, finishing turning, case hardening, and grinding. Fig. 2(a) shows a produced analogue specimen.

<figure><img src="image_1336.png" /><figcaption>Fig. 2: (a) Case-hardened 16MnCr5 gear analogue shaft specimen; (b) Experimental test setup with external rotation axis; (c) Spiral-like machining strategy with MHP impact angle.</figcaption></figure>

After manufacturing of the specimens, they are placed in the external rotation axis and subjected to MHP using the Accurapuls hammer system, as shown in Fig. 2(b). Previous analyses have determined that a low stroke *h* in combination with a small step over distance *s* optimally enhances time strengths and reduces wear [12]. For this reason, *h* = 0.3 mm and *s* = 0.07 mm are selected as constant manipulated variables. Additionally, the hammer head diameter is set at 8 mm across all tests.

Guided by findings from a previous study, the selected MHP strategy for this research is a spiral-like pattern [13], as illustrated in Fig. 2(c). This strategy is beneficial as it avoids the need for directional changes, thus preventing repeated peening on the same spot. Employing this spiral-like strategy, impact angles $β_i$ are varied at 15°, 30°, and 45° to assess their effects. Furthermore, each angle is applied in both positive and negative directions to facilitate surface treatment in
two main objectives: first, to evaluate the impact of different hammering strategies, with an emphasis on the peening angles and directions, on the surface integrity of the gear analogue shafts; second, to establish a basis for the application of MHP to spur gears, necessitated by their complex geometry which requires non-orthogonal MHP approaches. This comprehensive investigation of diverse MHP strategies aims to provide a deeper understanding of the influence MHP on the mechanical properties of gears. The results of this study make a substantial contribution to the field of gear technology by not only establishing foundational methods for implementing MHP in gear manufacturing but also by assessing the service life of gears after MHP treatment. This approach ensures a holistic understanding of the effects of MHP, from process parameters to practical applications in enhancing gear longevity.

## Experimental Setup

This study employs an experimental approach to investigate the effects of various angle settings and machining directions in MHP on the surface structure and edge zone properties of case-hardened 16MnCr5 gear analogue specimens. The specimens are produced through a comprehensive manufacturing process chain that includes pre-turning, stress-relief annealing, finishing turning, case hardening, and grinding. Fig. 2(a) shows a produced analogue specimen.

<figure><img src="image_1340.png" /><figcaption>Fig. 2: (a) Case-hardened 16MnCr5 gear analogue shaft specimen; (b) Experimental test setup with external rotation axis; (c) Spiral-like machining strategy with MHP impact angle.</figcaption></figure>

After manufacturing of the specimens, they are placed in the external rotation axis and subjected to MHP using the Accurapuls hammer system, as shown in Fig. 2(b). Previous analyses have determined that a low stroke *h* in combination with a small step over distance *s* optimally enhances time strengths and reduces wear [12]. For this reason, *h* = 0.3 mm and *s* = 0.07 mm are selected as constant manipulated variables. Additionally, the hammer head diameter is set at 8 mm across all tests.

Guided by findings from a previous study, the selected MHP strategy for this research is a spiral-like pattern [13], as illustrated in Fig. 2(c). This strategy is beneficial as it avoids the need for directional changes, thus preventing repeated peening on the same spot. Employing this spiral-like strategy, impact angles $\beta_i$ are varied at 15°, 30°, and 45° to assess their effects. Furthermore, each angle is applied in both positive and negative directions to facilitate surface treatment in
pushing and pulling modes. This methodology allows for the identification of the MHP strategy with the greatest potential for enhancement of the surface hardness and reducing the surface roughness of the gear analogue shafts. The final phase of this research entails a detailed investigation of the edge zone properties of the specimens. This analysis is conducted on specimens after grinding before any surface treatment, named as initial state, and after undergoing MHP using the different mentioned strategies. To increase the reliability of the results, three separate specimens are used for each of these conditions, as outlined in **Table 1**.

<table><caption>Table 1: Overview of the experimental strategies and number of test specimens.</caption><thead><tr><th colspan="2">Initial state</th><th>Number of specimens</th></tr></thead><tbody><tr><td colspan="2">without MHP treatment</td><td>3</td></tr><tr><th>MHP β<sub>i</sub> [°]</th><th>MHP direction</th><th>Number of specimens</th></tr><tr><td>15</td><td>pushing</td><td>3</td></tr><tr><td>15</td><td>pulling</td><td>3</td></tr><tr><td>30</td><td>pushing</td><td>3</td></tr><tr><td>30</td><td>pulling</td><td>3</td></tr><tr><td>45</td><td>pushing</td><td>3</td></tr><tr><td>45</td><td>pulling</td><td>3</td></tr></tbody></table>

## Results and Conclusion

The results of the experimental investigations on case-hardened 16MnCr5 gear analogue shaft specimens subjected to MHP provide insights into the extent to which MHP influences the performance characteristics of gears. The focus is on the changes observed in key mechanical properties, such as surface roughness and hardness.

**Roughness.** 2D geometry and depth of the impacts from MHP are determined through tactile measurements using a Hommel-Etamic nanoscan 855 contour and roughness measuring device. The measurements are taken with a resolution of 0.5 µm and a probe tip rounding of 2 µm, according to standards set by DIN EN ISO 4287 [14] and VDI 2612-5 [15]. In each experimental setup, three distinct measurement paths are traced along the central functional surface of the gear analogue shaft specimens, each with a tactile path length of 4.8 mm. The measurements are oriented longitudinally in relation to the axis of the gear analogue shafts. **Fig. 3** illustrates the average of the obtained data, showing the arithmetic average roughness Ra and the average maximum height Rz measured both before and after MHP surface treatment at various impact angles.
pushing and pulling modes. This methodology allows for the identification of the MHP strategy with the greatest potential for enhancement of the surface hardness and reducing the surface roughness of the gear analogue shafts. The final phase of this research entails a detailed investigation of the edge zone properties of the specimens. This analysis is conducted on specimens after grinding before any surface treatment, named as initial state, and after undergoing MHP using the different mentioned strategies. To increase the reliability of the results, three separate specimens are used for each of these conditions, as outlined in **Table 1**.

<table><caption>Table 1: Overview of the experimental strategies and number of test specimens.</caption><thead><tr><th colspan="2">Initial state</th><th>Number of specimens</th></tr></thead><tbody><tr><td colspan="2">without MHP treatment</td><td>3</td></tr><tr><th>MHP β<sub>i</sub> [°]</th><th>MHP direction</th><th>Number of specimens</th></tr><tr><td>15</td><td>pushing</td><td>3</td></tr><tr><td>15</td><td>pulling</td><td>3</td></tr><tr><td>30</td><td>pushing</td><td>3</td></tr><tr><td>30</td><td>pulling</td><td>3</td></tr><tr><td>45</td><td>pushing</td><td>3</td></tr><tr><td>45</td><td>pulling</td><td>3</td></tr></tbody></table>

## Results and Conclusion

The results of the experimental investigations on case-hardened 16MnCr5 gear analogue shaft specimens subjected to MHP provide insights into the extent to which MHP influences the performance characteristics of gears. The focus is on the changes observed in key mechanical properties, such as surface roughness and hardness.

**Roughness.** 2D geometry and depth of the impacts from MHP are determined through tactile measurements using a Hommel-Etamic nanoscan 855 contour and roughness measuring device. The measurements are taken with a resolution of 0.5 µm and a probe tip rounding of 2 µm, according to standards set by DIN EN ISO 4287 [14] and VDI 2612-5 [15]. In each experimental setup, three distinct measurement paths are traced along the central functional surface of the gear analogue shaft specimens, each with a tactile path length of 4.8 mm. The measurements are oriented longitudinally in relation to the axis of the gear analogue shafts. **Fig. 3** illustrates the average of the obtained data, showing the arithmetic average roughness Ra and the average maximum height Rz measured both before and after MHP surface treatment at various impact angles.
<figure><img src="image_1337.png" /><figcaption>Fig. 3: Surface roughness Ra and Rz of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at different impact angles.</figcaption></figure>

**Fig. 3** clearly demonstrates that MHP reduces surface roughness in comparison to the initial state after grinding, which did not receive any post-processing treatment. It is observed that smaller absolute impact angles in MHP correlate with lower values of Ra and Rz, suggesting that impacts closer to perpendicular to the surface are more effective in achieving plastic deformation, leading to a smoother finish. This improved surface smoothing is due to the higher energy input as a consequence of force being more directly applied into the material, which is more efficiently achieved with near-orthogonal impacts. Thus, the most significant reduction in average roughness is observed at the impact angle of $β_i = -15°$, where it is reduced from $Ra = 0.1033 \ \mu m$ to $Ra = 0.0467 \ \mu m$. In addition, the most significant reduction in average maximum height is achieved at the impact angle of $β_i = 15°$, where it is reduced from $Rz = 0.7367 \ \mu m$ to $Rz = 0.3667 \ \mu m$. The results also indicate that the direction of machining, whether pushing or pulling, does not substantially affect the surface roughness overall.

To avoid the possible issues that can come from 2D measuring surface roughness, which might miss some surface details, 3D surface topographies are also taken in a measuring field of 2×2 mm. **Fig. 4** shows the 3D topography of the case-hardened 16MnCr5 gear analogue shaft specimen before and after MHP at the impact angle of $β_i = -15°$. This comprehensive 3D view of the surface texture ensures a more accurate evaluation of the effect of MHP on enhancing surface finish. The detailed 3D representation confirms the uniform refinement achieved by MHP, which is crucial for optimizing the functional performance of the workpiece and extending its service life.
<figure><img src="image_1341.png" /><figcaption>Fig. 3: Surface roughness Ra and Rz of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at different impact angles.</figcaption></figure>

Fig. 3 clearly demonstrates that MHP reduces surface roughness in comparison to the initial state after grinding, which did not receive any post-processing treatment. It is observed that smaller absolute impact angles in MHP correlate with lower values of Ra and Rz, suggesting that impacts closer to perpendicular to the surface are more effective in achieving plastic deformation, leading to a smoother finish. This improved surface smoothing is due to the higher energy input as a consequence of force being more directly applied into the material, which is more efficiently achieved with near-orthogonal impacts. Thus, the most significant reduction in average roughness is observed at the impact angle of $β_i = -15°$, where it is reduced from $Ra = 0.1033 \ \mu m$ to $Ra = 0.0467 \ \mu m$. In addition, the most significant reduction in average maximum height is achieved at the impact angle of $β_i = 15°$, where it is reduced from $Rz = 0.7367 \ \mu m$ to $Rz = 0.3667 \ \mu m$. The results also indicate that the direction of machining, whether pushing or pulling, does not substantially affect the surface roughness overall.

To avoid the possible issues that can come from 2D measuring surface roughness, which might miss some surface details, 3D surface topographies are also taken in a measuring field of 2×2 mm. Fig. 4 shows the 3D topography of the case-hardened 16MnCr5 gear analogue shaft specimen before and after MHP at the impact angle of $β_i = -15°$. This comprehensive 3D view of the surface texture ensures a more accurate evaluation of the effect of MHP on enhancing surface finish. The detailed 3D representation confirms the uniform refinement achieved by MHP, which is crucial for optimizing the functional performance of the workpiece and extending its service life.
<figure><img src="image_1338.png" /><figcaption>Fig. 4: 3D topographical measurements of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at $\beta_i = -15^\circ$.</figcaption></figure>

The SEM images in **Fig. 5** effectively illustrate the surface smoothing effect induced by MHP. This phenomenon is attributed to the stress applied during the MHP process, which surpasses the yield stress of the material. As a result, plastic deformation occurs within the surface grooves, altering the surface topography and culminating in a more refined and smoother finish. It should be noted that the grooves that persist even after MHP are remnants of the initial machining process.

<figure><img src="image_1339.png" /><figcaption>Fig. 5: SEM images of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment.</figcaption></figure>

**Hardness.** Surface hardness measurements are conducted using the Vickers hardness test, following the standards outlined in DIN EN ISO 6507 [16]. For assessing macro hardness, five individual Vickers measurements are obtained from the functional surface of each specimen and
<figure><img src="image_1342.png" /><figcaption>Fig. 4: 3D topographical measurements of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at $\beta_i = -15°$.</figcaption></figure>

The SEM images in **Fig. 5** effectively illustrate the surface smoothing effect induced by MHP. This phenomenon is attributed to the stress applied during the MHP process, which surpasses the yield stress of the material. As a result, plastic deformation occurs within the surface grooves, altering the surface topography and culminating in a more refined and smoother finish. It should be noted that the grooves that persist even after MHP are remnants of the initial machining process.

<figure><img src="image_1343.png" /><figcaption>Fig. 5: SEM images of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment.</figcaption></figure>

**Hardness.** Surface hardness measurements are conducted using the Vickers hardness test, following the standards outlined in DIN EN ISO 6507 [16]. For assessing macro hardness, five individual Vickers measurements are obtained from the functional surface of each specimen and
subsequently averaged. **Fig. 6** illustrates the measured macro hardness before and after MHP surface treatment at various impact angles.

<figure><img src="image_1340.png" /><figcaption>Fig. 6: Macro hardness of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at different impact angles.</figcaption></figure>

**Fig. 6** reveals that MHP results in increased hardness compared to the initial state. Consistent with the roughness results, the most significant increase in hardness occurs at lower absolute impact angles, i.e. those closer to perpendicular. This is exemplified at an impact angle of $β_i = 15°$, where hardness notably increases from HV = 648 HV30 in initial state to over HV = 846 HV30 after MHP. This enhancement is attributed to the strain hardening induced in the edge zone during the MHP process. Similar to the observations for roughness, the machining direction, whether pushing or pulling, does not significantly influence the hardness outcome. Additionally, the consistency of hardness measurements within each specific impact angle, indicates a uniform and reliable response to the MHP process at that particular angle. This uniformity within the individual sets of measurements at each angle is crucial for confirming the stability and predictability of mechanical properties in gear analogue shafts treated with MHP.

## Summary and Outlook

This study has yielded valuable insights into the surface topography and edge zone properties of case-hardened 16MnCr5 gear analogue shaft specimens, both before and after undergoing surface treatment with MHP with varying machining directions and impact angles. The key observations are as follows:

* MHP effectively improves the surface integrity of case-hardened16MnCr5 gear analogue shafts by reducing surface roughness from $Ra = 0.1033μm$ to $Ra = 0.0467 μm$ and increasing hardness from HV = 648 HV30 to HV = 846 HV30.

* Impact angles closer to being perpendicular to the surface of the workpiece during MHP demonstrate a more pronounced positive effect on the surface integrity of the gear analogue shafts.

* The direction of machining in MHP, whether pushing or pulling, does not significantly influence the treatment outcomes on the workpiece.

The results of this study provide a foundation for future research in surface treatment processes for gear systems. Key areas for subsequent research, stemming from this study, include:

* The present study has addressed the surface integrity of case-hardened16MnCr5 gear analogue shafts affected by MHP. Future research should expand on this by exploring the
subsequently averaged. **Fig. 6** illustrates the measured macro hardness before and after MHP surface treatment at various impact angles.

<figure><img src="image_1344.png" /><figcaption>Fig. 6: Macro hardness of the functional surface of the case-hardened 16MnCr5 specimens before and after MHP treatment at different impact angles.</figcaption></figure>

**Fig. 6** reveals that MHP results in increased hardness compared to the initial state. Consistent with the roughness results, the most significant increase in hardness occurs at lower absolute impact angles, i.e. those closer to perpendicular. This is exemplified at an impact angle of $β_i = 15°$, where hardness notably increases from HV = 648 HV30 in initial state to over HV = 846 HV30 after MHP. This enhancement is attributed to the strain hardening induced in the edge zone during the MHP process. Similar to the observations for roughness, the machining direction, whether pushing or pulling, does not significantly influence the hardness outcome. Additionally, the consistency of hardness measurements within each specific impact angle, indicates a uniform and reliable response to the MHP process at that particular angle. This uniformity within the individual sets of measurements at each angle is crucial for confirming the stability and predictability of mechanical properties in gear analogue shafts treated with MHP.

## Summary and Outlook

This study has yielded valuable insights into the surface topography and edge zone properties of case-hardened 16MnCr5 gear analogue shaft specimens, both before and after undergoing surface treatment with MHP with varying machining directions and impact angles. The key observations are as follows:

* MHP effectively improves the surface integrity of case-hardened16MnCr5 gear analogue shafts by reducing surface roughness from $Ra = 0.1033μm$ to $Ra = 0.0467 μm$ and increasing hardness from HV = 648 HV30 to HV = 846 HV30.

* Impact angles closer to being perpendicular to the surface of the workpiece during MHP demonstrate a more pronounced positive effect on the surface integrity of the gear analogue shafts.

* The direction of machining in MHP, whether pushing or pulling, does not significantly influence the treatment outcomes on the workpiece.

The results of this study provide a foundation for future research in surface treatment processes for gear systems. Key areas for subsequent research, stemming from this study, include:

* The present study has addressed the surface integrity of case-hardened16MnCr5 gear analogue shafts affected by MHP. Future research should expand on this by exploring the
broader impacts of MHP on the overall service life and performance of gears, with a focus on wear resistance, pitting endurance, and frictional characteristics.

* This study has primarily examined the benefits of MHP, leaving its potential drawbacks unexplored. A notable challenge of MHP is its application to components with complex geometries due to accessibility issues. Future research will therefore focus on applying MHP to case-hardened 16MnCr5 spur gears, which have more complex shapes than gear analogue shafts. This will enable a more comprehensive comparison between conventional shot peening technique and MHP.

## Acknowledgements

This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the project "Optimization of the application behavior of spur gears by machine-hammered tooth surfaces—OptiGear2 (project number: 390969378)".

## References

[1] D.H. Trauth. Tribology of Machine Hammer Peened Tool Surfaces for Deep Drawing [Dissertation]: Fraunhofer-Institut für Produktionstechnologie IPT; Rheinisch-Westfälische Technische Hochschule Aachen; Apprimus Verlag [2016].

[2] VDI Verein Deutscher Ingenieure e.V. Maschinelles Oberflächenhämmern: Grundlagen (3416 Blatt 1) [2019].

[3] C. Revilla-Gomez, J-Y. Buffiere, C. Verdu, C. Peyrac, L. Daflon, F. Lefebvre. Assessment of the Surface Hardening Effects from Hammer Peening on High Strength Steel. Procedia Engineering 66:150–60 [2013]. https://doi.org/10.1016/j.proeng.2013.12.070

[4] F. Bleicher, C. Lechner, C. Habersohn, E. Kozeschnik, B. Adjassoho, H. Kaminski. Mechanism of surface modification using machine hammer peening technology. CIRP Annals 61(1):375–8 [2012]. https://doi.org/10.1016/j.cirp.2012.03.139

[5] M. Dadgar, S. Graefe, M. Müller, T. Herrig, T. Bergs. Influences of Machine Hammer Peening on Inconel 718 Workpieces Manufactured by Wire-based Laser Metal Deposition. Procedia CIRP 121(2):192-197 [2024]. https://doi.org/10.1016/j.procir.2023.08.064

[6] P. Sandmann, S. Keller, N. Kashaev, S. Ghouse, P.A. Hooper, B. Klusemann, C.M. Davies. Influence of laser shock peening on the residual stresses in additively manufactured 316L by Laser Powder Bed Fusion: A combined experimental–numerical study. Additive Manufacturing 60:103204 [2022]. https://doi.org/10.1016/j.addma.2022.103204

[7] Y. Xiao, C. Peng. Influence of laser shock peening on fatigue life of transmission gears in aeroengine. 2016 Prognostics and System Health Management Conference (PHM-Chengdu). IEEE 1–4 [2016]. https://doi.org/10.1109/PHM.2016.7819847

[8] F. Klocke, C. Brecher. Zahnrad- und Getriebetechnik: Auslegung – Herstellung – Untersuchung – Simulation. München: Carl Hanser Verlag [2017].

[9] R.D. Lambert, C.J. Aylott, B.A. Shaw. Evaluation of bending fatigue strength in automotive gear steel subjected to shot peening techniques. Procedia Structural Integrity 13:1855–60 [2018]. https://doi.org/10.1016/j.prostr.2018.12.329

[10] R. Rego, C. Löpenhaus, J. Gomes, F. Klocke. Residual stress interaction on gear manufacturing. Journal of Materials Processing Technology 252:249–58 [2018]. https://doi.org/10.1016/j.jmatprotec.2017.09.017

[11] T. Bergs, L. Uhlmann, R Mannens, D. Trauth. Inkrementelle Randzonenmodifikation von einsatzgehärteten 16MnCr5-Stirnrädern mittels maschinellem Oberflächenhämmern. Tribologie und Schmierungstechnik 67(2) 4-17 [2020]. https://doi.org/10.30419/TuS-2020-0008
broader impacts of MHP on the overall service life and performance of gears, with a focus on wear resistance, pitting endurance, and frictional characteristics.

* This study has primarily examined the benefits of MHP, leaving its potential drawbacks unexplored. A notable challenge of MHP is its application to components with complex geometries due to accessibility issues. Future research will therefore focus on applying MHP to case-hardened 16MnCr5 spur gears, which have more complex shapes than gear analogue shafts. This will enable a more comprehensive comparison between conventional shot peening technique and MHP.

## Acknowledgements

This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the project "Optimization of the application behavior of spur gears by machine-hammered tooth surfaces—OptiGear2 (project number: 390969378)".

## References

[1] D.H. Trauth. Tribology of Machine Hammer Peened Tool Surfaces for Deep Drawing [Dissertation]: Fraunhofer-Institut für Produktionstechnologie IPT; Rheinisch-Westfälische Technische Hochschule Aachen; Apprimus Verlag [2016].

[2] VDI Verein Deutscher Ingenieure e.V. Maschinelles Oberflächenhämmern: Grundlagen (3416 Blatt 1) [2019].

[3] C. Revilla-Gomez, J-Y. Buffiere, C. Verdu, C. Peyrac, L. Daflon, F. Lefebvre. Assessment of the Surface Hardening Effects from Hammer Peening on High Strength Steel. Procedia Engineering 66:150–60 [2013]. https://doi.org/10.1016/j.proeng.2013.12.070

[4] F. Bleicher, C. Lechner, C. Habersohn, E. Kozeschnik, B. Adjassoho, H. Kaminski. Mechanism of surface modification using machine hammer peening technology. CIRP Annals 61(1):375–8 [2012]. https://doi.org/10.1016/j.cirp.2012.03.139

[5] M. Dadgar, S. Graefe, M. Müller, T. Herrig, T. Bergs. Influences of Machine Hammer Peening on Inconel 718 Workpieces Manufactured by Wire-based Laser Metal Deposition. Procedia CIRP 121(2):192-197 [2024]. https://doi.org/10.1016/j.procir.2023.08.064

[6] P. Sandmann, S. Keller, N. Kashaev, S. Ghouse, P.A. Hooper, B. Klusemann, C.M. Davies. Influence of laser shock peening on the residual stresses in additively manufactured 316L by Laser Powder Bed Fusion: A combined experimental-numerical study. Additive Manufacturing 60:103204 [2022]. https://doi.org/10.1016/j.addma.2022.103204

[7] Y. Xiao, C. Peng. Influence of laser shock peening on fatigue life of transmission gears in aeroengine. 2016 Prognostics and System Health Management Conference (PHM-Chengdu). IEEE 1–4 [2016]. https://doi.org/10.1109/PHM.2016.7819847

[8] F. Klocke, C. Brecher. Zahnrad- und Getriebetechnik: Auslegung – Herstellung – Untersuchung – Simulation. München: Carl Hanser Verlag [2017].

[9] R.D. Lambert, C.J. Aylott, B.A. Shaw. Evaluation of bending fatigue strength in automotive gear steel subjected to shot peening techniques. Procedia Structural Integrity 13:1855–60 [2018]. https://doi.org/10.1016/j.prostr.2018.12.329

[10] R. Rego, C. Löpenhaus, J. Gomes, F. Klocke. Residual stress interaction on gear manufacturing. Journal of Materials Processing Technology 252:249–58 [2018]. https://doi.org/10.1016/j.jmatprotec.2017.09.017

[11] T. Bergs, L. Uhlmann, R Mannens, D. Trauth. Inkrementelle Randzonenmodifikation von einsatzgehärteten 16MnCr5-Stirnrädern mittels maschinellem Oberflächenhämmern. Tribologie und Schmierungstechnik 67(2) 4-17 [2020]. https://doi.org/10.30419/TuS-2020-0008
[12] D. Mevissen, L. Uhlmann, J. Brimmers, T. Herring, T. Bergs. Wälzfestigkeit maschinell gehämmerter Oberflächenstrukturen im Zahnflankenanalogieversuch. Tribologie und Schmierungstechnik 69(4) 34–40 [2022]. https://doi.org/10.24053/TuS-2022-0021.

[13] L.H. Uhlmann. Optimization of the application behavior of spur gears by means of machine hammered tooth surfaces [M.Sc. thesis]: RWTH Aachen University [2019].

[14] DIN EN ISO 4287: Geometrische Produktspezifikation (GPS) – Oberflächenbeschaffenheit: Tastschnittverfahren – Benennungen, Definitionen und Kenngrößen der Oberflächenbeschaffenheit. 3rd ed. Berlin: Beuth [2010].

[15] VDI-Richtlinie 2612-5: Measurement and testing of gearings Surface roughness measurement of cylindrical gears and bevel gears by means of stylus-type instruments [2015].

[16] DIN-Normenausschuss Materialprüfung. DIN EN ISO 6507-1, Metallische Werkstoffe – Härteprüfung nach Vickers – Teil 1: Prüfverfahren (ISO/DIS 6507-1:2022); Deutsche und Englische Fassung prEN ISO 6507-1 [2022].
[12] D. Mevissen, L. Uhlmann, J. Brimmers, T. Herring, T. Bergs. Wälzfestigkeit maschinell gehämmerter Oberflächenstrukturen im Zahnflankenanalogieversuch. Tribologie und Schmierungstechnik 69(4) 34–40 [2022]. https://doi.org/10.24053/TuS-2022-0021.

[13] L.H. Uhlmann. Optimization of the application behavior of spur gears by means of machine hammered tooth surfaces [M.Sc. thesis]: RWTH Aachen University [2019].

[14] DIN EN ISO 4287: Geometrische Produktspezifikation (GPS) – Oberflächenbeschaffenheit: Tastschnittverfahren – Benennungen, Definitionen und Kenngrößen der Oberflächenbeschaffenheit. 3rd ed. Berlin: Beuth [2010].

[15] VDI-Richtlinie 2612-5: Measurement and testing of gearings Surface roughness measurement of cylindrical gears and bevel gears by means of stylus-type instruments [2015].

[16] DIN-Normenausschuss Materialprüfung. DIN EN ISO 6507-1, Metallische Werkstoffe – Härteprüfung nach Vickers – Teil 1: Prüfverfahren (ISO/DIS 6507-1:2022); Deutsche und Englische Fassung prEN ISO 6507-1 [2022].
# Numerical and experimental analysis of struts joined by electromagnetic forming for aircraft applications

PSYK Verena¹,ᵃ, LINNEMANN Maik¹,ᵇ, HENKEL Marcel¹,ᶜ* and KRÄUSEL Verena¹,ᵈ

¹Fraunhofer Institute for Machine Tools and Forming Technology, Reichenhainer Strasse 88, 09126 Chemnitz, Germany

**Keywords:** Electromagnetic Forming, Aluminum, Finite Element Method (FEM)

**Abstract.** Joining by electromagnetic forming can provide high-strength connections of tubes and connector parts from different materials. In order to qualify this technology for manufacturing components made of high-strength aluminum alloys typically used in aircraft manufacturing a parameter study was performed on form fit joining of tubes (outer diameter: 70 mm, wall thickness: 1.6 mm) and mandrels (diameter: 66.6 mm) both made of EN AW-2024 (T351). Since some aircraft applications, e. g. the so-called z-struts, which support the passenger floor of the airplane, are related to high axial compressive loads and medium axial tensile loads, this load scenario was considered. In order to increase especially the compressive load-bearing capacity, joint configurations featuring direct support of the tube end via a step or a shoulder of the joining partner were designed and investigated. The axial support can increase the transferable compressive load, while the tensile load remains largely unaffected. Attention must be paid to the gap between tube end and axial support, which cannot be fully avoided due to axial material flow during the electromagnetic joining process. Bending the tube end into a groove providing axial support of the tube end enables compressive load-bearing capacities, which can approximate the strength of the tube material. Here, increasing bending angles improve the load-bearing capacity under tensile force, but reduce the transferable compressive load. Multiple groove configurations can provide acceptable load bearing capacity considering tensile and compressive load. Numerical simulation can predict the general behavior of components joined by electromagnetic forming, help to understand the damage mechanisms of the joint and allow identifying trends for joint design.

**Introduction**

The implementation of lightweight design strategies has been in the focus of research for many years. Aerospace industry has taken a pioneering role and still remains a driver for innovation in this field. Developments include the application of materials with particularly high lightweighting potential, such as high-strength aluminum alloys, which have not been widely used in other industries due to the cost structure. Struts and tie rods made of these materials are assembled to build up light frameworks. In this context, joining of tubes and hollow profiles to connector parts is a relevant issue as the resulting connections must be able to withstand forces of up to 250 kN, depending on the specific application in the airplane [1].

Joining by electromagnetic forming is known as an energy- and resource-efficient technology, which is especially suitable for manufacturing high strength joints from similar and dissimilar materials without additives or auxiliary joining elements [2]. The technology invented by Harvey and Brower in the early 1960s [3] uses the energy density of pulsed magnetic fields to apply Lorentz Forces, which accelerate and deform a workpiece made of electrically conductive material. For this purpose, a capacitor battery is charged to a defined voltage and then discharged via a so-called tool coil or inductor, thus imposing a transient highly damped sinusoidal current,

<figure><img src="image_1341.png" /></figure>

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under license by Materials Research Forum LLC.

<footnote>ᵃverena.psyk@iwu.fraunhofer.de, ᵇmaik.linnemann@iwu.fraunhofer.de,</footnote>

<footnote>ᶜmarcel.henkel@iwu.fraunhofer.de, ᵈverena.kraeusel@iwu.fraunhofer.de</footnote>
# Numerical and experimental analysis of struts joined by electromagnetic forming for aircraft applications

PSYK Verena¹,ᵃ, LINNEMANN Maik¹,ᵇ, HENKEL Marcel¹,ᶜ* and KRÄUSEL Verena¹,ᵈ

¹Fraunhofer Institute for Machine Tools and Forming Technology, Reichenhainer Strasse 88, 09126 Chemnitz, Germany

**Keywords:** Electromagnetic Forming, Aluminum, Finite Element Method (FEM)

**Abstract.** Joining by electromagnetic forming can provide high-strength connections of tubes and connector parts from different materials. In order to qualify this technology for manufacturing components made of high-strength aluminum alloys typically used in aircraft manufacturing a parameter study was performed on form fit joining of tubes (outer diameter: 70 mm, wall thickness: 1.6 mm) and mandrels (diameter: 66.6 mm) both made of EN AW-2024 (T351). Since some aircraft applications, e. g. the so-called z-struts, which support the passenger floor of the airplane, are related to high axial compressive loads and medium axial tensile loads, this load scenario was considered. In order to increase especially the compressive load-bearing capacity, joint configurations featuring direct support of the tube end via a step or a shoulder of the joining partner were designed and investigated. The axial support can increase the transferable compressive load, while the tensile load remains largely unaffected. Attention must be paid to the gap between tube end and axial support, which cannot be fully avoided due to axial material flow during the electromagnetic joining process. Bending the tube end into a groove providing axial support of the tube end enables compressive load-bearing capacities, which can approximate the strength of the tube material. Here, increasing bending angles improve the load-bearing capacity under tensile force, but reduce the transferable compressive load. Multiple groove configurations can provide acceptable load bearing capacity considering tensile and compressive load. Numerical simulation can predict the general behavior of components joined by electromagnetic forming, help to understand the damage mechanisms of the joint and allow identifying trends for joint design.

**Introduction**

The implementation of lightweight design strategies has been in the focus of research for many years. Aerospace industry has taken a pioneering role and still remains a driver for innovation in this field. Developments include the application of materials with particularly high lightweighting potential, such as high-strength aluminum alloys, which have not been widely used in other industries due to the cost structure. Struts and tie rods made of these materials are assembled to build up light frameworks. In this context, joining of tubes and hollow profiles to connector parts is a relevant issue as the resulting connections must be able to withstand forces of up to 250 kN, depending on the specific application in the airplane [1].

Joining by electromagnetic forming is known as an energy- and resource-efficient technology, which is especially suitable for manufacturing high strength joints from similar and dissimilar materials without additives or auxiliary joining elements [2]. The technology invented by Harvey and Brower in the early 1960s [3] uses the energy density of pulsed magnetic fields to apply Lorentz Forces, which accelerate and deform a workpiece made of electrically conductive material. For this purpose, a capacitor battery is charged to a defined voltage and then discharged via a so-called tool coil or inductor, thus imposing a transient highly damped sinusoidal current,

<figure><img src="image_1345.png" /></figure>

<footnote>ᵃverena.psyk@iwu.fraunhofer.de, ᵇmaik.linnemann@iwu.fraunhofer.de,</footnote>

<footnote>ᶜmarcel.henkel@iwu.fraunhofer.de, ᵈverena.kraeusel@iwu.fraunhofer.de</footnote>
which induces a magnetic field and a counter-current in the electrically conductive workpiece. The interactions of current and magnetic field result in the above-mentioned Lorentz forces, which form tubular or sheet metal workpieces at velocities of up to 500 m/s and strain rates of up to 10$^5$/s, thus increasing formability of many materials [4].

One of the most promising application fields of electromagnetic forming is joining of aluminum tubes to connector parts. Comprehensive studies dedicated to process analysis and joint design have been carried out considering aluminum alloys from the 6000 series, which are frequently used for series production in the automotive industry. These involved all three joining mechanisms facilitated by electromagnetic forming, specifically interference-fit joining (e.g. [5], [6]), form-fit joining (e.g. [7], [8]) and magnetic pulse welding (e.g. [9], [10]). More recently, the authors of this article have extended the research to higher strength aluminum alloys, specifically EN AW-2024 (T351) [11]. They pointed out that form-fit joining is particularly promising for producing struts for aerospace applications with medium load requirements and investigated the effects of groove parameters (shape, depth, width, and edge radius) and the capacitor charging energy on the load-bearing capacity of the resulting joint in terms of axial compression force. Here, triangular grooves can provide highest load-bearing capacity if groove depth, width, and edge radius as well as capacitor charging energy are well chosen allowing formation of a distinctive undercut without pre-damaging the tube at the edge radius. [11]

However, the load-bearing capacity of conventional single groove configurations (see Fig. 1a) is limited, so that further improvement of the joint design is necessary. Under pure axial compression load, supporting a straight cylindrical tube by a shoulder of the inner mating part (mandrel) as shown in Fig. 1b variant 1 can be expected to be a favorable solution. However, this setup cannot transmit noteworthy tensile forces, while typical requirement profiles in the field of aircraft construction usually include at least moderate axial tensile loads. Therefore, this paper analyzes how the compressive and tensile load-bearing capacities of form-fit joints produced by electromagnetic forming are affected by different joint geometries and arrangements including such an axial support. As numerical simulation in [11] showed that the position of the groove in relation to the tube end can influence the axial material flow into the groove, this study considers grooves arranged at some distance to the tube end (see Fig. 1b variant 2), grooves arranged directly at the end of the tube and (see Fig. 1b variant 3), and combinations of these groove types (see Fig. 1b variant 4).

<figure><img src="image_1342.png" /><figcaption>Figure 1. Different types of groove geometries and arrangements.</figcaption></figure>

## Experimental setup and numerical modelling

Complementary numerical and experimental investigations are carried out to analyze the correlations described above. Similar to [11], tubes and mandrels made of EN AW-2024 (T351) are regarded. The tubes feature an outer diameter of 70 mm and a wall thickness of 1.6 mm while the outer mandrel diameter is set to 66.6 mm. For joining by electromagnetic forming a 4-turn coil with a diameter of 82 mm and a length of 91 mm was applied together with a 2-segment fieldshaper, which focused the magnetic field and the corresponding magnetic pressure to a length of 32 mm. This inductor system is used with a pulsed power generator featuring the electrical
which induces a magnetic field and a counter-current in the electrically conductive workpiece. The interactions of current and magnetic field result in the above-mentioned Lorentz forces, which form tubular or sheet metal workpieces at velocities of up to 500 m/s and strain rates of up to 10$^5$/s, thus increasing formability of many materials [4].

One of the most promising application fields of electromagnetic forming is joining of aluminum tubes to connector parts. Comprehensive studies dedicated to process analysis and joint design have been carried out considering aluminum alloys from the 6000 series, which are frequently used for series production in the automotive industry. These involved all three joining mechanisms facilitated by electromagnetic forming, specifically interference-fit joining (e.g. [5], [6]), form-fit joining (e.g. [7], [8]) and magnetic pulse welding (e.g. [9], [10]). More recently, the authors of this article have extended the research to higher strength aluminum alloys, specifically EN AW-2024 (T351) [11]. They pointed out that form-fit joining is particularly promising for producing struts for aerospace applications with medium load requirements and investigated the effects of groove parameters (shape, depth, width, and edge radius) and the capacitor charging energy on the load-bearing capacity of the resulting joint in terms of axial compression force. Here, triangular grooves can provide highest load-bearing capacity if groove depth, width, and edge radius as well as capacitor charging energy are well chosen allowing formation of a distinctive undercut without pre-damaging the tube at the edge radius. [11]

However, the load-bearing capacity of conventional single groove configurations (see Fig. 1a) is limited, so that further improvement of the joint design is necessary. Under pure axial compression load, supporting a straight cylindrical tube by a shoulder of the inner mating part (mandrel) as shown in Fig. 1b variant 1 can be expected to be a favorable solution. However, this setup cannot transmit noteworthy tensile forces, while typical requirement profiles in the field of aircraft construction usually include at least moderate axial tensile loads. Therefore, this paper analyzes how the compressive and tensile load-bearing capacities of form-fit joints produced by electromagnetic forming are affected by different joint geometries and arrangements including such an axial support. As numerical simulation in [11] showed that the position of the groove in relation to the tube end can influence the axial material flow into the groove, this study considers grooves arranged at some distance to the tube end (see Fig. 1b variant 2), grooves arranged directly at the end of the tube and (see Fig. 1b variant 3), and combinations of these groove types (see Fig. 1b variant 4).

<figure><img src="image_1346.png" /><figcaption>Figure 1. Different types of groove geometries and arrangements.</figcaption></figure>

## Experimental setup and numerical modelling

Complementary numerical and experimental investigations are carried out to analyze the correlations described above. Similar to [11], tubes and mandrels made of EN AW-2024 (T351) are regarded. The tubes feature an outer diameter of 70 mm and a wall thickness of 1.6 mm while the outer mandrel diameter is set to 66.6 mm. For joining by electromagnetic forming a 4-turn coil with a diameter of 82 mm and a length of 91 mm was applied together with a 2-segment fieldshaper, which focused the magnetic field and the corresponding magnetic pressure to a length of 32 mm. This inductor system is used with a pulsed power generator featuring the electrical
properties listed in Table 1. All experiments and simulations considered in this paper were performed using a capacitor charging voltage of 11 kV.

<table><caption>Table 1. Properties of the considered pulsed power generator.</caption><thead><tr><th>Maximum capacitor charging voltage</th><th>Inner resistance</th><th>Capacity</th><th>Inner inductivity</th></tr></thead><tbody><tr><td>25 kV</td><td>5 mΩ</td><td>330 μF</td><td>100 nH</td></tr></tbody></table>

The resulting joints were evaluated via axial push out test and tensile tests, both performed on a universal testing machine Z100 by ZwickRoell at a velocity of 4 mm/min. During the tests, the forces were recorded using a load cell and the corresponding displacement was observed via the crosshead extension. The different test setups are illustrated in Fig. 2. For compression test the specimen (i. e. the tube joined to a mandrel at one end) could be easily inserted between the parallel contact surfaces of the sample holders to apply the forces. For the tensile tests, the tubes were joined to mandrels with attached clamping devices at both ends in order to enable proper load application. The recorded force-displacement-curves in such tests are typically characterized by an initial linear rise followed by a non-linear progression as qualitatively shown in Fig. 2 [11]. The transition from the linear to the non-linear curve section indicates the onset of plastic deformation and the corresponding force was interpreted as load-bearing capacity of the specimen L. To evaluate the further optimization potential of the joint, this load-bearing capacity can be referred to the maximum force that the weaker joining partner (i. e. usually the tube) can transfer without plastic deformation. The latter corresponds to the product of yield strength R<sub>p0.2</sub> and cross section A (see equation 1). When this relative joint quality indicator K approximates 100%, the load-bearing capacity of the joint approximates that of the surrounding structure and further optimization of the joint brings no additional benefit for the component.

$$K = \frac{L}{R_{p0.2} \cdot A} \qquad (1)$$

<figure><img src="image_1343.png" /><figcaption>Figure 2. Experimental setup for a) axial tensile and b) axial compression test.</figcaption></figure>

Numerical modeling and simulation covered both, joining by electromagnetic forming and loading of the joint with axial compression or tensile force in order to quantify the load-bearing capacity. Electromagnetic forming was represented by a coupled electromagnetic and structural mechanical simulation in LS-Dyna [12]. Thereby processes in solid bodies were calculated using finite element methods, while the surrounding air was considered using boundary element methods. All parts were modelled with 8-point hexahedron solid elements. The time step size for coupled simulations was 20 ns. The corresponding model is depicted in Fig. 3. It contains the inductor system, i. e. the tool coil including the fieldshaper, both modeled as rigid copper bodies with an electrical conductivity of 49.6 MS/m, the tube, and the mandrel, both modeled as elasto-plastically deformable aluminum bodies (von Mises material) with a measured flow curve and strain rate scaling and with an electrical conductivity of 29.5 MS/m. The pulsed power generator is represented by its electrical parameters (capacitor charging energy, capacitance, inner inductivity and inner resistance) according to Table 1.
properties listed in Table 1. All experiments and simulations considered in this paper were performed using a capacitor charging voltage of 11 kV.

<table><caption>Table 1. Properties of the considered pulsed power generator.</caption><thead><tr><th>Maximum capacitor<br>charging voltage</th><th>Inner resistance</th><th>Capacity</th><th>Inner inductivity</th></tr></thead><tbody><tr><td>25 kV</td><td>5 mΩ</td><td>330 μF</td><td>100 nH</td></tr></tbody></table>

The resulting joints were evaluated via axial push out test and tensile tests, both performed on a universal testing machine Z100 by ZwickRoell at a velocity of 4 mm/min. During the tests, the forces were recorded using a load cell and the corresponding displacement was observed via the crosshead extension. The different test setups are illustrated in Fig. 2. For compression test the specimen (i. e. the tube joined to a mandrel at one end) could be easily inserted between the parallel contact surfaces of the sample holders to apply the forces. For the tensile tests, the tubes were joined to mandrels with attached clamping devices at both ends in order to enable proper load application. The recorded force-displacement-curves in such tests are typically characterized by an initial linear rise followed by a non-linear progression as qualitatively shown in Fig. 2 [11]. The transition from the linear to the non-linear curve section indicates the onset of plastic deformation and the corresponding force was interpreted as load-bearing capacity of the specimen L. To evaluate the further optimization potential of the joint, this load-bearing capacity can be referred to the maximum force that the weaker joining partner (i. e. usually the tube) can transfer without plastic deformation. The latter corresponds to the product of yield strength R<sub>p0.2</sub> and cross section A (see equation 1). When this relative joint quality indicator K approximates 100%, the load-bearing capacity of the joint approximates that of the surrounding structure and further optimization of the joint brings no additional benefit for the component.

$$K = \frac{L}{R_{p0.2} \cdot A} \qquad (1)$$

<figure><img src="image_1347.png" /><figcaption>Figure 2. Experimental setup for a) axial tensile and b) axial compression test.</figcaption></figure>

Numerical modeling and simulation covered both, joining by electromagnetic forming and loading of the joint with axial compression or tensile force in order to quantify the load-bearing capacity. Electromagnetic forming was represented by a coupled electromagnetic and structural mechanical simulation in LS-Dyna [12]. Thereby processes in solid bodies were calculated using finite element methods, while the surrounding air was considered using boundary element methods. All parts were modelled with 8-point hexahedron solid elements. The time step size for coupled simulations was 20 ns. The corresponding model is depicted in Fig. 3. It contains the inductor system, i. e. the tool coil including the fieldshaper, both modeled as rigid copper bodies with an electrical conductivity of 49.6 MS/m, the tube, and the mandrel, both modeled as elasto-plastically deformable aluminum bodies (von Mises material) with a measured flow curve and strain rate scaling and with an electrical conductivity of 29.5 MS/m. The pulsed power generator is represented by its electrical parameters (capacitor charging energy, capacitance, inner inductivity and inner resistance) according to Table 1.
<figure><img src="image_1344.png" /><figcaption>Figure 3. Numerical models for simulation of joining by electromagnetic forming (a) and testing of the joint under axial compression load (b) and tensile load (c)</figcaption></figure>

Numerical simulation of the mechanical loading of the joined specimen was also performed in LS-Dyna using implicit calculation. The model for evaluation of the load-bearing capacity is relatively simple, containing only the tube and the mandrel. All parameters regarding the mechanical behavior were adopted from the preceding electromagnetic forming simulation. Furthermore, all information relevant regarding the forming history of the parts (i. e. especially the local distribution of stresses and strains in tube and mandrel after joining) are transferred. The time step size was automatically adapted between 10 ns and 1 s. Tensile and compression forces, respectively, are applied as boundary conditions, so that all elasticities from the experimental testing setup are disregarded.

## Influence of axial support of the tube end on the component load-bearing capacity under axial tensile and compression load

To investigate the influence of an axial support of the tube end on the load-bearing capacity of a form-fit joint produced by electromagnetic compression, a triangular groove with a depth of 3 mm, a width of 15 mm and a groove edge radius of 0.6 mm is selected as reference. This geometry was analyzed in detail in [11] and provides relatively high compressive-load-bearing capacity for the conventional joint configuration (i. e. without support of the tube end). This configuration is now supplemented by an additional step in the mandrel, providing axial support of the tube end (see Fig. 4) and both variants of the configuration (with and without axial support) are joined and then exposed to axial tensile and compression load in numerical simulation.

Regarding the electromagnetic joining process, it is important to consider the axial material flow. Although the high forming velocity in combination with inertia effects causes the material to flow predominantly in thickness direction, thus causing increase of the tube's wall thickness if the diameter is reduced in joining by electromagnetic tube compression, axial material flow cannot be completely disregarded [13]. Consequently, the tube end slightly recedes from the mandrel during filling of the groove, so that a small gap occurs. In this specific case, the predefined initial gap in the numerical simulation was set to 1 µm and, due to axial material flow, after joining by electromagnetic forming a gap of 0.24 mm results. However, the ratio of axial and radial material flow depends on the geometric conditions such as the length of the deformation zone and its distance to the end of the workpiece [13]. In an experimental implementation, gap widths in the range of several tenths of a millimeter and slight variations of this gap-width due to positioning inaccuracies must be expected.
<figure><img src="image_1348.png" /><figcaption>Figure 3. Numerical models for simulation of joining by electromagnetic forming (a) and testing of the joint under axial compression load (b) and tensile load (c)</figcaption></figure>

Numerical simulation of the mechanical loading of the joined specimen was also performed in LS-Dyna using implicit calculation. The model for evaluation of the load-bearing capacity is relatively simple, containing only the tube and the mandrel. All parameters regarding the mechanical behavior were adopted from the preceding electromagnetic forming simulation. Furthermore, all information relevant regarding the forming history of the parts (i. e. especially the local distribution of stresses and strains in tube and mandrel after joining) are transferred. The time step size was automatically adapted between 10 ns and 1 s. Tensile and compression forces, respectively, are applied as boundary conditions, so that all elasticities from the experimental testing setup are disregarded.

## Influence of axial support of the tube end on the component load-bearing capacity under axial tensile and compression load

To investigate the influence of an axial support of the tube end on the load-bearing capacity of a form-fit joint produced by electromagnetic compression, a triangular groove with a depth of 3 mm, a width of 15 mm and a groove edge radius of 0.6 mm is selected as reference. This geometry was analyzed in detail in [11] and provides relatively high compressive-load-bearing capacity for the conventional joint configuration (i. e. without support of the tube end). This configuration is now supplemented by an additional step in the mandrel, providing axial support of the tube end (see Fig. 4) and both variants of the configuration (with and without axial support) are joined and then exposed to axial tensile and compression load in numerical simulation.

Regarding the electromagnetic joining process, it is important to consider the axial material flow. Although the high forming velocity in combination with inertia effects causes the material to flow predominantly in thickness direction, thus causing increase of the tube's wall thickness if the diameter is reduced in joining by electromagnetic tube compression, axial material flow cannot be completely disregarded [13]. Consequently, the tube end slightly recedes from the mandrel during filling of the groove, so that a small gap occurs. In this specific case, the predefined initial gap in the numerical simulation was set to 1 µm and, due to axial material flow, after joining by electromagnetic forming a gap of 0.24 mm results. However, the ratio of axial and radial material flow depends on the geometric conditions such as the length of the deformation zone and its distance to the end of the workpiece [13]. In an experimental implementation, gap widths in the range of several tenths of a millimeter and slight variations of this gap-width due to positioning inaccuracies must be expected.
<figure><img src="image_1345.png" /><figcaption>Figure 4. Tube deformation stages under axial tensile (a) and compressive (b) load and corresponding force-displacement-curves.</figcaption></figure>

Under axial tensile load, this effect and the modification of the mandrel in terms of adding a step for support of the tube end has no significant effect. The tube is pulled out of the groove and consequently, the tube radius expands again as shown via representative forming stages during load testing depicted in Fig. 4a. Due to the locally increased strength and stiffness in the region, where the undercut was formed, the generated tube shape remains wavy. The corresponding force-time- and force-displacement curves show the expected approximately linear rise at the beginning, which is then followed by a non-linear curve section. The load-bearing capacity under axial tensile load $L_{tensile}$ is approximately 28 KN, which corresponds to a quality indicator $K_{tensile}$ of 26.6 %. The loading process and the load-bearing capacity of the component is the same as in case of the conventional joint setup without the additional step in the mandrel.

Under compressive load, however, the situation is different as shown in Fig. 4b. At the beginning of the process, the tube is shifted towards the mandrel's shoulder. During this time, the tube lifts from the groove flank facing away the tube end and slides over the groove flank facing the tube end. In the force-time and force-displacement curves this behavior is characterized by a moderate linear rise to approximately 10 kN, which can be attributed to friction. This curve section is followed by another linear section with higher gradient, which can be attributed to elastic
<figure><img src="image_1349.png" /><figcaption>Figure 4. Tube deformation stages under axial tensile (a) and compressive (b) load and corresponding force-displacement-curves.</figcaption></figure>

Under axial tensile load, this effect and the modification of the mandrel in terms of adding a step for support of the tube end has no significant effect. The tube is pulled out of the groove and consequently, the tube radius expands again as shown via representative forming stages during load testing depicted in Fig. 4a. Due to the locally increased strength and stiffness in the region, where the undercut was formed, the generated tube shape remains wavy. The corresponding force-time- and force-displacement curves show the expected approximately linear rise at the beginning, which is then followed by a non-linear curve section. The load-bearing capacity under axial tensile load $L_{tensile}$ is approximately 28 KN, which corresponds to a quality indicator $K_{tensile}$ of 26.6 %. The loading process and the load-bearing capacity of the component is the same as in case of the conventional joint setup without the additional step in the mandrel.

Under compressive load, however, the situation is different as shown in Fig. 4b. At the beginning of the process, the tube is shifted towards the mandrel's shoulder. During this time, the tube lifts from the groove flank facing away the tube end and slides over the groove flank facing the tube end. In the force-time and force-displacement curves this behavior is characterized by a moderate linear rise to approximately 10 kN, which can be attributed to friction. This curve section is followed by another linear section with higher gradient, which can be attributed to elastic
deformation of the material after closing of the initial gap of 0.24 mm, when the tube end is supported by shoulder of the mandrel. The load-bearing capacity under axial pressure load $L_{pressure}$ is 35 kN, which corresponds to a quality indicator $K_{pressure}$ of 33.3 %. This means, that compared to the conventional groove configuration analyzed in [11] with a load bearing capacity of 26 kN an improvement of nearly 35% of the load bearing capacity was obtained while the quality indicator still rised by 10%.

## Influence of groove configurations arranged at the tube end on the component load-bearing capacity under axial tensile and compressive load

In the next step, form-fit joining with grooves at the tube end was investigated. For this purpose, the geometry depicted in Fig. 5 is regarded and groove width and height were varied in a numerical parameter study in order to identify the influence on the load-bearing capacity and the quality indicator for the joint design. Fig. 5 illustrates these values plotted as functions of the angle $\alpha$.

<figure><img src="image_1346.png" /><figcaption>Figure 5. Geometry for investigation of groove configurations arranged at the tube end and corresponding load bearing capacities and quality indicators for the joint design.</figcaption></figure>

Obviously, the load bearing capacity of these configurations under axial compression load is much higher compared to conventional grooves without support of the tube end and compared to the triangular groove setup with support of the tube end presented above. In some cases, the load-bearing capacity of the tube material is even approximated to just a few percent. When comparing the different parameter combinations, it turns out that for the same height $H$, the forces decrease with decreasing width $W$ and correspondingly increasing angle $\alpha$. Similarly, also a general trend of decreasing force-bearing capacity with increasing angle can be observed. A possible reason is, that force flow is more deflected in case of higher $\alpha$-values and at the same time the overlap length between the tube and the mandrel is decreased with decreasing groove width, which results in lower surface friction. Moreover, in case of similar angles a groove height of 1.6 mm seems to be beneficial. This advantage is especially significant in comparison to the higher value of 2.4 mm, but the trend can also be recognized when comparing the lower value of 0.8 mm. For every groove length considered here a height of 1.6 mm, which corresponds to the wall thickness of the tube, leads to maximum transferable force. Considering tensile load, the correlations related to the angle $\alpha$ are reversed. The load-bearing capacity and the quality indicator for the joint design increase with increasing angle and correspondingly increasing undercut formation.

## Influence of multiple groove configuration on the component load-bearing capacity under axial tensile and compressive load

Due to the opposing trends, observed in the preceding section a compromise regarding the load-bearing capacities under tensile and compression load must be found, when designing a joint for a specific application. Considering z-struts (i. e. the struts carrying the passenger floor in a passenger aircraft) as a demanding application from aircraft industry, which requests high compressive-load-bearing capacity and medium tensile-load-bearing capacity, none of the above mentioned solutions
deformation of the material after closing of the initial gap of 0.24 mm, when the tube end is supported by shoulder of the mandrel. The load-bearing capacity under axial pressure load $L_{pressure}$ is 35 kN, which corresponds to a quality indicator $K_{pressure}$ of 33.3 %. This means, that compared to the conventional groove configuration analyzed in [11] with a load bearing capacity of 26 kN an improvement of nearly 35% of the load bearing capacity was obtained while the quality indicator still rised by 10%.

## Influence of groove configurations arranged at the tube end on the component load-bearing capacity under axial tensile and compressive load

In the next step, form-fit joining with grooves at the tube end was investigated. For this purpose, the geometry depicted in Fig. 5 is regarded and groove width and height were varied in a numerical parameter study in order to identify the influence on the load-bearing capacity and the quality indicator for the joint design. Fig. 5 illustrates these values plotted as functions of the angle $\alpha$.

<figure><img src="image_1350.png" /><figcaption>Figure 5. Geometry for investigation of groove configurations arranged at the tube end and corresponding load bearing capacities and quality indicators for the joint design.</figcaption></figure>

Obviously, the load bearing capacity of these configurations under axial compression load is much higher compared to conventional grooves without support of the tube end and compared to the triangular groove setup with support of the tube end presented above. In some cases, the load-bearing capacity of the tube material is even approximated to just a few percent. When comparing the different parameter combinations, it turns out that for the same height $H$, the forces decrease with decreasing width $W$ and correspondingly increasing angle $\alpha$. Similarly, also a general trend of decreasing force-bearing capacity with increasing angle can be observed. A possible reason is, that force flow is more deflected in case of higher $\alpha$-values and at the same time the overlap length between the tube and the mandrel is decreased with decreasing groove width, which results in lower surface friction. Moreover, in case of similar angles a groove height of 1.6 mm seems to be beneficial. This advantage is especially significant in comparison to the higher value of 2.4 mm, but the trend can also be recognized when comparing the lower value of 0.8 mm. For every groove length considered here a height of 1.6 mm, which corresponds to the wall thickness of the tube, leads to maximum transferable force. Considering tensile load, the correlations related to the angle $\alpha$ are reversed. The load-bearing capacity and the quality indicator for the joint design increase with increasing angle and correspondingly increasing undercut formation.

## Influence of multiple groove configuration on the component load-bearing capacity under axial tensile and compressive load

Due to the opposing trends, observed in the preceding section a compromise regarding the load-bearing capacities under tensile and compression load must be found, when designing a joint for a specific application. Considering z-struts (i. e. the struts carrying the passenger floor in a passenger aircraft) as a demanding application from aircraft industry, which requests high compressive-load-bearing capacity and medium tensile-load-bearing capacity, none of the above mentioned solutions
is directly applicable. Therefore, in the next step, a combination was tested in order to combine the acceptable load-bearing capacity under axial tensile load from the triangular groove and the better load-bearing capacity under axial compressive load from the groove arranged at the tube end. Fig. 6 shows the resulting double groove configuration. The two grooves are positioned without distance in-between them in order to shorten the overlap length of tube and mandrel and the corresponding weight of the component as much as possible. The width of the triangular groove implemented here was slightly reduced compared to the measurements in the investigations presented above, because according to [11], this geometry provides highest compressive load bearing capacity for the conventional joint configuration (i. e. without support of the tube end). The width of the groove at the tube's end was adjusted to enable joining the complete groove configuration in one electromagnetic forming process using the inductor system including the fieldshaper with 32 mm long concentration area. Numerical simulation of the electromagnetic forming and testing of the joint provided the load bearing capacities and joint quality indicators listed in Fig. 6. These results show that the combination of the two grooves allowed obtaining nearly the high load-bearing capacity under compressive load provided by the groove at the tube and nearly the sufficiently high load-bearing capacity under tensile load achieved earlier from the triangular groove at the same time.

<figure><img src="image_1347.png" /><figcaption>Figure 6. Multiple groove configuration and corresponding evaluation parameters.</figcaption></figure>

### Load bearing capacity

under axial compression load: $L_{compression} = 80$ kN

under axial tensile load: $L_{tensile} = 27$ kN

### Joint quality indicator

under axial compression load: $K_{compression} = 76\%$

under axial tensile load: $K_{tensile} = 25\%$

For validation purposes mandrels featuring the double groove configuration were manufactured and joined with tubes in electromagnetic forming tests. Afterwards several joined components were exposed to tensile and compression tests and others were examined via metallographic analysis. Fig. 7 compares experimental and numerical results.

Considering the final shape of the joint, experimental and numerical results are in relatively good agreement. Especially the degree of filling of the triangular groove corresponds well, while alignment of the tube to the mandrel at the end of the second groove and at the inner edge of the mandrel is a bit overestimated in the simulation. The final shape in the experimental results suggests that springback happened, which was not exactly reproduced in the numerical simulation.
is directly applicable. Therefore, in the next step, a combination was tested in order to combine the acceptable load-bearing capacity under axial tensile load from the triangular groove and the better load-bearing capacity under axial compressive load from the groove arranged at the tube end. Fig. 6 shows the resulting double groove configuration. The two grooves are positioned without distance in-between them in order to shorten the overlap length of tube and mandrel and the corresponding weight of the component as much as possible. The width of the triangular groove implemented here was slightly reduced compared to the measurements in the investigations presented above, because according to [11], this geometry provides highest compressive load bearing capacity for the conventional joint configuration (i. e. without support of the tube end). The width of the groove at the tube's end was adjusted to enable joining the complete groove configuration in one electromagnetic forming process using the inductor system including the fieldshaper with 32 mm long concentration area. Numerical simulation of the electromagnetic forming and testing of the joint provided the load bearing capacities and joint quality indicators listed in Fig. 6. These results show that the combination of the two grooves allowed obtaining nearly the high load-bearing capacity under compressive load provided by the groove at the tube and nearly the sufficiently high load-bearing capacity under tensile load achieved earlier from the triangular groove at the same time.

<figure><img src="image_1351.png" /><figcaption>Figure 6. Multiple groove configuration and corresponding evaluation parameters.</figcaption></figure>

### Load bearing capacity

under axial compression load: $L_{compression} = 80$ kN

under axial tensile load: $L_{tensile} = 27$ kN

### Joint quality indicator

under axial compression load: $K_{compression} = 76\%$

under axial tensile load: $K_{tensile} = 25\%$

For validation purposes mandrels featuring the double groove configuration were manufactured and joined with tubes in electromagnetic forming tests. Afterwards several joined components were exposed to tensile and compression tests and others were examined via metallographic analysis. Fig. 7 compares experimental and numerical results.

Considering the final shape of the joint, experimental and numerical results are in relatively good agreement. Especially the degree of filling of the triangular groove corresponds well, while alignment of the tube to the mandrel at the end of the second groove and at the inner edge of the mandrel is a bit overestimated in the simulation. The final shape in the experimental results suggests that springback happened, which was not exactly reproduced in the numerical simulation.
<figure><img src="image_1348.png" /><figcaption>Figure 7. Comparison of experimental and numerical results concerning final shape of the joint, simulated deformation stages under axial tensile and compression load, and corresponding force-displacement-curves under tensile and compressive load.</figcaption></figure>

Concerning the force displacement curves under both, tensile and compressive load, the courses of experimental and numerical results are in good qualitative agreement. The most obvious deviation concerns the slope of the rising curve. This can be attributed to the simple displacement measurement via the crosshead extension, which includes elastic deformation of the clamping and the testing machine, while the numerical simulation considers the displacement directly at the specimen end, disregarding all elasticities in the rest of the test setup and is therefore more meaningful. This explanation is strengthened by the fact that the deviation is higher under tensile load, because here the clamping devices bring additional elasticities at both sides of the specimen.

Due to this shortcoming of the experiment the load bearing capacity under tensile load was not reached until 100 s, so that the testing sequence was extended accordingly to obtain all relevant data. Fig. 7 shows that considering the load-bearing capacity, the simulation can predict the ratio of the different values under tensile and compressive loads, but it slightly overestimates the absolute achieved values. This might be attributed to the overestimated contact surface (due to inaccurate simulation of the springback), which is relevant for calculating the friction forces or to
<figure><img src="image_1352.png" /><figcaption>Figure 7. Comparison of experimental and numerical results concerning final shape of the joint, simulated deformation stages under axial tensile and compression load, and corresponding force-displacement-curves under tensile and compressive load.</figcaption></figure>

Concerning the force displacement curves under both, tensile and compressive load, the courses of experimental and numerical results are in good qualitative agreement. The most obvious deviation concerns the slope of the rising curve. This can be attributed to the simple displacement measurement via the crosshead extension, which includes elastic deformation of the clamping and the testing machine, while the numerical simulation considers the displacement directly at the specimen end, disregarding all elasticities in the rest of the test setup and is therefore more meaningful. This explanation is strengthened by the fact that the deviation is higher under tensile load, because here the clamping devices bring additional elasticities at both sides of the specimen.

Due to this shortcoming of the experiment the load bearing capacity under tensile load was not reached until 100 s, so that the testing sequence was extended accordingly to obtain all relevant data. Fig. 7 shows that considering the load-bearing capacity, the simulation can predict the ratio of the different values under tensile and compressive loads, but it slightly overestimates the absolute achieved values. This might be attributed to the overestimated contact surface (due to inaccurate simulation of the springback), which is relevant for calculating the friction forces or to
the material model, which was taken from earlier investigations on sheet material made of the same alloy and exposed to the same heat treatment. According to [14], this procedure is standard in simulation of forming processes using tube material, but it can cause significant deviations. The damage mechanism in the joint is slipping, which well predicted by the simulation.

## Summary and conclusion

Joining by electromagnetic forming is known to be a technology that can provide high-strength connections of tubes and fittings from different materials including conventional aluminum alloys. Recently, attempts were made to qualify the process for high-strength aluminum alloys in order to enable manufacturing typical components for aerospace industry. Such applications frequently require transfer of high compressive and medium tensile load. In order to fulfill this requirement scenario and specially to enhance the load-bearing capacity under compressive axial loading, different joint configurations featuring direct support of the tube end via a step or a shoulder of the joining partner were designed and investigated. Numerical parameter studies simulating the electromagnetic joining process and the subsequent loading of the joined component with axial tensile and compressive force were carried out and the results were interpreted as load-bearing capacity and evaluated via a quality indicator for joint design. Experimental validation was performed via electromagnetic forming tests followed by axial tensile and compression tests. The following conclusions were found:

- Enhancing a conventional e. g. triangular groove configuration by an axial support can increase the transferable compressive load. Attention must be paid to the gap between tube end and axial support, which cannot be fully avoided due to axial material flow during the electromagnetic joining process.

- Bending the tube end into a groove to axially support the tube end can even provide load-bearing capacities against axial compression which approximate the strength of the tube material. The load-bearing capacity under both, tensile and compressive load, depends on the bending angle $α$. Increasing $α$-values improve the load-bearing capacity under tensile force, but reduce the transferable compressive load, so that a compromise must be found depending on the specifically required loadability profile.

- Multiple groove configurations can exploit the advantages of both mentioned groove types to a large extent, thus providing a promising solution for typical aircraft applications.

- Numerical simulation can predict the general behavior of components connected via form-fit joint by electromagnetic forming under axial tensile and compressive load. Thus, it helps to understand the damage mechanisms of the joint and allows identifying trends for joint design, although the quantitative prediction of the load-bearing capacity slightly overestimates the experimental results.

## Acknowledgments

The presented research was performed in the project "Automotive Verfahren und autonome Prozesse für metallische Luftfahrtbauteile". The authors wish to thank the Federal Ministry for Economic Affairs and Climate Action for the financial support and Premium Aerotec for supporting this work with substantial background information regarding strut-applications in aircraft design.

## References

[1] Information on http://www.gmt-gmbh.de

[2] V. Psyk, D. Risch, B.L. Kinsey, A.E. Tekkaya, M. Kleiner, Electromagnetic forming - a review, Journal of Materials Processing Technology 211 (2011) 787-829. https://doi.org/10.1016/j.jmatprotec.2010.12.012

[3] G.W. Harvey, D. Brower, U.S. Patent 2,976,907. (1961).
the material model, which was taken from earlier investigations on sheet material made of the same alloy and exposed to the same heat treatment. According to [14], this procedure is standard in simulation of forming processes using tube material, but it can cause significant deviations. The damage mechanism in the joint is slipping, which well predicted by the simulation.

## Summary and conclusion

Joining by electromagnetic forming is known to be a technology that can provide high-strength connections of tubes and fittings from different materials including conventional aluminum alloys. Recently, attempts were made to qualify the process for high-strength aluminum alloys in order to enable manufacturing typical components for aerospace industry. Such applications frequently require transfer of high compressive and medium tensile load. In order to fulfill this requirement scenario and specially to enhance the load-bearing capacity under compressive axial loading, different joint configurations featuring direct support of the tube end via a step or a shoulder of the joining partner were designed and investigated. Numerical parameter studies simulating the electromagnetic joining process and the subsequent loading of the joined component with axial tensile and compressive force were carried out and the results were interpreted as load-bearing capacity and evaluated via a quality indicator for joint design. Experimental validation was performed via electromagnetic forming tests followed by axial tensile and compression tests. The following conclusions were found:

- Enhancing a conventional e. g. triangular groove configuration by an axial support can increase the transferable compressive load. Attention must be paid to the gap between tube end and axial support, which cannot be fully avoided due to axial material flow during the electromagnetic joining process.

- Bending the tube end into a groove to axially support the tube end can even provide load-bearing capacities against axial compression which approximate the strength of the tube material. The load-bearing capacity under both, tensile and compressive load, depends on the bending angle $α$. Increasing $α$-values improve the load-bearing capacity under tensile force, but reduce the transferable compressive load, so that a compromise must be found depending on the specifically required loadability profile.

- Multiple groove configurations can exploit the advantages of both mentioned groove types to a large extent, thus providing a promising solution for typical aircraft applications.

- Numerical simulation can predict the general behavior of components connected via form-fit joint by electromagnetic forming under axial tensile and compressive load. Thus, it helps to understand the damage mechanisms of the joint and allows identifying trends for joint design, although the quantitative prediction of the load-bearing capacity slightly overestimates the experimental results.

## Acknowledgments

The presented research was performed in the project "Automotive Verfahren und autonome Prozesse für metallische Luftfahrtbauteile". The authors wish to thank the Federal Ministry for Economic Affairs and Climate Action for the financial support and Premium Aerotec for supporting this work with substantial background information regarding strut-applications in aircraft design.

## References

[1] Information on http://www.gmt-gmbh.de

[2] V. Psyk, D. Risch, B.L. Kinsey, A.E. Tekkaya, M. Kleiner, Electromagnetic forming - a review, Journal of Materials Processing Technology 211 (2011) 787-829. https://doi.org/10.1016/j.jmatprotec.2010.12.012

[3] G.W. Harvey, D. Brower, U.S. Patent 2,976,907. (1961).
[4] S.F. Golovashchenko, Material formability and coil design in electromagnetic forming, Journal of Materials Engineering and Performance 16 (2007) 314-320.
https://doi.org/10.1007/s11665-007-9058-7

[5] M. Kleiner, M. Marré, C. Beerwald, W. Homberg, D. Löhe, P. Barreiro, V. Schulze, Investigation of force-fit joints produced by electromagnetic tube compression, Annals of the German Academic Society for Production Engineering WGP 13 (2006) 227-230.

[6] M. Geier, E. Paese, R. Rossi, P. A. R. Rosa, R. P. Homrich, Experimental Analysis of Interference-Fit Joining of Aluminum Tubes by Electromagnetic Forming, IEEE Transactions on Applied Superconductivity 30 (2020). https://doi.org/10.1109/TASC.2020.2972499

[7] C. Weddeling, S. T. Woodward, M. Marré, J. Nellesen, V. Psyk, A. E. Tekkaya, W. Tillmann, Influence of groove characteristics on strength of form-fit joints, Journal of Materials Processing Technology 211 (2011) 925-935. https://doi.org/10.1016/j.jmatprotec.2010.08.004

[8] Y.B. Park, H.Y. Kim, S.I. Oh, Design of axial/torque joint made by electromagnetic forming, Thin-Walled Structures 43 (2005) 826-844. https://doi.org/10.1016/j.tws.2004.10.009

[9] R.N. Raoelison, D. Racine, Z. Zhang, N. Buiron, D. Marceau, M. Rachik, Magnetic pulse welding: Interface of Al/Cu joint and investigation of intermetallic formation effect on the weld features, Journal of Manufacturing Processes 16 (2014) 427-434.
https://doi.org/10.1016/j.jmapro.2014.05.002

[10] H. Yu, Z. Xu, Z. Fan, Z. Zhao, C. Li, Mechanical property and microstructure of aluminum alloy-steel tubes joint by magnetic pulse welding, Materials Science & Engineering: A 561 (2013) 259-265. https://doi.org/10.1016/j.msea.2012.11.015

[11] V. Psyk, M. Linnemann, M. Henkel, V. Kräusel, M. Dix, Joint design for strut connections in airplane structures produced by electromagnetic forming, Proceedings of the 14th International Conference on the Technology of Plasticity - Current Trends in the Technology of Plasticity (2023) 149-156. https://doi.org/10.1007/978-3-031-41341-4_16

[12] P. L'Eplattenier, G. Cook, C. Ashcraft, M. Burger, J. Imbert, M. Worswick, Introduction of an electromagnetism module in LS-DYNA for coupled mechanical-thermal-electromagnetic simulations, Steel Research International 80 (2009) 351-358. https://doi.org/10.2374/SRI08SP152

[13] Psyk. V, Prozesskette Krümmen – Elektromagnetisch Komprimieren – Innenhochdruck-umformen für Rohre und profilförmige Bauteile, PhD Thesis, TU-Dortmund, 2009.

[14] Reuther. F, Mosel. A, Freytag. P, Lambarri. J, Degenkolb. L, Werner. M, Winter. S, Numerical and experimental investigations for hot metal gas forming of stainless steel X2CrTiNb18, Procedia Manufacturing 27 (2019) 112-117.
https://doi.org/10.1016/j.promfg.2018.12.052
[4] S.F. Golovashchenko, Material formability and coil design in electromagnetic forming, Journal of Materials Engineering and Performance 16 (2007) 314-320.
https://doi.org/10.1007/s11665-007-9058-7

[5] M. Kleiner, M. Marré, C. Beerwald, W. Homberg, D. Löhe, P. Barreiro, V. Schulze, Investigation of force-fit joints produced by electromagnetic tube compression, Annals of the German Academic Society for Production Engineering WGP 13 (2006) 227-230.

[6] M. Geier, E. Paese, R. Rossi, P. A. R. Rosa, R. P. Homrich, Experimental Analysis of Interference-Fit Joining of Aluminum Tubes by Electromagnetic Forming, IEEE Transactions on Applied Superconductivity 30 (2020). https://doi.org/10.1109/TASC.2020.2972499

[7] C. Weddeling, S. T. Woodward, M. Marré, J. Nellesen, V. Psyk, A. E. Tekkaya, W. Tillmann, Influence of groove characteristics on strength of form-fit joints, Journal of Materials Processing Technology 211 (2011) 925-935. https://doi.org/10.1016/j.jmatprotec.2010.08.004

[8] Y.B. Park, H.Y. Kim, S.I. Oh, Design of axial/torque joint made by electromagnetic forming, Thin-Walled Structures 43 (2005) 826-844. https://doi.org/10.1016/j.tws.2004.10.009

[9] R.N. Raoelison, D. Racine, Z. Zhang, N. Buiron, D. Marceau, M. Rachik, Magnetic pulse welding: Interface of Al/Cu joint and investigation of intermetallic formation effect on the weld features, Journal of Manufacturing Processes 16 (2014) 427-434.
https://doi.org/10.1016/j.jmapro.2014.05.002

[10] H. Yu, Z. Xu, Z. Fan, Z. Zhao, C. Li, Mechanical property and microstructure of aluminum alloy-steel tubes joint by magnetic pulse welding, Materials Science & Engineering: A 561 (2013) 259-265. https://doi.org/10.1016/j.msea.2012.11.015

[11] V. Psyk, M. Linnemann, M. Henkel, V. Kräusel, M. Dix, Joint design for strut connections in airplane structures produced by electromagnetic forming, Proceedings of the 14th International Conference on the Technology of Plasticity - Current Trends in the Technology of Plasticity (2023) 149-156. https://doi.org/10.1007/978-3-031-41341-4_16

[12] P. L'Eplattenier, G. Cook, C. Ashcraft, M. Burger, J. Imbert, M. Worswick, Introduction of an electromagnetism module in LS-DYNA for coupled mechanical-thermal-electromagnetic simulations, Steel Research International 80 (2009) 351-358. https://doi.org/10.2374/SRI08SP152

[13] Psyk. V, Prozesskette Krümmen – Elektromagnetisch Komprimieren – Innenhochdruck-umformen für Rohre und profilförmige Bauteile, PhD Thesis, TU-Dortmund, 2009.

[14] Reuther. F, Mosel. A, Freytag. P, Lambarri. J, Degenkolb. L, Werner. M, Winter. S, Numerical and experimental investigations for hot metal gas forming of stainless steel X2CrTiNb18, Procedia Manufacturing 27 (2019) 112-117.
https://doi.org/10.1016/j.promfg.2018.12.052
# Modular 3D roller straightening – a new approach to straightening and forming of spring steel wires (X10CrNi18-8)

DAHMS Frederik¹,ª*, HOMBERG Werner¹b

¹ Paderborn University, Forming and Machining Technology, 33098 Paderborn, Germany

ªfd@luf.upb.de, ᵇwh@luf.upb.de

**Keywords:** Incremental Forming, Straightening, Flat Wire, Spring Steel Wire, Sabre Curvatures

**Abstract.** Spring steel wires are usually supplied and stored on coils. The manufacturing and coiling processes of these wires induce inhomogeneous plastic deformations that lead to undesirable residual stresses and varying wire curvatures in the semi-finished product. These residual stresses and curvatures defects are causing varying process conditions in the subsequent manufacturing processes, which have a negative impact on the product quality, leading to wastage and thus affecting the economic and ecological efficiency. Especially the curvature deviations must be compensated for the stability of the subsequent processes. This is usually realised with roller straighteners, which are set manually by the machine operators only at the beginning of a process. In this paper, we introduce a new approach with a modular straightening-machine design and a new set-up process. The more isolated deformation behaviour in a module-based straightener overcomes the complexity of interactions between the close-positioned spaced straightening rollers. This is combined with a set-up process that is independent of conventional material testing, modelling the actual and batch-specific behaviour of the wire in the straightening process. The exact knowledge and time-consuming determination of the material properties thus becomes obsolete. The experimental investigations show the influence of defined straightening strategies on the residual stress evolution and the residual forming limit of the spring steel wires (X10CrNi18-8) in the new straightening process.

**Introduction**

Spring steel wires are usually supplied and stored on coils. The manufacturing and coiling processes of these wires lead to inhomogeneous plastic deformations and friction induced heat that lead to undesirable residual stresses and varying wire curvatures in the semi-finished product [1, 2]. These residual stresses and curvatures defects are causing varying process conditions in the subsequent manufacturing processes, which have a negative impact on the product quality, leading to wastage and failure and thus affecting the economic and ecological efficiency [3]. Especially the curvature deviations must be compensated for the stability of the subsequent manufacturing processes. This is usually realised with roller straighteners (Fig. 1, (a)), which are only set manually by the machine operators at the beginning of a process and are not adjusted during the continuous process. The disadvantages here are the necessary experience of the machine operator, the duration of setting up and the static setting of the rollers that do not respond to the variations in the material properties and curvature in the online process. Therefore, various approaches for the model-based determination of the set-up and control of the straightening-machines have been developed. These include analytical forming models [4, 5], models considering the Bauschinger effect [2, 6], and also FEM [7]. But, all these approaches, of course, require the operator to have a greater understanding of materials science and testing, which increases labour costs and set-up times.

Therefore, the aim of our research project is to enable the development of an automated and online controlled continuous wire straightening process. However, as previously mentioned,

<figure><img src="image_1349.png" /></figure>
# Modular 3D roller straightening – a new approach to straightening and forming of spring steel wires (X10CrNi18-8)

DAHMS Frederik¹,ª*, HOMBERG Werner¹b

¹ Paderborn University, Forming and Machining Technology, 33098 Paderborn, Germany

ªfd@luf.upb.de, ᵇwh@luf.upb.de

**Keywords:** Incremental Forming, Straightening, Flat Wire, Spring Steel Wire, Sabre Curvatures

**Abstract.** Spring steel wires are usually supplied and stored on coils. The manufacturing and coiling processes of these wires induce inhomogeneous plastic deformations that lead to undesirable residual stresses and varying wire curvatures in the semi-finished product. These residual stresses and curvatures defects are causing varying process conditions in the subsequent manufacturing processes, which have a negative impact on the product quality, leading to wastage and thus affecting the economic and ecological efficiency. Especially the curvature deviations must be compensated for the stability of the subsequent processes. This is usually realised with roller straighteners, which are set manually by the machine operators only at the beginning of a process. In this paper, we introduce a new approach with a modular straightening-machine design and a new set-up process. The more isolated deformation behaviour in a module-based straightener overcomes the complexity of interactions between the close-positioned spaced straightening rollers. This is combined with a set-up process that is independent of conventional material testing, modelling the actual and batch-specific behaviour of the wire in the straightening process. The exact knowledge and time-consuming determination of the material properties thus becomes obsolete. The experimental investigations show the influence of defined straightening strategies on the residual stress evolution and the residual forming limit of the spring steel wires (X10CrNi18-8) in the new straightening process.

**Introduction**

Spring steel wires are usually supplied and stored on coils. The manufacturing and coiling processes of these wires lead to inhomogeneous plastic deformations and friction induced heat that lead to undesirable residual stresses and varying wire curvatures in the semi-finished product [1, 2]. These residual stresses and curvatures defects are causing varying process conditions in the subsequent manufacturing processes, which have a negative impact on the product quality, leading to wastage and failure and thus affecting the economic and ecological efficiency [3]. Especially the curvature deviations must be compensated for the stability of the subsequent manufacturing processes. This is usually realised with roller straighteners (Fig. 1, (a)), which are only set manually by the machine operators at the beginning of a process and are not adjusted during the continuous process. The disadvantages here are the necessary experience of the machine operator, the duration of setting up and the static setting of the rollers that do not respond to the variations in the material properties and curvature in the online process. Therefore, various approaches for the model-based determination of the set-up and control of the straightening-machines have been developed. These include analytical forming models [4, 5], models considering the Bauschinger effect [2, 6], and also FEM [7]. But, all these approaches, of course, require the operator to have a greater understanding of materials science and testing, which increases labour costs and set-up times.

Therefore, the aim of our research project is to enable the development of an automated and online controlled continuous wire straightening process. However, as previously mentioned,

<figure><img src="image_1353.png" /></figure>
setting up, modelling and controlling the straightening process on conventional straightening machines is an enormous challenge due to the complex mechanical interactions between the closely spaced straightening rollers.

<figure><img src="image_1350.png" /><figcaption>Fig. 1 (a) (Sabre) straightening-machine with conventional design, (b) 3D straightening-machine with modular design.</figcaption></figure>

Therefore, a new approach on straightening with a modular straightening-machine design (cf. Fig. 1, (b)) and a new calibration process is presented (cf. Fig. 2). With a more isolated deformation behaviour in a module-based straightening machine, we will overcome the complexity of the interactions between the close-positioned straightening rollers, enabling a model-based process control. This is combined with a calibration process that is independent of conventional material testing, modelling the actual and batch-specific behaviour of the wire in the straightening process. The exact knowledge and time-consuming determination of the material properties thus becomes obsolete. With this new approach, bending and sabre curvatures and their combined occurrence (helix) are to be compensated but also purposefully formed. The last module, for the straightening of sabre curvature, can also be pivoted to compensate twisting.

<figure><img src="image_1351.png" /><figcaption>Fig. 2 Concept of the calibration process of the modular straightening machine with exemplary data.</figcaption></figure>

As there are no standardised guidelines on how to set up conventional straightening machines and, of course, the novel modular straightening machine, first a set-up strategy (calibration process) was developed (cf. Fig. 2):

1. Measure the wire's initial curvature *b*, in this case, represented by the vertical height on a defined segment of a circle.

2. Define a straightening strategy, e.g. the desired curvatures *b* after each straightening operation.

3. Cut a set of 250-500 mm long wire segments. At least two per module. More will make it more accurate.

4. Measure the resulting curvature *b* after the first straightening operation in the first module of at least two different roller positions *z*. A starting value for a first positioning of the roller *z* can be calculated using the corresponding strain from a calculated bending curve and the yield strength reported by the supplier or is known from previous calibration processes.
setting up, modelling and controlling the straightening process on conventional straightening machines is an enormous challenge due to the complex mechanical interactions between the closely spaced straightening rollers.

<figure><img src="image_1354.png" /><figcaption>Fig. 1 (a) (Sabre) straightening-machine with conventional design, (b) 3D straightening-machine with modular design.</figcaption></figure>

Therefore, a new approach on straightening with a modular straightening-machine design (cf. Fig. 1, (b)) and a new calibration process is presented (cf. Fig. 2). With a more isolated deformation behaviour in a module-based straightening machine, we will overcome the complexity of the interactions between the close-positioned straightening rollers, enabling a model-based process control. This is combined with a calibration process that is independent of conventional material testing, modelling the actual and batch-specific behaviour of the wire in the straightening process. The exact knowledge and time-consuming determination of the material properties thus becomes obsolete. With this new approach, bending and sabre curvatures and their combined occurrence (helix) are to be compensated but also purposefully formed. The last module, for the straightening of sabre curvature, can also be pivoted to compensate twisting.

<figure><img src="image_1355.png" /><figcaption>Fig. 2 Concept of the calibration process of the modular straightening machine with exemplary data.</figcaption></figure>

As there are no standardised guidelines on how to set up conventional straightening machines and, of course, the novel modular straightening machine, first a set-up strategy (calibration process) was developed (cf. Fig. 2):

1. Measure the wire's initial curvature *b*, in this case, represented by the vertical height on a defined segment of a circle.

2. Define a straightening strategy, e.g. the desired curvatures *b* after each straightening operation.

3. Cut a set of 250-500 mm long wire segments. At least two per module. More will make it more accurate.

4. Measure the resulting curvature *b* after the first straightening operation in the first module of at least two different roller positions *z*. A starting value for a first positioning of the roller *z* can be calculated using the corresponding strain from a calculated bending curve and the yield strength reported by the supplier or is known from previous calibration processes.
5. The model of the actual and batch-specific behaviour of the wire is built up by least-square regression of the resulting curvatures *b* and the roller positions *z*. These can be linear for simple straightening jobs and quadratic for higher accuracy.

6. Roller position *z*₁ can now be determined solving the regression model for the curvature value *b* defined in the straightening strategy.

7. Prepare at least two wires (with *z*₁) for each of the following directional modules for setting them up.

8. The following straightening modules are then set up as described in the previous steps (4-6), whereby the last target value is usually 0.

This process is possible because the design is modular, and therefore, there are no interactions between the modules and their straightening operations. The same set up process is also performed for sabre straightening and forming (cf. Fig. 3 (b)), whereby this process is generally located subsequent (cf. Fig. 1 (b)). The main reason for this layout is that the dominating curvature component is to be straightened first.

<figure><img src="image_1352.png" /><figcaption>Fig. 3 (a) Potential straightening strategies to be assessed. (b) Examples of sabre curvatures.</figcaption></figure>

The above-described guideline for the calibration process makes it possible to follow the path of a defined straightening strategy. However, to decide which strategy is optimal, suitable indicators must be used. Therefore, Fig. 3 illustrates potential straightening strategies (1-5) to be assessed in the following. The initial curvature (0) of the wire (from the coil) is *b* = 9 mm on a 300 mm segment of a circle. Strategy 1 follows the idea of minimizing the forming operations, whereas strategy (5) features three forming operations. Strategies (2-4) are intermediate, with two forming operations and different target curvatures.

## Materials and Methods

The tested material is an austenitic X10CrNi18-8 spring steel flat wire with a cross-section of 3.9 x 0.4 mm². Tensile testing is performed according to DIN EN ISO 6892-1 [8] with Zwick Z100 tensile testing machine. The criterion for evaluating the residual forming limit is defined as the integral of the tensile stress σ over the strain ε until fracture. Residual stress measurements were carried out according to DIN EN 15305:2009 [9] using X-ray diffractometer DR45 by Stresstech GmbH performing sin2ψ method in γ-Fe {311} lattice plane in the depth of approx. 6 µm. The stresses were measured in the centre on the outer and inner side (in relation to the coil winding) in the longitudinal direction of the 500 mm long wire segments.

## Results

The first finding is that the above-described straightening process (using individual straightening modules) is a capable process, i.e. that the paths of the straightening strategy described in Fig. 3 (a) can be followed accurately. Especially, it is also possible to first straighten a wire and then form curvatures like a sabre with the modular 3D straightening-machine in a controlled manner (cf. Fig. 3, b). However, this freedom in the straightening process raises the question of which
5. The model of the actual and batch-specific behaviour of the wire is built up by least-square regression of the resulting curvatures *b* and the roller positions *z*. These can be linear for simple straightening jobs and quadratic for higher accuracy.

6. Roller position *z*₁ can now be determined solving the regression model for the curvature value *b* defined in the straightening strategy.

7. Prepare at least two wires (with *z*₁) for each of the following directional modules for setting them up.

8. The following straightening modules are then set up as described in the previous steps (4-6), whereby the last target value is usually 0.

This process is possible because the design is modular, and therefore, there are no interactions between the modules and their straightening operations. The same set up process is also performed for sabre straightening and forming (cf. Fig. 3 (b)), whereby this process is generally located subsequent (cf. Fig. 1 (b)). The main reason for this layout is that the dominating curvature component is to be straightened first.

<figure><img src="image_1356.png" /><figcaption>Fig. 3 (a) Potential straightening strategies to be assessed. (b) Examples of sabre curvatures.</figcaption></figure>

The above-described guideline for the calibration process makes it possible to follow the path of a defined straightening strategy. However, to decide which strategy is optimal, suitable indicators must be used. Therefore, Fig. 3 illustrates potential straightening strategies (1-5) to be assessed in the following. The initial curvature (0) of the wire (from the coil) is *b* = 9 mm on a 300 mm segment of a circle. Strategy 1 follows the idea of minimizing the forming operations, whereas strategy (5) features three forming operations. Strategies (2-4) are intermediate, with two forming operations and different target curvatures.

## Materials and Methods

The tested material is an austenitic X10CrNi18-8 spring steel flat wire with a cross-section of 3.9 x 0.4 mm². Tensile testing is performed according to DIN EN ISO 6892-1 [8] with Zwick Z100 tensile testing machine. The criterion for evaluating the residual forming limit is defined as the integral of the tensile stress σ over the strain ε until fracture. Residual stress measurements were carried out according to DIN EN 15305:2009 [9] using X-ray diffractometer DR45 by Stresstech GmbH performing sin2ψ method in γ-Fe {311} lattice plane in the depth of approx. 6 µm. The stresses were measured in the centre on the outer and inner side (in relation to the coil winding) in the longitudinal direction of the 500 mm long wire segments.

## Results

The first finding is that the above-described straightening process (using individual straightening modules) is a capable process, i.e. that the paths of the straightening strategy described in Fig. 3 (a) can be followed accurately. Especially, it is also possible to first straighten a wire and then form curvatures like a sabre with the modular 3D straightening-machine in a controlled manner (cf. Fig. 3, b). However, this freedom in the straightening process raises the question of which
strategy should be chosen. Therefore, the evolution of the residual stresses and forming limits regarding the different straightening strategies have been investigated. These two aspects are considered to be antagonistic constraints when optimising straightening strategies.

<figure><img src="image_1353.png" /><figcaption>Fig. 4 Evolution of the curvature b in the reverse straightening experiment for the target values $b = 4.5, 0, -4.5, -9, -27, -35$ mm and an initial curvature of $b = 9$ mm on a 300 mm segment of a circle.</figcaption></figure>

First, the influence of the inhomogeneous properties of the wire are illustrated using a straightforward experiment. The reverse straightening experiment follows the hypothesis that a homogeneous wire regains approximately its initial curvature when it is passed through the straightening machine again with the same straightening parameters but upside down. This should apply in particular if the aim is to mirror the initial curvature (9/-9/9/...). The six target curvature values $b = 4.5, 0, -4.5, -9, -27, -35$ mm are reached accurately with the first forming operation. Then, six alternating forming operations are performed and evaluated. Fig. 4 shows that the resulting curvatures of the second and third straightening operations do not fulfil the hypothesis. This is attributed to the initial inhomogeneity and residual stresses distribution of the wire. The deformation releases the inhomogeneity, which manifests as springback, especially after the first straightening process. This is likely to be caused by the misfit of the residual and load stresses. Then, after the third straightening operation, an almost stationary and alternating path results, which indicates homogeneity (indicated by the average trendline) and thus fulfils the initial hypothesis.

<figure><img src="image_1354.png" /><figcaption>Fig. 5 (a) Near surface residual stress measurements depending on the number of straightening operations with the same position of the roller z (reverse straightening experiment: target $b = 0$). (b) Near surface residual stress measurements in dependence of the number of straightening operations and the strategy.</figcaption></figure>
strategy should be chosen. Therefore, the evolution of the residual stresses and forming limits regarding the different straightening strategies have been investigated. These two aspects are considered to be antagonistic constraints when optimising straightening strategies.

<figure><img src="image_1357.png" /><figcaption>Fig. 4 Evolution of the curvature b in the reverse straightening experiment for the target values $b = 4.5, 0, -4.5, -9, -27, -35$ mm and an initial curvature of $b = 9$ mm on a 300 mm segment of a circle.</figcaption></figure>

First, the influence of the inhomogeneous properties of the wire are illustrated using a straightforward experiment. The reverse straightening experiment follows the hypothesis that a homogeneous wire regains approximately its initial curvature when it is passed through the straightening machine again with the same straightening parameters but upside down. This should apply in particular if the aim is to mirror the initial curvature (9/-9/9/...). The six target curvature values $b = 4.5, 0, -4.5, -9, -27, -35$ mm are reached accurately with the first forming operation. Then, six alternating forming operations are performed and evaluated. Fig. 4 shows that the resulting curvatures of the second and third straightening operations do not fulfil the hypothesis. This is attributed to the initial inhomogeneity and residual stresses distribution of the wire. The deformation releases the inhomogeneity, which manifests as springback, especially after the first straightening process. This is likely to be caused by the misfit of the residual and load stresses. Then, after the third straightening operation, an almost stationary and alternating path results, which indicates homogeneity (indicated by the average trendline) and thus fulfils the initial hypothesis.

<figure><img src="image_1358.png" /><figcaption>Fig. 5 (a) Near surface residual stress measurements depending on the number of straightening operations with the same position of the roller z (reverse straightening experiment: target $b = 0$).</figcaption></figure>

<caption>(b) Near surface residual stress measurements in dependence of the number of straightening operations and the strategy.</caption>
Near-surface residual stress measurements were performed to confirm the observation of the preceding reverse straightening experiment and to establish the basis for the optimization process of straightening strategies. At first Fig. 5 illustrates the initial inhomogeneous residual stress distribution of the wire taken from the coil (straightening operation/strategy 0), stated by a deviation from the inner to the outer surface of approx. 240 MPa. This stress distribution counters a homogeneous forming behaviour, as the major deformation in the straightening process takes place in the surface layer. Fig. 5 (a) shows the corresponding residual stress evolution in the reverse straightening experiment for target value $b = 0$ for the first two straightening operations. The inhomogeneity is reduced but not eliminated. This measurement proves the superposition of an inhomogeneous residual stress distribution with the load stresses, which was assumed in the evaluation of the reverse straightening experiment (cf. Fig. 4). Due to the residual stress distribution, the tensile load on the inner surface layer is reduced, and the compressive load on the outer surface layer is increased in the first forming process. Since a smaller curvature occurs after the first straightening operation than in subsequent straightening operations, it is considered that the decrease in tensile load on the inner surface layer is dominant, although a definite assessment is not possible for the time being without a complete residual stress depth evaluation. Vice versa, this leads to the conclusion that the reverse straightening experiment is a useful method to determine the effect of the residual stresses, which in the case of straightening is considered more relevant than determining the residual stresses per se.

Fig. 5 (b) shows the residual stress distributions and deviations between the inner and outer surface in dependence of the number of straightening operations and straightening strategy. It can be seen that the level of residual stresses is not significantly reduced by straightening. However, the deviation of the residual stress distribution is significantly reduced, and thus homogeneity is achieved. In particular, a higher number of straightening operations (>1) tends to lead to a greater reduction in the deviation of the near-surface residual stresses. But, with a measurement uncertainty of 60 MPa in the confidence interval of 95 %, this tendency is considered less significant regarding the selection of the straightening strategy.

<figure><img src="image_1355.png" /><figcaption>Fig. 6 (a) Residual forming limit in dependence of the number of straightening operations and the strategy. (b) Stress-strain-curve of the flat wire with initial curvature of $b = 9$ mm (from coil).</figcaption></figure>

Another key indicator for defining a straightening strategy is the residual forming limit. Therefore, the influence of different straightening strategies on the residual forming limit was investigated. Fig. 6 (a) shows a trend towards a slight reduction in residual forming limit, but with the standard deviation of the test points being greater than the observed effect. In this context, it has to be considered that with a high-strength spring wire, a significant change in the residual
Near-surface residual stress measurements were performed to confirm the observation of the preceding reverse straightening experiment and to establish the basis for the optimization process of straightening strategies. At first Fig. 5 illustrates the initial inhomogeneous residual stress distribution of the wire taken from the coil (straightening operation/strategy 0), stated by a deviation from the inner to the outer surface of approx. 240 MPa. This stress distribution counters a homogeneous forming behaviour, as the major deformation in the straightening process takes place in the surface layer. Fig. 5 (a) shows the corresponding residual stress evolution in the reverse straightening experiment for target value $b = 0$ for the first two straightening operations. The inhomogeneity is reduced but not eliminated. This measurement proves the superposition of an inhomogeneous residual stress distribution with the load stresses, which was assumed in the evaluation of the reverse straightening experiment (cf. Fig. 4). Due to the residual stress distribution, the tensile load on the inner surface layer is reduced, and the compressive load on the outer surface layer is increased in the first forming process. Since a smaller curvature occurs after the first straightening operation than in subsequent straightening operations, it is considered that the decrease in tensile load on the inner surface layer is dominant, although a definite assessment is not possible for the time being without a complete residual stress depth evaluation. Vice versa, this leads to the conclusion that the reverse straightening experiment is a useful method to determine the effect of the residual stresses, which in the case of straightening is considered more relevant than determining the residual stresses per se.

Fig. 5 (b) shows the residual stress distributions and deviations between the inner and outer surface in dependence of the number of straightening operations and straightening strategy. It can be seen that the level of residual stresses is not significantly reduced by straightening. However, the deviation of the residual stress distribution is significantly reduced, and thus homogeneity is achieved. In particular, a higher number of straightening operations (>1) tends to lead to a greater reduction in the deviation of the near-surface residual stresses. But, with a measurement uncertainty of 60 MPa in the confidence interval of 95 %, this tendency is considered less significant regarding the selection of the straightening strategy.

<figure><img src="image_1359.png" /><figcaption>Fig. 6 (a) Residual forming limit in dependence of the number of straightening operations and the strategy. (b) Stress-strain-curve of the flat wire with initial curvature of $b = 9$ mm (from coil).</figcaption></figure>

Another key indicator for defining a straightening strategy is the residual forming limit. Therefore, the influence of different straightening strategies on the residual forming limit was investigated. Fig. 6 (a) shows a trend towards a slight reduction in residual forming limit, but with the standard deviation of the test points being greater than the observed effect. In this context, it has to be considered that with a high-strength spring wire, a significant change in the residual
forming limit is not to be expected because it has a long history of forming operations and thus has been strongly affected by work hardening. We therefore conclude that within the limits of the investigated straightening strategies there is no influence on the residual forming limit.

## Conclusion and Outlook

In conclusion, the modular design is an advance in straightening technology, enabling low set-up times without extensive material testing. The operator does not need to have a detailed knowledge of materials science and testing. Furthermore, the modular design is the key to optimising the straightening strategy. By isolating the levelling processes and thus eliminating the interactions between the straightening operations, the process becomes controllable. The mere fact that a defined strategy can be easily followed ensures that more residual forming limit will be retained than in conventional straightening processes.

The residual stress analyses show that significant homogenisation is already achieved with a single straightening operation. However, the residual stresses are not significantly reduced, which is usually not necessary with the present compressive residual stresses. But, as these measurements have near-surface and microscopically resolution, further investigations with in-depth and macroscopic resolution are required. An (optical) hole-drilling-method [10] is therefore being adapted in parallel to this work with regard to the wire-specific challenges. However, even without this knowledge, the actual material behaviour, i.e. the sum of the actual material properties of the wire, including residual stresses, is determined by the calibration process of the modular straightening machine. In this context the developed reverse straightening experiment is a useful method to determine the effect of the residual stresses, especially their inhomogeneity, which in the case of straightening is considered more relevant than determining the residual stresses profiles per se.

Regarding the variations in wire properties that occur during the continuous straightening process, an online-control design and a corresponding compensation strategy are required. Here, it appears to be most sensible to pursue the objective of controlling the straightness at the last straightening module of each type because this does not cause any interactions with preceding straightening operations. This possibility is a key benefit of the modular design compared to the conventional straighteners. However, it is necessary to find measurable process quantities that enable a closed-loop control. These may include force, eddy current or tactile and optical curvature measurements of the straightening process or the subsequent processes.

## Acknowledgement

The authors would like to thank the German Federal Ministry of Economics and Climate Protection for funding this research project: "Development of an innovative straightening machine for three-dimensional straightening and forming", (AiF Research Association: FOSTA-No. 1565, IGF-No. 22114 N / 1).

## References

[1] P. Enghag, Steel wire technology, Materialteknik HB, Orebro, Swedan, 2004.

[2] E. Doege, R. Menz, S. Huinink, Analysis of the levelling process based upon an analytic forming model, CIRP Annals - Manufacturing Technology 51 (2002) 191–194.
https://doi.org/10.1016/S0007-8506(07)61497-8

[3] P.J. Withers, Residual stress and its role in failure, Rep. Prog. Phys. 70 (2007) 2211–2264.
https://doi.org/10.1088/0034-4885/70/12/R04

[4] W. Guericke, M. Paech, E. Albert, Simulating the wire straightening process, Wire Technology International 8 (1996).
forming limit is not to be expected because it has a long history of forming operations and thus has been strongly affected by work hardening. We therefore conclude that within the limits of the investigated straightening strategies there is no influence on the residual forming limit.

## Conclusion and Outlook

In conclusion, the modular design is an advance in straightening technology, enabling low set-up times without extensive material testing. The operator does not need to have a detailed knowledge of materials science and testing. Furthermore, the modular design is the key to optimising the straightening strategy. By isolating the levelling processes and thus eliminating the interactions between the straightening operations, the process becomes controllable. The mere fact that a defined strategy can be easily followed ensures that more residual forming limit will be retained than in conventional straightening processes.

The residual stress analyses show that significant homogenisation is already achieved with a single straightening operation. However, the residual stresses are not significantly reduced, which is usually not necessary with the present compressive residual stresses. But, as these measurements have near-surface and microscopically resolution, further investigations with in-depth and macroscopic resolution are required. An (optical) hole-drilling-method [10] is therefore being adapted in parallel to this work with regard to the wire-specific challenges. However, even without this knowledge, the actual material behaviour, i.e. the sum of the actual material properties of the wire, including residual stresses, is determined by the calibration process of the modular straightening machine. In this context the developed reverse straightening experiment is a useful method to determine the effect of the residual stresses, especially their inhomogeneity, which in the case of straightening is considered more relevant than determining the residual stresses profiles per se.

Regarding the variations in wire properties that occur during the continuous straightening process, an online-control design and a corresponding compensation strategy are required. Here, it appears to be most sensible to pursue the objective of controlling the straightness at the last straightening module of each type because this does not cause any interactions with preceding straightening operations. This possibility is a key benefit of the modular design compared to the conventional straighteners. However, it is necessary to find measurable process quantities that enable a closed-loop control. These may include force, eddy current or tactile and optical curvature measurements of the straightening process or the subsequent processes.

## Acknowledgement

The authors would like to thank the German Federal Ministry of Economics and Climate Protection for funding this research project: "Development of an innovative straightening machine for three-dimensional straightening and forming", (AiF Research Association: FOSTA-No. 1565, IGF-No. 22114 N / 1).

## References

[1] P. Enghag, Steel wire technology, Materialteknik HB, Orebro, Swedan, 2004.

[2] E. Doege, R. Menz, S. Huinink, Analysis of the levelling process based upon an analytic forming model, CIRP Annals - Manufacturing Technology 51 (2002) 191–194.
https://doi.org/10.1016/S0007-8506(07)61497-8

[3] P.J. Withers, Residual stress and its role in failure, Rep. Prog. Phys. 70 (2007) 2211–2264.
https://doi.org/10.1088/0034-4885/70/12/R04

[4] W. Guericke, M. Paech, E. Albert, Simulating the wire straightening process, Wire Technology International 8 (1996).
[5] I. Khromov, R. Kawalla, Simulation of a steel wire straightening taking into account nonlinear hardening of material, Eng. Technol. Appl. Sci. Res. 2 (2012) 320-324.
https://doi.org/10.48084/etasr.275

[6] W. Guericke, Material model describing cyclic elastic-plastic deformation of roller levelling and straightening processes, steel research international (2009).

[7] M. Grüber, L. Kümmel, G. Hirt, Control of residual stresses by roller leveling with regard to process stability and one-sided surface removal, Journal of Materials Processing Technology 280 (2020) 116600. https://doi.org/10.1016/j.jmatprotec.2020.116600

[8] DIN EN ISO 6892-1:2020-06, Metallic materials - Tensile testing - Part 1: Method of test at room temperature (ISO 6892-1:2019); German version EN ISO 6892-1:2019, Beuth Verlag GmbH, Berlin.

[9] DIN EN 15305:2009-01, Non-destructive testing - Test method for residual stress analysis by X-ray diffraction; German version EN 15305:2008, Beuth Verlag GmbH, Berlin.

[10] F. Dahms, W. Homberg, Investigations and improvements in 3D-DIC optical residual stress analysis—A new temperature compensation method, in: G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, Y. Yoshida (Eds.), FORMING THE FUTURE: Proceedings of the 13th international conference on the Technology of Plasticity, Springer Cham., 2021, pp. 2249–2259.
https://doi.org/10.1007/978-3-030-75381-8_189
[5] I. Khromov, R. Kawalla, Simulation of a steel wire straightening taking into account nonlinear hardening of material, Eng. Technol. Appl. Sci. Res. 2 (2012) 320-324.
https://doi.org/10.48084/etasr.275

[6] W. Guericke, Material model describing cyclic elastic-plastic deformation of roller levelling and straightening processes, steel research international (2009).

[7] M. Grüber, L. Kümmel, G. Hirt, Control of residual stresses by roller leveling with regard to process stability and one-sided surface removal, Journal of Materials Processing Technology 280 (2020) 116600. https://doi.org/10.1016/j.jmatprotec.2020.116600

[8] DIN EN ISO 6892-1:2020-06, Metallic materials - Tensile testing - Part 1: Method of test at room temperature (ISO 6892-1:2019); German version EN ISO 6892-1:2019, Beuth Verlag GmbH, Berlin.

[9] DIN EN 15305:2009-01, Non-destructive testing - Test method for residual stress analysis by X-ray diffraction; German version EN 15305:2008, Beuth Verlag GmbH, Berlin.

[10] F. Dahms, W. Homberg, Investigations and improvements in 3D-DIC optical residual stress analysis—A new temperature compensation method, in: G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, Y. Yoshida (Eds.), FORMING THE FUTURE: Proceedings of the 13th international conference on the Technology of Plasticity, Springer Cham., 2021, pp. 2249–2259.
https://doi.org/10.1007/978-3-030-75381-8_189
# Sensor integration for process control in deep drawing

JUNG Robert Oliver¹, a*, SEPER Christoph², b, JURICEK Christian², c and BLEICHER Friedrich¹, d

¹Institute for Production Engineering and Photonic Technologies, TU Wien, Franz Grill Straße 4, Object OA, Vienna 1030, Austria

²MAGNA Cosma, Puchberger Straße 267, Weikersdorf 2722, Austria

a>jung@ift.at, bchristoph.seper@magna.com, cchristian.juricek@magna.com, dbleicher@ift.at

**Keywords:** Sheet Metal Forming, Deep Drawing, Control, Sensor Integration

**Abstract.** In the context of increasing resource efficiency and profitability, deep drawing can be improved using a digital twin and closed-loop process control. Cyber-physical production systems (CPPS) enable data capture and analysis for an autonomous optimization of the manufacturing process. In this work reference sensor signals are used to control the force and material flow with hydraulic actuators between the blank holder and the die. A novel model-based optimization method is proposed to determine the best sensor location, allowing for standardized evaluation and reduced integration time. FE simulations and forming trials are conducted for validation. The findings indicate time and resource savings through an efficient sensor implementation in deep drawing tools for process control.

**Introduction**

In the European Union (EU), 2.4 million jobs are directly dependent and approximately 12.9 million jobs are overall connected to the automotive industry [1]. In 2021, the EU invested a total of 59.1 billion euros in research and development (R&D) in the automotive sector, which corresponds to 31 % of their overall R&D expenditures [1]. The revenue generated from the automotive industry for the EU amounted to 392.2 billion euros in 2022 [1], which highlights the significance of this fiercely competitive industry sector. Approximately two-thirds of a vehicle body is manufactured using forming technology with deep drawing being the primary method employed. However, the processing window narrows as a result of lightweight construction and the demand for complex geometries. To widen the processing window as well as to enhance resource efficiency and cost-effectiveness, CPPS are required. A categorization of CPPS for deep drawing processes can be realized in different ways. One approach divides them based on the manufacturing technology, namely tandem press setups and single-press setups with transfer and progressive dies [2]. Another approach classifies them based on the computation time of the algorithm. The model based analysis can happen *after*, *during*, or - at the most advanced stage - *before* the stroke. In [3] the algorithm predicts the optimal process parameters for the next stroke *after* a measured stroke. Investigations on control of the material flow in real-time *during* the measured stroke can be found in [4]. A prediction of the optimal process parameters *before* the forming for each blank individually based on the mechanical properties of the incoming material is presented in [5]. For regulating the material flow during the stroke, hydraulic actuators between the blank holder and the die can be used in order to control the material inflow in the flange area based on the stresses in the punch, die and blank holder. Previous investigations can be found in [2], and a general overview of closed-loop control of product properties in metal forming in [6]. Further, [7] provides a comprehensive overview of smart tooling for metal forming, which includes a dedicated chapter on smart tooling with embedded sensors. A crucial aspect for a successful process control during the stroke is to obtain high-quality information about the current

<figure><img src="image_1356.png" /></figure>
# Sensor integration for process control in deep drawing

JUNG Robert Oliver¹, a*, SEPER Christoph², b, JURICEK Christian², c and BLEICHER Friedrich¹, d

¹Institute for Production Engineering and Photonic Technologies, TU Wien, Franz Grill Straße 4, Object OA, Vienna 1030, Austria

²MAGNA Cosma, Puchberger Straße 267, Weikersdorf 2722, Austria

a>jung@ift.at, bchristoph.seper@magna.com, cchristian.juricek@magna.com, dbleicher@ift.at

**Keywords:** Sheet Metal Forming, Deep Drawing, Control, Sensor Integration

**Abstract.** In the context of increasing resource efficiency and profitability, deep drawing can be improved using a digital twin and closed-loop process control. Cyber-physical production systems (CPPS) enable data capture and analysis for an autonomous optimization of the manufacturing process. In this work reference sensor signals are used to control the force and material flow with hydraulic actuators between the blank holder and the die. A novel model-based optimization method is proposed to determine the best sensor location, allowing for standardized evaluation and reduced integration time. FE simulations and forming trials are conducted for validation. The findings indicate time and resource savings through an efficient sensor implementation in deep drawing tools for process control.

**Introduction**

In the European Union (EU), 2.4 million jobs are directly dependent and approximately 12.9 million jobs are overall connected to the automotive industry [1]. In 2021, the EU invested a total of 59.1 billion euros in research and development (R&D) in the automotive sector, which corresponds to 31 % of their overall R&D expenditures [1]. The revenue generated from the automotive industry for the EU amounted to 392.2 billion euros in 2022 [1], which highlights the significance of this fiercely competitive industry sector. Approximately two-thirds of a vehicle body is manufactured using forming technology with deep drawing being the primary method employed. However, the processing window narrows as a result of lightweight construction and the demand for complex geometries. To widen the processing window as well as to enhance resource efficiency and cost-effectiveness, CPPS are required. A categorization of CPPS for deep drawing processes can be realized in different ways. One approach divides them based on the manufacturing technology, namely tandem press setups and single-press setups with transfer and progressive dies [2]. Another approach classifies them based on the computation time of the algorithm. The model based analysis can happen *after*, *during*, or - at the most advanced stage - *before* the stroke. In [3] the algorithm predicts the optimal process parameters for the next stroke *after* a measured stroke. Investigations on control of the material flow in real-time *during* the measured stroke can be found in [4]. A prediction of the optimal process parameters *before* the forming for each blank individually based on the mechanical properties of the incoming material is presented in [5]. For regulating the material flow during the stroke, hydraulic actuators between the blank holder and the die can be used in order to control the material inflow in the flange area based on the stresses in the punch, die and blank holder. Previous investigations can be found in [2], and a general overview of closed-loop control of product properties in metal forming in [6]. Further, [7] provides a comprehensive overview of smart tooling for metal forming, which includes a dedicated chapter on smart tooling with embedded sensors. A crucial aspect for a successful process control during the stroke is to obtain high-quality information about the current

<figure><img src="image_1360.png" /></figure>
process state, driven by the positioning and type of the sensor. To avoid an iterative experimental evaluation based selection of the location in the tool, a defined methodological approach is proposed in this work.

## Methodological approach

The methodological approach to optimize the sensor integration in deep drawing tools for process control is illustrated in Fig. 1. The process starts with the identification of a tool. Next, a finite element (FE) simulation is performed for both a good part and a defective part with splits or wrinkles to evaluate the differences in the simulation outcomes.

<figure><img src="image_1357.png" /><figcaption>Fig. 1 - Methodological approach to optimize the sensor integration in deep drawing tools for process control during the stroke</figcaption></figure>

Subsequently, the differences in the simulation results provide initial indications at which positions in the tool measurements could be performed. Furthermore, the simulation results help to select the sensor types based on the specific measurement variables. In particular, the implementation of a flange inflow sensor at the location of maximum inflow difference between good and defective parts as well as the implementation of force sensors at the locations of maximum difference in the stress distribution in the tool have been chosen as being appropriate for the application of the respective use case. However, other types of sensors with different physical measurement principles are also considered in the presented approach. Afterwards, the simulation of the good and defective parts needs to be performed again, as the sensor implementations, including milled pockets for assembly and cable routing, influence the stiffness of the tool components. This results in simulated sensor signals, which allows for the calculation of the eligibility η. In this work η represents the suitability of a sensor in a deep drawing tool for control during the stroke, allowing for the classification of process reliability as a Fig. of merit. The procedure for the calculation is explained in a later section. After interpreting the results, a decision is made on whether this process needs to be iteratively repeated or not. The sensor with the highest value for η is physically implemented in the tool, and practical forming experiments are conducted. Ideally, the experimental and simulated results, such as flange draw-in and sheet thinning, coincide, thereby validating the simulation. In this study, the new methodological approach is validated alongside the simulation by implementing and testing the selected sensor in an industrial relevant tool setup.

## FE Simulation

Nowadays, FE simulation is indispensable in the design of forming processes. It is also an essential component for the sensor integration presented in this study, as it allows for the simulation of sensor curves, which are subsequently used as input for the calculation of η. LS-DYNA is used in this work and the blank is modeled using shell elements (fully integrated shell DynaType 16 with 7 integration points through the thickness). The element edge length in the sheet is constant and measures 1.5 mm. The tool is modeled using rigid body surfaces with locally refined meshing at
process state, driven by the positioning and type of the sensor. To avoid an iterative experimental evaluation based selection of the location in the tool, a defined methodological approach is proposed in this work.

## Methodological approach

The methodological approach to optimize the sensor integration in deep drawing tools for process control is illustrated in Fig. 1. The process starts with the identification of a tool. Next, a finite element (FE) simulation is performed for both a good part and a defective part with splits or wrinkles to evaluate the differences in the simulation outcomes.

<figure><img src="image_1361.png" /><figcaption>Fig. 1 - Methodological approach to optimize the sensor integration in deep drawing tools for process control during the stroke</figcaption></figure>

Subsequently, the differences in the simulation results provide initial indications at which positions in the tool measurements could be performed. Furthermore, the simulation results help to select the sensor types based on the specific measurement variables. In particular, the implementation of a flange inflow sensor at the location of maximum inflow difference between good and defective parts as well as the implementation of force sensors at the locations of maximum difference in the stress distribution in the tool have been chosen as being appropriate for the application of the respective use case. However, other types of sensors with different physical measurement principles are also considered in the presented approach. Afterwards, the simulation of the good and defective parts needs to be performed again, as the sensor implementations, including milled pockets for assembly and cable routing, influence the stiffness of the tool components. This results in simulated sensor signals, which allows for the calculation of the eligibility η. In this work η represents the suitability of a sensor in a deep drawing tool for control during the stroke, allowing for the classification of process reliability as a Fig. of merit. The procedure for the calculation is explained in a later section. After interpreting the results, a decision is made on whether this process needs to be iteratively repeated or not. The sensor with the highest value for η is physically implemented in the tool, and practical forming experiments are conducted. Ideally, the experimental and simulated results, such as flange draw-in and sheet thinning, coincide, thereby validating the simulation. In this study, the new methodological approach is validated alongside the simulation by implementing and testing the selected sensor in an industrial relevant tool setup.

## FE Simulation

Nowadays, FE simulation is indispensable in the design of forming processes. It is also an essential component for the sensor integration presented in this study, as it allows for the simulation of sensor curves, which are subsequently used as input for the calculation of η. LS-DYNA is used in this work and the blank is modeled using shell elements (fully integrated shell DynaType 16 with 7 integration points through the thickness). The element edge length in the sheet is constant and measures 1.5 mm. The tool is modeled using rigid body surfaces with locally refined meshing at
the radii. Elastic volume elements are used to model the stresses in the tool at the sensor positions. The volume of tool inserts is represented by SOLID TET linear with an element edge length of approximately 3 mm and locally refined radii. Coulomb friction model with a constant friction factor of $\mu = 0.1$ is used [8]. Dynamic friction with pressure and velocity dependency was also tested but proved to be ineffective. The Barlat89 material model (LS-DYNA Mat36 - *MAT_3-PARAMETER_BARLAT) is used to model sheet materials with anisotropic properties under plane stress conditions [9]. The used material 1.0952 [10] is cold rolled, has the chemical composition shown in Table 1 and is coated with 50 g/m² of zinc at each side.

<table><caption>Table 1 – Chemical composition of 1.0952 in mass-%</caption><thead><tr><th>C</th><th>Si</th><th>Mn</th><th>P</th><th>S</th><th>Ti</th><th>V</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Mo</th></tr></thead><tbody><tr><td>0.120</td><td>0.500</td><td>0.600</td><td>0.100</td><td>0.045</td><td>0.300</td><td>0.004</td><td>0.019</td><td>0.137</td><td>0.009</td><td>0.002</td></tr></tbody></table>

Tensile tests are conducted at 0°, 45°, and 90° to the rolling direction for calibration [11]. The extrapolation of the flow curve is performed using a combination of Swift [12] and Hockett-Sherby [13]. Sheet failure is represented using the Müschenborn-Sonne Forming Limit Diagram (MSFLD) [14].

In the simulation, a decreasing blank holder force (BHF) profile represents a good part, while a constant BHF of 250 kN represents a defective part. After comparing the simulation results, a defect in the form of critical sheet thinning leading to a split is detected on the front side with a constant BHF of 250 kN, see Fig. 2.

<figure><img src="image_1358.png" /><figcaption>Fig. 2 - Sensor locations and blank thickness in mm of a 1) FE simulated and 2) formed part with A) decreasing BHF profile and B) BHF constant 250 kN</figcaption></figure>

To indirectly measure this split on the flange, a mechanical inflow sensor is used. This sensor consists of a metal blade that can slide through a groove in the blank holder and is permanently pressed against the sheet edge by a pneumatic cylinder. To identify a suitable position for a piezo force sensor, the stress distributions in the tool are analyzed by subtracting the simulation results of the good part from the defective part. The upper punch radius, as marked in Fig. 2, is identified as a potential suitable position for the piezo force sensor. The component geometry is based on a wheelhouse. Recesses in the tool are implemented in the FE simulation to accommodate the installation and cable routing of the two sensors. The new setup is then simulated again.

## Eligibility η

In order to explain the general procedure for calculating $\eta$, an example is provided for the two selected sensors. The eligibility is defined as the factor describing the necessary qualities or satisfying necessary conditions [15]. In this work, the eligibility $\eta$ is a defined feature that represents the suitability of a sensor in a deep drawing tool for control during the stroke. It considers cause and effect and is a criterion that allows the classification of process reliability as
the radii. Elastic volume elements are used to model the stresses in the tool at the sensor positions. The volume of tool inserts is represented by SOLID TET linear with an element edge length of approximately 3 mm and locally refined radii. Coulomb friction model with a constant friction factor of $\mu = 0.1$ is used [8]. Dynamic friction with pressure and velocity dependency was also tested but proved to be ineffective. The Barlat89 material model (LS-DYNA Mat36 - *MAT_3-PARAMETER_BARLAT) is used to model sheet materials with anisotropic properties under plane stress conditions [9]. The used material 1.0952 [10] is cold rolled, has the chemical composition shown in Table 1 and is coated with 50 g/m² of zinc at each side.

<table><caption>Table 1 – Chemical composition of 1.0952 in mass-%</caption><thead><tr><th>C</th><th>Si</th><th>Mn</th><th>P</th><th>S</th><th>Ti</th><th>V</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Mo</th></tr></thead><tbody><tr><td>0.120</td><td>0.500</td><td>0.600</td><td>0.100</td><td>0.045</td><td>0.300</td><td>0.004</td><td>0.019</td><td>0.137</td><td>0.009</td><td>0.002</td></tr></tbody></table>

Tensile tests are conducted at 0°, 45°, and 90° to the rolling direction for calibration [11]. The extrapolation of the flow curve is performed using a combination of Swift [12] and Hockett-Sherby [13]. Sheet failure is represented using the Müschenborn-Sonne Forming Limit Diagram (MSFLD) [14].

In the simulation, a decreasing blank holder force (BHF) profile represents a good part, while a constant BHF of 250 kN represents a defective part. After comparing the simulation results, a defect in the form of critical sheet thinning leading to a split is detected on the front side with a constant BHF of 250 kN, see Fig. 2.

<figure><img src="image_1362.png" /><figcaption>Fig. 2 - Sensor locations and blank thickness in mm of a 1) FE simulated and 2) formed part with A) decreasing BHF profile and B) BHF constant 250 kN</figcaption></figure>

To indirectly measure this split on the flange, a mechanical inflow sensor is used. This sensor consists of a metal blade that can slide through a groove in the blank holder and is permanently pressed against the sheet edge by a pneumatic cylinder. To identify a suitable position for a piezo force sensor, the stress distributions in the tool are analyzed by subtracting the simulation results of the good part from the defective part. The upper punch radius, as marked in Fig. 2, is identified as a potential suitable position for the piezo force sensor. The component geometry is based on a wheelhouse. Recesses in the tool are implemented in the FE simulation to accommodate the installation and cable routing of the two sensors. The new setup is then simulated again.

## Eligibility η

In order to explain the general procedure for calculating $\eta$, an example is provided for the two selected sensors. The eligibility is defined as the factor describing the necessary qualities or satisfying necessary conditions [15]. In this work, the eligibility $\eta$ is a defined feature that represents the suitability of a sensor in a deep drawing tool for control during the stroke. It considers cause and effect and is a criterion that allows the classification of process reliability as
a Fig. of merit. The values for the η-parameter range from 0 to 10. However, it is not possible to generalize up to which order of magnitude η can be identified as good or bad. This is because the component geometry, drawing depth, and material strongly influence the calculation. A comparison of η between different tools is therefore not meaningful. Despite of these basic conditions, an absolute comparison of sensors and their positions within a specific deep drawing tool is possible. In the calculation of η, three variables are considered, as represented in Eq. 1.

$$ \eta = \frac{5}{2} (2T + D + F) \qquad (1) $$

The time parameter T is doubly weighted compared to the distance parameter D and the failure condition parameter F as it is the most crucial. The multiplication of the term by 2.5 scales the value range to $W_{\eta} = [0; 10]$. Eq. 2 illustrates how the time parameter is derived. T describes how early a defect in the sensor curve becomes apparent. Specifically, this parameter represents, when the absolute sensor value curve of the defective component deviates the first time from that of the good component by more than one eighth of magnitude. In this case, the sensor curve of the good component is considered 100 %. An early occurrence of this deviation is preferred as it provides more time to adjust the process by adapting the BHF.

$$ T = \frac{s_{12.5}}{s_f} \qquad (2) $$

$s_f$ represents the forming stroke from starting point of forming until end of stroke. For instance, if the forming occurs between 280 and 400 mm, with 400 mm total stroke corresponding to Bottom Dead Center (BDC), then $s_f$ would be 120 mm. $s_{12.5}$ represents the displacement at which the deviation between the curves exceeds 12.5 % for the first time. As a result, T approaches 1 when the deviation occurs immediately. Conversely, when the deviation happens closer to BDC, T approaches 0. In this work, the sensors signals are analyzed with respect to the ram slide and thus becomes independent from cycle time. When plotting the sensor signal against time, the x-axis varies depending on the strokes per minute (SPM). The actual critical reaction time required to prevent defects through countermeasures depends on factors such as sensor sampling rate, processor cycle time, and program execution time. Experimental forming trials are performed to indicate whether the control system as a whole will operate effectively. The calculation of the distance parameter D is explained in Eq. 3 and 4. Essentially, the sensor signal of the defective component $y_b$ is divided by the sensor signal of the good component $y_g$, both measured at one quarter of $s_f$ before BDC.

$$ D = \left| \frac{y_b}{y_g} - 1 \right|, \quad \text{if } |y_b| < |2y_g| \qquad (3) $$

$$ D = 1, \quad \text{if } |y_b| \geq |2y_g| \qquad (4) $$

If $y_b$ is significantly smaller than $y_g$, the fraction term approaches 0, resulting in the entire term approaching 1. To ensure that this equation works for both, positive and negative sensor signals, e.g., positive flange inflow or negative stress (compression), the absolute value of D is taken. If $y_b$ is significantly larger than $y_g$, the term theoretically converges to infinity and would exceed by far T and F. This typically does not occur in flange draw-in but can happen if a part splits and the compressive stress in the tool abruptly drops to 0. Therefore, Eq. 4 is used when the absolute value of $y_b$ is twice as large as the absolute value of $y_g$, which limits the value range of D to $W_D = [0; 1]$. The failure condition parameter F is selected based on the severity of the defect. This is
a Fig. of merit. The values for the η-parameter range from 0 to 10. However, it is not possible to generalize up to which order of magnitude η can be identified as good or bad. This is because the component geometry, drawing depth, and material strongly influence the calculation. A comparison of η between different tools is therefore not meaningful. Despite of these basic conditions, an absolute comparison of sensors and their positions within a specific deep drawing tool is possible. In the calculation of η, three variables are considered, as represented in Eq. 1.

$$ \eta = \frac{5}{2} (2T + D + F) \qquad (1) $$

The time parameter T is doubly weighted compared to the distance parameter D and the failure condition parameter F as it is the most crucial. The multiplication of the term by 2.5 scales the value range to $W_{\eta} = [0; 10]$. Eq. 2 illustrates how the time parameter is derived. T describes how early a defect in the sensor curve becomes apparent. Specifically, this parameter represents, when the absolute sensor value curve of the defective component deviates the first time from that of the good component by more than one eighth of magnitude. In this case, the sensor curve of the good component is considered 100 %. An early occurrence of this deviation is preferred as it provides more time to adjust the process by adapting the BHF.

$$ T = \frac{s_{12.5}}{s_f} \qquad (2) $$

$s_f$ represents the forming stroke from starting point of forming until end of stroke. For instance, if the forming occurs between 280 and 400 mm, with 400 mm total stroke corresponding to Bottom Dead Center (BDC), then $s_f$ would be 120 mm. $s_{12.5}$ represents the displacement at which the deviation between the curves exceeds 12.5 % for the first time. As a result, T approaches 1 when the deviation occurs immediately. Conversely, when the deviation happens closer to BDC, T approaches 0. In this work, the sensors signals are analyzed with respect to the ram slide and thus becomes independent from cycle time. When plotting the sensor signal against time, the x-axis varies depending on the strokes per minute (SPM). The actual critical reaction time required to prevent defects through countermeasures depends on factors such as sensor sampling rate, processor cycle time, and program execution time. Experimental forming trials are performed to indicate whether the control system as a whole will operate effectively. The calculation of the distance parameter D is explained in Eq. 3 and 4. Essentially, the sensor signal of the defective component $y_b$ is divided by the sensor signal of the good component $y_g$, both measured at one quarter of $s_f$ before BDC.

$$ D = \left| \frac{y_b}{y_g} - 1 \right|, \quad \text{if } |y_b| < |2y_g| \qquad (3) $$

$$ D = 1, \quad \text{if } |y_b| \geq |2y_g| \qquad (4) $$

If $y_b$ is significantly smaller than $y_g$, the fraction term approaches 0, resulting in the entire term approaching 1. To ensure that this equation works for both, positive and negative sensor signals, e.g., positive flange inflow or negative stress (compression), the absolute value of D is taken. If $y_b$ is significantly larger than $y_g$, the term theoretically converges to infinity and would exceed by far T and F. This typically does not occur in flange draw-in but can happen if a part splits and the compressive stress in the tool abruptly drops to 0. Therefore, Eq. 4 is used when the absolute value of $y_b$ is twice as large as the absolute value of $y_g$, which limits the value range of D to $W_D = [0; 1]$. The failure condition parameter F is selected based on the severity of the defect. This is
necessary, because an early significant difference between two sensor curves can result from large cracks or wrinkles. The challenge lies in obtaining a significant difference in the sensor curves for the onset of necking or wrinkling. Fig. 3 shows an example subdivision of the defect appearance considering cracks.

<figure><img src="image_1359.png" /><figcaption>Fig. 3 - Classification of component quality with regard to crack formation for the failure condition parameter F</figcaption></figure>

In the following, an exemplary determination of η for the simulated intake sensor at the flange and the simulated piezo force sensor in the punch is presented. The quality condition of the component in the final step of the FE simulation is compared with the classification shown in Fig. 3, and thus F = 0.2 is selected. The variables $y_g$ and $y_b$ are measured a quarter of $s_f$ before BDC. Since $s_f$ is 120 mm, $y_g$ and $y_b$ are measured 30 mm before BDC. The results are based solely on the FE simulation and η is calculated for the intake and piezo force sensor, as shown in Table 2.

<table><caption>Table 2 - Results of η for intake and piezo force sensor</caption><thead><tr><th></th><th>s<sub>12.5</sub></th><th>y<sub>g</sub></th><th>y<sub>g</sub></th><th>T</th><th>D</th><th>F</th><th>η</th></tr></thead><tbody><tr><td>Intake sensor</td><td>21.55 mm</td><td>30.96 mm</td><td>28.85 mm</td><td>0.18</td><td>0.07</td><td>0.20</td><td>1.57</td></tr><tr><td>Piezo force sensor</td><td>47.96 mm</td><td>-866.55 pC</td><td>-993.68 pC</td><td>0.40</td><td>0.15</td><td>0.20</td><td>2.87</td></tr></tbody></table>

The two sensor signals are plotted over the ram slide in Fig. 4 and Fig. 5. Additionally, the calculated parameters and the crack initiation of the defective part are marked. Since η is higher for the piezo force sensor than for the intake sensor, the piezo force sensor is implemented for control purpose.
necessary, because an early significant difference between two sensor curves can result from large cracks or wrinkles. The challenge lies in obtaining a significant difference in the sensor curves for the onset of necking or wrinkling. Fig. 3 shows an example subdivision of the defect appearance considering cracks.

<figure><img src="image_1363.png" /><figcaption>Fig. 3 - Classification of component quality with regard to crack formation for the failure condition parameter F</figcaption></figure>

In the following, an exemplary determination of η for the simulated intake sensor at the flange and the simulated piezo force sensor in the punch is presented. The quality condition of the component in the final step of the FE simulation is compared with the classification shown in Fig. 3, and thus F = 0.2 is selected. The variables $y_g$ and $y_b$ are measured a quarter of $s_f$ before BDC. Since $s_f$ is 120 mm, $y_g$ and $y_b$ are measured 30 mm before BDC. The results are based solely on the FE simulation and η is calculated for the intake and piezo force sensor, as shown in Table 2.

<table><caption>Table 2 - Results of η for intake and piezo force sensor</caption><thead><tr><th></th><th>s<sub>12.5</sub></th><th>y<sub>g</sub></th><th>y<sub>g</sub></th><th>T</th><th>D</th><th>F</th><th>η</th></tr></thead><tbody><tr><td>Intake sensor</td><td>21.55 mm</td><td>30.96 mm</td><td>28.85 mm</td><td>0.18</td><td>0.07</td><td>0.20</td><td>1.57</td></tr><tr><td>Piezo force sensor</td><td>47.96 mm</td><td>-866.55 pC</td><td>-993.68 pC</td><td>0.40</td><td>0.15</td><td>0.20</td><td>2.87</td></tr></tbody></table>

The two sensor signals are plotted over the ram slide in Fig. 4 and Fig. 5. Additionally, the calculated parameters and the crack initiation of the defective part are marked. Since η is higher for the piezo force sensor than for the intake sensor, the piezo force sensor is implemented for control purpose.
<figure><img src="image_1360.png" /><figcaption>Fig. 4 - Material inflow signals based on FE simulation and variables for determination of eligibility η</figcaption></figure>

<figure><img src="image_1361.png" /><figcaption>Fig. 5 – Piezo force sensor signals based on FE simulation and variables for determination of eligibility η</figcaption></figure>

Experimental forming trials with quality control during the stroke

In Fig. 6, simulated (blue and purple) and experimentally determined signals (red, green and black) of the piezo force sensor are plotted in pC over the ram slide in mm. The magnitude of the signal decreases as the pressure-induced stresses in the punch increase. Comparing the purple curve, representing a simulated split, with the three red curves, representing experimental splits, it reveals
<figure><img src="image_1364.png" /><figcaption>Fig. 4 - Material inflow signals based on FE simulation and variables for determination of eligibility η</figcaption></figure>

<figure><img src="image_1365.png" /><figcaption>Fig. 5 – Piezo force sensor signals based on FE simulation and variables for determination of eligibility η</figcaption></figure>

Experimental forming trials with quality control during the stroke

In Fig. 6, simulated (blue and purple) and experimentally determined signals (red, green and black) of the piezo force sensor are plotted in pC over the ram slide in mm. The magnitude of the signal decreases as the pressure-induced stresses in the punch increase. Comparing the purple curve, representing a simulated split, with the three red curves, representing experimental splits, it reveals
that the simulation closely matches reality. However, in the simulation, the tension in the sensor element abruptly drops to zero at the onset of cracking, which is not observed in the experimental tests. Here, the stress distribution in the tool appears to be more homogeneous. By adjusting the failure model of the FE simulation, the real behavior of the component could be captured even more accurately. The blue curves, representing the simulated good part, and green curves, representing the experimental good parts, also closely match, until a tension drop can be identified in the simulated good parts at approximately 30 mm before BDC. It should be noted that the FE simulation is only an approximation of the real deep drawing process, as many simplified assumptions are made, such as the idealized geometry of the tool and blank, constant friction, and excluded inaccuracies in the determined material properties. Furthermore, the portion of the simulated sensor curves that deviates from the experimentally determined sensor curves does not affect the calculation of η, as all relevant values are extracted only from the matching region before the simulated sensor curves exhibit a sudden tension drop.

<figure><img src="image_1362.png" /><figcaption>Fig. 6 – Comparison of piezo force sensor signals: FE simulation, experimental forming trials without control, and with control</figcaption></figure>

The black curve represents the sensor signal from the experiment where the BHF is set to
defective part settings (250 kN constant causing splits), but a control with the piezo force sensor
and hydraulic actuators between the blank holder and die is active. Up to 30 mm before BDC, the
sensor signal aligns with the green and good part curves. However, as the pressure stresses near
the sensor curves of the defective parts at around 5 mm before BDC, a deviation between the good
parts with active control and 250 kN constant BHF and the good parts without active control but a
decreasing BHF profile becomes evident. The only distinguishing factor between the parts
represented by the red sensor curves and those represented by the black curves is the presence of
active control. The red parts exhibit a significant split across the front and are considered scrap,
that the simulation closely matches reality. However, in the simulation, the tension in the sensor element abruptly drops to zero at the onset of cracking, which is not observed in the experimental tests. Here, the stress distribution in the tool appears to be more homogeneous. By adjusting the failure model of the FE simulation, the real behavior of the component could be captured even more accurately. The blue curves, representing the simulated good part, and green curves, representing the experimental good parts, also closely match, until a tension drop can be identified in the simulated good parts at approximately 30 mm before BDC. It should be noted that the FE simulation is only an approximation of the real deep drawing process, as many simplified assumptions are made, such as the idealized geometry of the tool and blank, constant friction, and excluded inaccuracies in the determined material properties. Furthermore, the portion of the simulated sensor curves that deviates from the experimentally determined sensor curves does not affect the calculation of η, as all relevant values are extracted only from the matching region before the simulated sensor curves exhibit a sudden tension drop.

<figure><img src="image_1366.png" /><figcaption>Fig. 6 – Comparison of piezo force sensor signals: FE simulation, experimental forming trials without control, and with control</figcaption></figure>

The black curve represents the sensor signal from the experiment where the BHF is set to
defective part settings (250 kN constant causing splits), but a control with the piezo force sensor
and hydraulic actuators between the blank holder and die is active. Up to 30 mm before BDC, the
sensor signal aligns with the green and good part curves. However, as the pressure stresses near
the sensor curves of the defective parts at around 5 mm before BDC, a deviation between the good
parts with active control and 250 kN constant BHF and the good parts without active control but a
decreasing BHF profile becomes evident. The only distinguishing factor between the parts
represented by the red sensor curves and those represented by the black curves is the presence of
active control. The red parts exhibit a significant split across the front and are considered scrap,
whereas the black parts are of good quality. Two PID controllers are used. The higher-level control loop regulates the current sensor data to the reference sensor data of a good part by adjusting the pressure in the hydraulic actuators between the blank holder and the die. The second control loop regulates the actual pressure of the actuators to the desired pressure. The η-value for the piezo force sensor is higher than for the draw-in sensor and the control with the piezo force sensor is successfully implemented. The additional use of the draw-in sensor signal offers an alternative solution of single sensor signal implementation. In general, it is recommended to consider more than one single sensor source by the sensor fusion approach. The presented model is basically aimed at identifying the optimal sensor position.

## Summary and future directions

This new methodological approach allows for improving sensor integration for the control of deep drawing processes during the stroke. It is achieved by a combination of FE simulation and assessment of results by calculation of sensor eligibility η. Initially, the differences between good parts and defective parts are identified using FE simulation. The required types of sensors are derived from this analysis. In the experimental set-up and by the selected testing specimen used in this study, this resulted in the selection of a mechanical inflow sensor at the front end of the component and a piezoelectric force sensor in the punch. The area depicted in Fig. 3 is referred to as the front. Subsequently, the sensors, including all necessary mountings and cable routing, are implemented in the FE simulation. The sensor eligibility η, which is defined to consider cause and effect issues, is calculated for the simulated sensor curves. This metric takes into account, how early and how sensitively the sensor detects the occurrence of a component defect, considering both, the sensor's response magnitude and the severity of the defect. Finally, the sensor with the highest η value is implemented in the process control, resulting in successful crack avoidance. A close agreement between the simulated sensor curves and the experimental results is a prerequisite. This approach not only accelerates sensor integration by the use of process modelling but also provides the opportunity to select sensor positions according to quantitative measures. However, the comparison between η values is only valid within one tool. Different tools can significantly influence the calculation of η due to variations in friction, drawing depths, geometries, and materials. It is possible that a defect may occur late in the stroke, close to the bottom dead center, without any prior indication through changes in, for example, flange inflow speed or tool stresses. In such cases, implementing control during the stroke may be challenging, and the proposed approach may have limitations.

The formed components of a vehicle body should be clustered, and a unified table for the failure condition parameter *F* should be created for each cluster, minimizing the user's discretion. The significance of the presented Fig. of merit should be ensured through additional deep drawn components. Furthermore, in the future, attempts should be made to train artificial intelligence to correlate the sensor signals and η by visually detectable effects on the component. Through this approach, a continuous automatic output of *F* and an increased process understanding would be conceivable. Integrating the assessed model directly into the FE simulation software would be desirable to enhance usability and eliminate the need for switching between different software tools.

## Acknowledgment

The authors thank the MAGNA Cosma R&D Team and the Institute of Production Engineering and Photonic Technologies (IFT) of TU Wien for their support in terms of scientific and technical expertise. Special appreciation to MAGNA Cosma for funding of this research project.
whereas the black parts are of good quality. Two PID controllers are used. The higher-level control loop regulates the current sensor data to the reference sensor data of a good part by adjusting the pressure in the hydraulic actuators between the blank holder and the die. The second control loop regulates the actual pressure of the actuators to the desired pressure. The $\eta$-value for the piezo force sensor is higher than for the draw-in sensor and the control with the piezo force sensor is successfully implemented. The additional use of the draw-in sensor signal offers an alternative solution of single sensor signal implementation. In general, it is recommended to consider more than one single sensor source by the sensor fusion approach. The presented model is basically aimed at identifying the optimal sensor position.

## Summary and future directions

This new methodological approach allows for improving sensor integration for the control of deep drawing processes during the stroke. It is achieved by a combination of FE simulation and assessment of results by calculation of sensor eligibility $\eta$. Initially, the differences between good parts and defective parts are identified using FE simulation. The required types of sensors are derived from this analysis. In the experimental set-up and by the selected testing specimen used in this study, this resulted in the selection of a mechanical inflow sensor at the front end of the component and a piezoelectric force sensor in the punch. The area depicted in Fig. 3 is referred to as the front. Subsequently, the sensors, including all necessary mountings and cable routing, are implemented in the FE simulation. The sensor eligibility $\eta$, which is defined to consider cause and effect issues, is calculated for the simulated sensor curves. This metric takes into account, how early and how sensitively the sensor detects the occurrence of a component defect, considering both, the sensor's response magnitude and the severity of the defect. Finally, the sensor with the highest $\eta$ value is implemented in the process control, resulting in successful crack avoidance. A close agreement between the simulated sensor curves and the experimental results is a prerequisite. This approach not only accelerates sensor integration by the use of process modelling but also provides the opportunity to select sensor positions according to quantitative measures. However, the comparison between $\eta$ values is only valid within one tool. Different tools can significantly influence the calculation of $\eta$ due to variations in friction, drawing depths, geometries, and materials. It is possible that a defect may occur late in the stroke, close to the bottom dead center, without any prior indication through changes in, for example, flange inflow speed or tool stresses. In such cases, implementing control during the stroke may be challenging, and the proposed approach may have limitations.

The formed components of a vehicle body should be clustered, and a unified table for the failure condition parameter $F$ should be created for each cluster, minimizing the user's discretion. The significance of the presented Fig. of merit should be ensured through additional deep drawn components. Furthermore, in the future, attempts should be made to train artificial intelligence to correlate the sensor signals and $\eta$ by visually detectable effects on the component. Through this approach, a continuous automatic output of $F$ and an increased process understanding would be conceivable. Integrating the assessed model directly into the FE simulation software would be desirable to enhance usability and eliminate the need for switching between different software tools.

## Acknowledgment

The authors thank the MAGNA Cosma R&D Team and the Institute of Production Engineering and Photonic Technologies (IFT) of TU Wien for their support in terms of scientific and technical expertise. Special appreciation to MAGNA Cosma for funding of this research project.
## References

[1] S. de Vries, The Automobile Industry - Pocket Guide 2023/2024, ACEA - European Automobile Manufacturers' Association (2023) 5-9.

[2] R.O. Jung, F. Bleicher, S. Krall, C. Juricek, R. Lottes, K. Steinschütz, T. Reininger, Cyber Physical Production Systems for Deep Drawing, J. Manuf. Sci. Eng. 145 (2023) 101006. https://doi.org/10.1115/1.4062903

[3] S. Thaddaeus, P. Henri, Adjustable Balancing Block for Closed Loop Die Control, Patent WO2021141819A1. (2021).

[4] M. Barthau, M. Liewald, New approach on controlling strain distribution manufactured in sheet metal components during deep drawing process, International Conference on the Technology of Plasticity, Procedia Engineering. 207 (2017) 66-71. https://doi.org/10.1016/j.proeng.2017.10.740

[5] H. Kim, J.C. Gu, L. Zoller, Control of the servo-press in stamping considering the variation of the incoming material properties, International Deep Drawing Research Group 38th Annual Conference, IOP Conference Series: Materials Science and Engineering. 651 (2019) 012062. https://doi.org/10.1088/1757-899X/651/1/012062

[6] J.M. Allwood, S.R. Duncan, J. Cao, P. Groche, G. Hirt, B. Kinsey, T. Kuboki, M. Liewald, A. Sterzing, A.E. Tekkaya, Closed-loop control of product properties in metal forming, CIRP Annals - Manufacturing Technology. 65 (2016) 573-596. https://doi.org/10.1016/j.cirp.2016.06.002

[7] J. Cao, E. Brinksmeier, M. Fu, R.X. Gao, B. Liang, M. Merklein, M. Schmidt, J. Yanagimoto, Manufacturing of advanced smart tooling for metal forming, CIRP Annals - Manufacturing Technology. 68 (2019) 605-628. https://doi.org/10.1016/j.cirp.2019.05.001

[8] C.A. Coulomb, Théorie des machines simples: en ayant égard au frottement de leurs parties, et à la roideur de cordages, Mémoires de mathématique et de physique, 1785

[9] F. Barlat, K. Lian, Plastic behavior and stretchability of sheet metals. Part I: A yield function for orthotropic sheets under plane stress conditions, International Journal of Plasticity. 5 (1989) 51-66. https://doi.org/10.1016/0749-6419(89)90019-3

[10] DIN EN 10027-2: Bezeichnungssysteme für Stähle - Teil 2: Nummernsystem. Beuth Verlag GmbH, 2015

[11] DIN EN ISO 6892-1: Metallische Werkstoffe - Zugversuch - Teil 1: Prüfverfahren bei Raumtemperatur. Beuth Verlag GmbH, 2020

[12] H.W. Swift, Plastic instability under plane stress, Journal of the Mechanics and Physics of Solids. 1 (1952) 1-18. https://doi.org/10.1016/0022-5096(52)90002-1

[13] J.E. Hockett, O.D. Sherby, Large strain deformation of polycrystalline metals at low homologous temperatures, Journal of the Mechanics and Physics of Solids. 23 (1975) 87-98. https://doi.org/10.1016/0022-5096(75)90018-6

[14] W. Müschenborn, H.-M. Sonne, Einfluß des Formänderungsweges auf die Grenzformänderungen des Feinblechs, Archiv für das Eisenhüttenwesen. 46 (1975) 597-602. https://doi.org/10.1002/srin.197503686

[15] Information on https://dictionary.cambridge.org/de/worterbuch/englisch/eligibility (last checked 5th of February, 2024)
## References

[1] S. de Vries, The Automobile Industry - Pocket Guide 2023/2024, ACEA - European Automobile Manufacturers' Association (2023) 5-9.

[2] R.O. Jung, F. Bleicher, S. Krall, C. Juricek, R. Lottes, K. Steinschütz, T. Reininger, Cyber Physical Production Systems for Deep Drawing, J. Manuf. Sci. Eng. 145 (2023) 101006. https://doi.org/10.1115/1.4062903

[3] S. Thaddaeus, P. Henri, Adjustable Balancing Block for Closed Loop Die Control, Patent WO2021141819A1. (2021).

[4] M. Barthau, M. Liewald, New approach on controlling strain distribution manufactured in sheet metal components during deep drawing process, International Conference on the Technology of Plasticity, Procedia Engineering. 207 (2017) 66-71. https://doi.org/10.1016/j.proeng.2017.10.740

[5] H. Kim, J.C. Gu, L. Zoller, Control of the servo-press in stamping considering the variation of the incoming material properties, International Deep Drawing Research Group 38th Annual Conference, IOP Conference Series: Materials Science and Engineering. 651 (2019) 012062. https://doi.org/10.1088/1757-899X/651/1/012062

[6] J.M. Allwood, S.R. Duncan, J. Cao, P. Groche, G. Hirt, B. Kinsey, T. Kuboki, M. Liewald, A. Sterzing, A.E. Tekkaya, Closed-loop control of product properties in metal forming, CIRP Annals - Manufacturing Technology. 65 (2016) 573-596. https://doi.org/10.1016/j.cirp.2016.06.002

[7] J. Cao, E. Brinksmeier, M. Fu, R.X. Gao, B. Liang, M. Merklein, M. Schmidt, J. Yanagimoto, Manufacturing of advanced smart tooling for metal forming, CIRP Annals - Manufacturing Technology. 68 (2019) 605-628. https://doi.org/10.1016/j.cirp.2019.05.001

[8] C.A. Coulomb, Théorie des machines simples: en ayant égard au frottement de leurs parties, et à la roideur de cordages, Mémoires de mathématique et de physique, 1785

[9] F. Barlat, K. Lian, Plastic behavior and stretchability of sheet metals. Part I: A yield function for orthotropic sheets under plane stress conditions, International Journal of Plasticity. 5 (1989) 51-66. https://doi.org/10.1016/0749-6419(89)90019-3

[10] DIN EN 10027-2: Bezeichnungssysteme für Stähle - Teil 2: Nummernsystem. Beuth Verlag GmbH, 2015

[11] DIN EN ISO 6892-1: Metallische Werkstoffe - Zugversuch - Teil 1: Prüfverfahren bei Raumtemperatur. Beuth Verlag GmbH, 2020

[12] H.W. Swift, Plastic instability under plane stress, Journal of the Mechanics and Physics of Solids. 1 (1952) 1-18. https://doi.org/10.1016/0022-5096(52)90002-1

[13] J.E. Hockett, O.D. Sherby, Large strain deformation of polycrystalline metals at low homologous temperatures, Journal of the Mechanics and Physics of Solids. 23 (1975) 87-98. https://doi.org/10.1016/0022-5096(75)90018-6

[14] W. Müschenborn, H.-M. Sonne, Einfluß des Formänderungsweges auf die Grenzformänderungen des Feinblechs, Archiv für das Eisenhüttenwesen. 46 (1975) 597-602. https://doi.org/10.1002/srin.197503686

[15] Information on https://dictionary.cambridge.org/de/worterbuch/englisch/eligibility (last checked 5th of February, 2024)
# Electrically-assisted forming of 5754 aluminium alloy under different strain conditions

DOBRAS Daniel¹,ª*, ZIMNIAK Zbigniew¹,ᵇ, DZIUBEK Mateusz¹,ᶜ

¹ Department of Mechanical Engineering, Wrocław University of Science and Technology, 5 Ignacego Łukasiewicza Street, 50-371 Wrocław, Poland

ªdaniel.dobras@pwr.edu.pl, ᵇzbigniew.zimniak@pwr.edu.pl, ᶜmateusz.dziubek@pwr.edu.pl

**Keywords:** Electroplastic Effect, Dynamic Recovery, Deep Drawing

**Abstract.** Electricity-assisted forming processes can significantly improve material ductility and process efficiency. However, further research into different strain conditions is necessary, for example, in stamping processes. In this study, tensile and deep drawing tests of the 5754 aluminium alloy were carried out with the application of current pulses on a specially constructed experimental setup. The study showed that it is possible to increase the plasticity of the material. The main cause responsible for the increase in plasticity was dynamic recovery.

**Introduction**

The use of light metal alloys with high specific strength helps reduce the weight of vehicles and thus reduce exhaust emissions in the automotive industry [1]. The formability of aluminium and magnesium alloys is generally low at room temperature [2]. Warm and hot forming processes improve formability; however, this results in higher energy consumption and generates problems such as dimensional accuracy and lubrication effectiveness reduction [3].

The formability of aluminium alloys (AA) can also be increased by applying current pulses during its deformation. This method is called Electrically-Assisted Forming (EAF) and has many advantages over conventional forming methods, such as reducing flow stress and increasing material formability [4]. Previous studies have shown that thanks to the additional application of current pulses, it is possible to increase the elongation of the 5052-H32 aluminium alloy [5] and the AZ91 magnesium alloy [6] even more than three times. This large increase in elongation can be explained by the localized Joule heat theory [7]. Nevertheless, other studies have shown that low-temperature pulsed current-assisted deformation can also lead to a significant improvement in the plasticity of zinc [8] and titanium alloys [9]. These changes can be explained by some athermal phenomena (electroplastic effect) [10] or reconfiguration of crystal lattice defects [9]. Further research is needed to precisely determine the impact of thermal and athermal effects.

Although the physical basis of the phenomena occurring during EAF processes is still not clearly defined, many attempts have been made to implement electrically-assisted (EA) industrial processes. Zimniak et al. [11] showed that it is possible to reduce the drawing force in the cooper EA wire drawing process. The products obtained in this way are characterized by better ductility, with no decrease in strength. Similar results were obtained in the rolling process of the AZ31 magnesium alloy [12] supported by the application of current pulses. Xie et al. [13] demonstrated that it is possible to increase the plasticity of the AZ31B magnesium alloy sheet in the EA deep drawing process. However, in the case of other alloys [14], [15] the increase in plasticity was insignificant; therefore, more research is needed to improve the efficiency of this process.

**Materials and Methods**

Samples made of 5754 aluminium alloy in the form of a 1 mm thick sheet were used in the tests. The material was delivered in two hardening states: H111 and H22. In order to realize different strain conditions, two types of tests were performed: tensile and deep drawing. An INSTRON 3369

<figure><img src="image_1363.png" /></figure>
# Electrically-assisted forming of 5754 aluminium alloy under different strain conditions

DOBRAS Daniel¹,ª*, ZIMNIAK Zbigniew¹,ᵇ, DZIUBEK Mateusz¹,ᶜ

¹ Department of Mechanical Engineering, Wrocław University of Science and Technology, 5 Ignacego Łukasiewicza Street, 50-371 Wrocław, Poland

ªdaniel.dobras@pwr.edu.pl, ᵇzbigniew.zimniak@pwr.edu.pl, ᶜmateusz.dziubek@pwr.edu.pl

**Keywords:** Electroplastic Effect, Dynamic Recovery, Deep Drawing

**Abstract.** Electricity-assisted forming processes can significantly improve material ductility and process efficiency. However, further research into different strain conditions is necessary, for example, in stamping processes. In this study, tensile and deep drawing tests of the 5754 aluminium alloy were carried out with the application of current pulses on a specially constructed experimental setup. The study showed that it is possible to increase the plasticity of the material. The main cause responsible for the increase in plasticity was dynamic recovery.

**Introduction**

The use of light metal alloys with high specific strength helps reduce the weight of vehicles and thus reduce exhaust emissions in the automotive industry [1]. The formability of aluminium and magnesium alloys is generally low at room temperature [2]. Warm and hot forming processes improve formability; however, this results in higher energy consumption and generates problems such as dimensional accuracy and lubrication effectiveness reduction [3].

The formability of aluminium alloys (AA) can also be increased by applying current pulses during its deformation. This method is called Electrically-Assisted Forming (EAF) and has many advantages over conventional forming methods, such as reducing flow stress and increasing material formability [4]. Previous studies have shown that thanks to the additional application of current pulses, it is possible to increase the elongation of the 5052-H32 aluminium alloy [5] and the AZ91 magnesium alloy [6] even more than three times. This large increase in elongation can be explained by the localized Joule heat theory [7]. Nevertheless, other studies have shown that low-temperature pulsed current-assisted deformation can also lead to a significant improvement in the plasticity of zinc [8] and titanium alloys [9]. These changes can be explained by some athermal phenomena (electroplastic effect) [10] or reconfiguration of crystal lattice defects [9]. Further research is needed to precisely determine the impact of thermal and athermal effects.

Although the physical basis of the phenomena occurring during EAF processes is still not clearly defined, many attempts have been made to implement electrically-assisted (EA) industrial processes. Zimniak et al. [11] showed that it is possible to reduce the drawing force in the cooper EA wire drawing process. The products obtained in this way are characterized by better ductility, with no decrease in strength. Similar results were obtained in the rolling process of the AZ31 magnesium alloy [12] supported by the application of current pulses. Xie et al. [13] demonstrated that it is possible to increase the plasticity of the AZ31B magnesium alloy sheet in the EA deep drawing process. However, in the case of other alloys [14], [15] the increase in plasticity was insignificant; therefore, more research is needed to improve the efficiency of this process.

**Materials and Methods**

Samples made of 5754 aluminium alloy in the form of a 1 mm thick sheet were used in the tests. The material was delivered in two hardening states: H111 and H22. In order to realize different strain conditions, two types of tests were performed: tensile and deep drawing. An INSTRON 3369

<figure><img src="image_1367.png" /></figure>
tensile machine was used to carry out the tensile tests with a strain rate of 0.0025 s⁻¹. Tensile samples with a experimentally fitted gauge length of 75 mm and a gauge width of 12 mm, milled along the rolling direction, were used.

The Erichsen 142 Sheet Metal Testing Machine was used to carry out deep drawing tests with a punch speed of 0.4 mm/s. Two operating modes were used to implement the deep drawing process: normal (NL) and sheet holder quick release (SHQR). In the NL mode, a constant blank holder force was maintained throughout the test. In SHQR mode, the blank holder force was immediately reduced from the initial value to zero after reaching the set punch depth value. A punch with a circular section with a diameter of 30 mm and a radius of 6 mm and a die with a diameter of 33.5 mm and a radius of 4 mm were used for the deep drawing process. Three samples of different shapes and dimensions were intended for the deep drawing process. Rectangular sample No. 1 with dimensions of 66 by 12 mm was formed in the NL mode with a blank holder force of 30 kN. Circular sample No. 2 with a diameter of 66 mm was formed in both modes with a blank holder force of 40 kN. Sample No. 3, with experimentally fitted dimensions visible in Fig. 1, was formed in the SHQR mode with a blank holder force of 40 kN. A lower value of the blank holder force was used for sample No. 1 due to its much smaller contact area with the blank holder than for other samples.

<figure><img src="image_1364.png" /><figcaption>Fig. 1. a) The shape and dimensions (in mm) of sample No. 3; b) Part of the experimental setup with sample No. 3.</figcaption></figure>

The self-constructed current pulse generator operating at a voltage of 2.52 V was used to apply current pulses to the samples during the tensile and deep drawing processes. Important parameters of the power generator also include: maximum value of the pulse current 15 kA and capacity of a bank of capacitors 14 000 F. In the tensile test, current pulses were delivered through electrodes attached to the sample. In the deep drawing test, current pulses were delivered by dies that were also electrodes, as shown in the scheme of the experimental setup (Fig. 2). Dies-electrodes were made of CuNi₂Be copper alloy with high conductivity and strength. In order to avoid the flow of current to the machine, insulators are used, visible, among others, in Fig. 2. For this purpose, the screws used to build the experimental setup were also made of non-conductive material. The current was applied in the form of pulsed current generated by a function generator. The pulsed current was chosen because it allows for a greater increase in plasticity than continuous current [9]. The current parameters used were marked in the form p/d, where p is the period and d is the pulse duration. The time p was the time after which the first pulse was applied in the tensile tests.
tensile machine was used to carry out the tensile tests with a strain rate of 0.0025 s⁻¹. Tensile samples with a experimentally fitted gauge length of 75 mm and a gauge width of 12 mm, milled along the rolling direction, were used.

The Erichsen 142 Sheet Metal Testing Machine was used to carry out deep drawing tests with a punch speed of 0.4 mm/s. Two operating modes were used to implement the deep drawing process: normal (NL) and sheet holder quick release (SHQR). In the NL mode, a constant blank holder force was maintained throughout the test. In SHQR mode, the blank holder force was immediately reduced from the initial value to zero after reaching the set punch depth value. A punch with a circular section with a diameter of 30 mm and a radius of 6 mm and a die with a diameter of 33.5 mm and a radius of 4 mm were used for the deep drawing process. Three samples of different shapes and dimensions were intended for the deep drawing process. Rectangular sample No. 1 with dimensions of 66 by 12 mm was formed in the NL mode with a blank holder force of 30 kN. Circular sample No. 2 with a diameter of 66 mm was formed in both modes with a blank holder force of 40 kN. Sample No. 3, with experimentally fitted dimensions visible in Fig. 1, was formed in the SHQR mode with a blank holder force of 40 kN. A lower value of the blank holder force was used for sample No. 1 due to its much smaller contact area with the blank holder than for other samples.

<figure><img src="image_1368.png" /><figcaption>Fig. 1. a) The shape and dimensions (in mm) of sample No. 3; b) Part of the experimental setup with sample No. 3.</figcaption></figure>

The self-constructed current pulse generator operating at a voltage of 2.52 V was used to apply current pulses to the samples during the tensile and deep drawing processes. Important parameters of the power generator also include: maximum value of the pulse current 15 kA and capacity of a bank of capacitors 14 000 F. In the tensile test, current pulses were delivered through electrodes attached to the sample. In the deep drawing test, current pulses were delivered by dies that were also electrodes, as shown in the scheme of the experimental setup (Fig. 2). Dies-electrodes were made of CuNi₂Be copper alloy with high conductivity and strength. In order to avoid the flow of current to the machine, insulators are used, visible, among others, in Fig. 2. For this purpose, the screws used to build the experimental setup were also made of non-conductive material. The current was applied in the form of pulsed current generated by a function generator. The pulsed current was chosen because it allows for a greater increase in plasticity than continuous current [9]. The current parameters used were marked in the form p/d, where p is the period and d is the pulse duration. The time p was the time after which the first pulse was applied in the tensile tests.
In the deep drawing tests, the application of pulses began when the SHQR mode was activated or after reaching 3 mm of punch depth (NL mode). The current flowing through the samples was measured using a Rogowski coil and an oscilloscope. The FLIR 440 thermal imaging camera was used to measure the surface temperature of samples previously painted with non-conductive black spray. Each tensile and deep drawing test was repeated three times.

Observations of the microstructure of selected samples were made using a Hitachi H-800 transmission electron microscope (TEM) operating at a voltage of 150 kV. Specimens for microstructure observation were thinned by grinding and then electrochemically polished. Finally, the 3 mm thin discs were ion milled to obtain sufficient quality of specimens.

<figure><img src="image_1365.png" /><figcaption>Fig. 2. Scheme of the electrically-assisted deep drawing experimental setup.</figcaption></figure>

## Results and Discussion

The engineering strass-strain curves of the aluminium alloys 5754-H22 and 5754-H111 with and without pulsed current application are shown in Figure 3a and 3b, respectively. It is clearly seen that the application of current pulses results in an increase in the total elongation of the 5754 aluminium alloy in both the H22 (by 105%) and H111 (by 48%) states. This is less than that of 5052-H32 aluminum alloy [5], but more than that of 5083 aluminum alloy in various hardening states [16]. When a current pulse is applied, the sample temperature increases significantly. At the same time, the stress value on the stress-strain curve drops dramatically. In this study, the nominal current density (the current value, measured by the Rogowski coil, divided by the cross section area of the sample) was 200 A/mm². This drop in stress is mainly caused by thermal expansion and softening due to Joule heating. However, just before the next pulse is applied, the temperature drops almost to the room value [17]. The lack of stress increase to the value corresponding to the curve without the application of current pulse, as well as the increase in material plasticity, is explained by the annealing of the material. The maximal values of the sample surface temperature recorded by the thermal camera are 332 and 295 °C for alloys in the H22 and H111 states, respectively. Nevertheless, according to the localized Joule heat theory, the temperature near grain boundaries and dislocation clusters could have been temporarily higher [7]. Therefore, these were places particularly suitable for recovery and recrystallization processes. It should be noted that the average surface temperature of the sample during the test was less than 150 °C. The sample under the H22 condition achieved a greater increase in elongation, and was intended for further tests.