journal article·2023-01-29Open access

Robust Design of Deep Drawing Process through In-Line Feedback Control of the Draw-In

Luigi Tricarico, Maria Emanuela Palmieri

Applied Sciences· Volume 13· Issue 3

Abstract

In the deep drawing process, the scatter of the friction coefficient between blank and tool interfaces as well as of the material properties between blank positions in the coil or between different coils significantly influences the part quality. These uncontrollable fluctuations increase the risk of waste. To avoid this problem, currently, the new era of Industry 4.0 aims at developing control algorithms able to in-line adjust process parameters and always meet the part quality requirements. Starting from this context, in this study a method for process control during the punch stroke is proposed. It assumes the blank draw-in in specific points as the control variable, while the blank holder force is adopted as an in-line adjustable process parameter. The approach was implemented for the deep drawing of a T-shaped component, using a blank in DC05 steel with a thickness of 0.75 mm. The results show that the measurement of blank draw-in is a representative index of the component quality, which in this study is evaluated in terms of formability (thinning) and cosmetic (surface deflections) defects. Once the optimal condition and the corresponding blank draw-in were identified, the feedback control algorithm was able to increase or reduce the blank holder force according to whether the recorded draw-in was higher or lower than the optimal one.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Metal Forming Simulation Techniques · Metallurgy and Material Forming · Advanced Surface Polishing Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical Engineering, Mathematics & Management Engineering, Politecnico of Bari, 70126 Bari, Italy

Funding

PNRR—Spoke 11 (Innovative Materials and Lightweighting) project · PICO&PRO project

References (45)

Show source-provided references
1. Novel concept for measurement of global blank draw-in when deep drawing outer skin automotive components10.1088/1742-6596/896/1/012034 ↗
2. A review on deep drawing process10.23956/ijermt.v6i6.260 ↗
3. Cold forming by stretching of aeronautic sheet metal parts10.1080/0951192X.2013.800641 ↗
4. Effect of die design parameters on thinning of sheet metal in the deep drawing process10.12691/ajme-1-2-1 ↗
5. Investigation of the effect of blank holder force distribution on deep drawing using developed blank holder divided into double rings10.1007/s40430-021-03003-7 ↗
6. Estimation of optimal blank holder force trajectories in segmented binders using an ARMA model10.1115/1.1616948 ↗
7. Ahmetoglu, M.A., Coremans, A., Kinzel, G.L., and Altan, T. (1993). Improving Drawability by Using Variable Blank Holder Force and Pressure in Deep Drawing of Round and Non-Symmetric Parts, SAE International. No. 930287; SAE Technical Paper.10.4271/930287 ↗
8. Palmieri, M., Lorusso, V., and Tricarico, L. (2021). Robust optimization and Kriging metamodeling of deep-drawing process to obtain a regulation curve of blank holder force. Metals, 11.10.3390/met11020319 ↗
9. Control of draw-in in the deep-drawing process by regulating the force on the blank holder10.1088/1757-899X/1238/1/012071 ↗
10. A review on effect of thinning, wrinkling and spring-back on deep drawing process10.1177/0954405417752509 ↗
11. Effect of material scatter on the plastic behavior and stretchability in sheet metal forming10.1016/j.jmatprotec.2013.08.008 ↗
12. Inline feedback control for deep drawing applications10.1088/1757-899X/159/1/012006 ↗
13. Robustness analysis with LS-OPT® and LS-DYNA® for sheet metal forming simulations10.1088/1757-899X/1157/1/012088 ↗
14. Wiebenga, J.H. (2014). Robust Design and Optimization of Forming Processes. [Ph.D. thesis, University of Twente Faculty of Engineering Technology].
15. Process optimization of sheet metal forming using operating window
16. Experiences with inline feedback control and data acquisition in deep drawing10.1016/j.promfg.2018.07.401 ↗
17. Implementation of feedback control in kitchen sink production10.1088/1757-899X/418/1/012110 ↗
18. A knowledge-based control system for the robust manufacturing of deep drawn parts10.1016/j.proeng.2017.10.735 ↗
19. (2022, December 10). Available online: https://ahssinsights.org/news/vision-for-industry-4-0-in-sheet-metal-forming/.
20. Real-time control of sheet stability during forming10.1115/1.2901664 ↗
21. New framework for on-line feedback control of a deep-drawing operation10.1016/j.jmatprotec.2006.04.026 ↗
22. A novel feedback control system–Controlling the material flow in deep drawing using distributed blank-holder force10.1016/j.jmatprotec.2012.08.003 ↗
23. Monitoring the displacement of a blank in a deep drawing process by using a new embedded-type sensor10.1007/s001700050137 ↗
24. Contactless on-line measurement of material flow for closed loop control of deep drawing10.1016/S0924-0136(02)00763-X ↗
25. Development of an optical sensor for the measurement of the material flow in deep drawing processes10.1016/S0007-8506(07)60571-X ↗
26. A Draw-In Sensor for Process Control and Optimization10.1063/1.2011330 ↗
27. Controllability of Temperature Induced Friction Effects during Deep Drawing of Car Body Parts with High Drawing Depths in Series Production10.1016/j.promfg.2020.04.166 ↗
28. Iterative process control and sensor evaluation for deep drawing tools with integrated piezoelectric actuators
29. Step by step control of a deep drawing process with piezo-electric actuators in serial operation10.1051/matecconf/20152104008 ↗
30. Active control of blankholder in sheet metal stamping10.1016/j.procir.2021.05.079 ↗
31. (2022, November 29). Available online: https://www.esb-group.com/en/products-din-en/cold-rolled-steel/.
32. Influence of material models on the accuracy of the sheet forming simulation10.1080/10426914.2011.578005 ↗
33. A theory of the yielding and plastic flow of anisotropic metals
34. Quantitative analysis of surface deflections in the automobile exterior panel based on a curvature-deviation method10.1016/j.jmatprotec.2012.03.005 ↗
35. Optimum settings for automatic controllers
36. Waleed, E.-B. (2022, December 19). Automated Ziegler Nicholas PID Tuning. MATLAB Central File Exchange. Available online: https://www.mathworks.com/matlabcentral/fileexchange/47836-automated-ziegler-nicholas-pid-tuning.
37. Design and control of forming parameters using finite element analysis
38. Accommodation of springback error in channel forming using active binder force control: Numerical simulations and experiments10.1115/1.2806830 ↗
39. Closed loop control of the friction force. Deep drawing process10.1016/S0924-0136(97)00158-1 ↗
40. Ziegler, M. (1999). Pulsating Blankholder Technology, SAE International. No. 1999-01-3155; SAE Technical Paper.10.4271/1999-01-3155 ↗
41. Development of process control in sheet metal forming10.1016/S0924-0136(02)00321-7 ↗
42. Lim, Y. (2010). MIMO Adaptive Process Control in Stamping Using Punch Force. [Ph.D. Thesis, University of Michigan].
43. Kriging metamodeling in simulation: A review10.1016/j.ejor.2007.10.013 ↗
44. Thinning and spring back prediction of sheet metal in the deep drawing process10.1016/j.matdes.2013.07.078 ↗
45. Bhaduri, A. (2018). Deep Drawing. Mechanical Properties and Working of Metals and Alloys, Springer.10.1007/978-981-10-7209-3 ↗