Reducing Uncertainty in Shunt Damping by Model-Predictive Product Stiffness Control in a Single Point Incremental Forming Process

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The stiffness of metal formed products strongly affects the dynamic behavior of structures in which they are integrated. Forming processes underlie short and long-term variations which cause the stiffness to be uncertain.In the application of resonant shunted piezoelectric transducers for vibration attenuation, uncertain stiffness may cause significant reduction in the vibration attenuation performance due to imprecise tuning. In the past, large efforts were made to control one or more geometrical feature of products while weightier features that cause uncertainty have not been addressed.In this paper, a single point incremental forming process of a membrane-like spring element on a servo press with a 3 degrees of freedom drive system is investigated. This spring element is used in a beam support for lateral vibration attenuation with resonant shunted transducers as well as axial buckling stabilization.To reduce uncertainty caused by process variations, an offline closed-loop control of product stiffness is presented. Different product and forming criteria are integrated into a control approach based on an optimization routine. By making use of a model-based prediction of the product properties, the approach shows how to realize a multi-objective control.

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Edited by:

Peter F. Pelz and Peter Groche

Pages:

35-47

Citation:

F. Hoppe et al., "Reducing Uncertainty in Shunt Damping by Model-Predictive Product Stiffness Control in a Single Point Incremental Forming Process", Applied Mechanics and Materials, Vol. 885, pp. 35-47, 2018

Online since:

November 2018

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[1] Dj.M. Maric, P.F. Meier and S.K. Estreicher: Mater. Sci. Forum Vol. 83-87 (1992), p.119.

[2] Jörg Heingärtner, Yasar Renkci, and Pavel Hora. Application of non-destructive testing to control material properties of stainless steel in kitchen sink production,. In: IDDRG 2013 Conference: Towards Zero Failure Production Methods by Advanced Modeling Techniques and a Process Integrated Virtual Control. Ed. by Pavel Hora. ETH Zurich, Institute of Virtual Manufacturing, 2013, p.80.

DOI: https://doi.org/10.1063/1.3623590

[3] C. Held, M. Liewald, and M. Sindel. Untersuchungen zum Einfluss werkstofflicher Schwankungen innerhalb eines Coils auf die Umformbarkeit,. In: wt Werkstattstechnik online 99 (2009), pp.732-739.

[4] Benny Endelt, Søren Tommerup, and Joachim Danckert. A novel feedback control system - Controlling the material flow in deep drawing using distributed blank-holder force,. In: Journal of Materials Processing Technology 213.1 (2013).

DOI: https://doi.org/10.1016/j.jmatprotec.2012.08.003

[5] Bernd Arno Behrens, J. W. Yun, and M. Milch. Closed-Loop-Control of the Material Flow in the Deep Drawing Process,. In: Advanced Materials Research 6-8 (2005), pp.321-328. ISBN: 1662-8985..

[6] Peter Groche et al. Blanking-bending process chain with disturbance feed-forward and closedloop control,. In: Journal of Manufacturing Processes 24 (2016), pp.62-70. ISBN: 15266125..

[7] Jos Havinga and Ton van den Boogaard. Estimating product-to-product variations in metal forming using force measurements,. In: AIP Conference Proceedings. Author(s), 2017, p.070002..

[8] Jos Havinga et al. Feedforward control of sheet bending based on force measurements,. In: Journal of Manufacturing Processes 31 (2018), pp.260-272. ISBN: 15266125. DOI: 10.1016/ j.jmapro.2017.10.011.

[9] Daniel Hesse, Florian Hoppe, and Peter Groche. Controlling Product Stiffness by an Incremental Sheet Metal Forming Process,. In: Procedia Manufacturing 10 (2017), pp.276-285. ISBN: 2351- 9789..

[10] Haibo Lu et al. Model predictive control of incremental sheet forming for geometric accuracy improvement,. In: The International Journal of Advanced Manufacturing Technology 82.9 (2016), pp.1781-1794. ISBN: 1433-3015..

[11] Benedict Götz, Roland Platz, and Tobias Melz. Effect of static axial loads on the lateral vibration attenuation of a beam with piezo-elastic supports,. In: Smart Materials and Structures 27.3 (2018), p.035011..

[12] Maximilian Schaeffner and Roland Platz. Gain-scheduled H1 buckling control of a circular beam-column subject to time-varying axial loads,. In: Smart Materials and Structures (2018).

DOI: https://doi.org/10.1088/1361-665x/aab63a

[13] M.H.A. Bonte, A. H. van den Boogaard, and J. Huétink. A Metamodel Based Optimisation Algorithm for Metal Forming Processes,. In: Advanced methods in material forming. Ed. by D. Banabic. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2007, pp.55-72. ISBN: 978-3- 540-69845-6..

[14] G.E.P. Box and K. P. Wilson. K B. 1951. On the Experimental Attainment of Optimum Conditions,. In: Journal of the Royal Statistical Society 13 (1951), pp.1-45.

[15] Angela Dean, Daniel Voss, and Danel Draguljić, eds. Design and Analysis of Experiments. Second edition. Springer Texts in Statistics. Cham: Springer International Publishing, 2017. ISBN: 978-3-319-52250-0.

DOI: https://doi.org/10.1007/978-3-319-52250-0_13

[16] Manfred Morari and Jay H. Lee. Model predictive control: Past, present and future,. In: Computers & Chemical Engineering 23.4-5 (1999), pp.667-682. ISBN: 0098-1354.

DOI: https://doi.org/10.1016/s0098-1354(98)00301-9

[17] L. Landi et al. Sheets impact simulation for safety guards design: Experiments and correlation for FE Explicit models of non-alloy steel,. In: Procedia Structural Integrity 8 (2018), pp.3-13. ISBN: 24523216..

[18] Benedict Götz et al. Model verification and validation of a piezo-elastic support for passive and active structural control of beams with circular cross-section,. In: Applied Mechanics and Materials, Trans Tech Publications 807 (2015), pp.67-77.

DOI: https://doi.org/10.4028/www.scientific.net/amm.807.67