Closed-Loop-Control of the Material Flow in the Deep Drawing Process

Behrens, Bernd Arno; Yun, Jae-Woong; Milch, M.

doi:10.4028/www.scientific.net/amr.6-8.321

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…They are therefore cost-effective and technically feasible [9]. Fuzzy controllers were successfully applied in forming technology by [11][12][13][14][15][16].…”

Section: F Fuzzy Uzzy-contr -Control Olmentioning

confidence: 99%

Design of a fuzzy controller to prevent wrinkling during rotary draw bending

Borchmann¹,

Schneider²,

Engel³

2021

Esaform 2021

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Rotary draw bending (RDB) is a forming process that is commonly used to bend tubes with small wall thicknesses and small bending radii. One of the limitations of this process is the formation of wrinkles caused by compressive stress on the inner bend. In order to design the bending process without wrinkles and to determine the necessary process parameters, adjustment tests are required. Within this work, a fuzzy controller is to be developed which automatically prevents the formation of wrinkles and thus eliminates the need for time-consuming set-up tests to determine the necessary process parameters. The fuzzy controller is based on fuzzy set theory and fuzzy logic. In connection with a rule base it is possible to simulate the human decision process. A fuzzy controller is programmed based on a max-min controller, with the required rules resulting from previous bending tests. After the fuzzy controller has been implemented, it must be connected to the bending machine by suitable interfaces. The input values, which indicate wrinkles, are measured by sensors during the bending process and provide the controller with data. The fuzzy controller then uses the control base to specify the required control variables. After programming has been completed, practical validation tests were carried out. In the validation tests using different tube wall thicknesses and materials, a significant reduction of wrinkles is achieved. Bending of completely wrinkle-free tubes is also possible due to the automated finding of optimal tool settings. Using the fuzzy controller eliminates the need for costly adjustment bends, resulting in significant time and cost savings.

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“…They are therefore cost-effective and technically feasible [9]. Fuzzy controllers were successfully applied in forming technology by [11][12][13][14][15][16].…”

Section: F Fuzzy Uzzy-contr -Control Olmentioning

confidence: 99%

Design of a fuzzy controller to prevent wrinkling during rotary draw bending

Borchmann¹,

Schneider²,

Engel³

2021

Esaform 2021

View full text Add to dashboard Cite

show abstract

“…A wide-spread alternative is to statistically correlate process variables with quality variables and control the process variables online. Therefore, online closed-loop control focuses on controlling process or machine variables like forces or paths [3], e. g. in deep-drawing processes [4,5]. Nevertheless, this approach only works up to a certain extent, as the quantitative relationship between process and product variables changes continuously over time, e.g.…”

Section: Introductionmentioning

confidence: 99%

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

Hoppe

Knoll

Götz

et al. 2018

AMM

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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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