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Potentials of an adaptive blank positioning to control material and process fluctuations in deep drawing
Author(s) -
David Briesenick,
Mathias Liewald,
Patrick Cyron
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/967/1/012068
Subject(s) - blank , deep drawing , sheet metal , process (computing) , scrap , position (finance) , quality (philosophy) , component (thermodynamics) , sensitivity (control systems) , mechanical engineering , relation (database) , computer science , process control , engineering , data mining , electronic engineering , philosophy , physics , finance , epistemology , economics , thermodynamics , operating system
Series production of sheet metal components in press shops is permanently subjected to an increasing pressure in time, cost and quality. Varying sheet metal properties due to batch fluctuations and changing process conditions lead to an increase of try out time phase and scrap rate, resulting in a demand for adaptive control strategies for deep drawing. Today, these chal-lenges are met by integrating sensors and actuators into tool structure which measure and control part quality, mainly through blank draw-in. However, such tool-based control systems require a complex and cost-intensive modification of the existing die or press technology. Against this background, the active adjustment of blank position prior the deep drawing process realized with an intelligent transfer and positioning system as a promising approach towards economic and technical aspects. This paper deals with blank positioning and its sensitivity to quality-related failures of deep drawn sheet metal components like splits and wrinkles. Therefore, a numerical study was conducted on a deep drawing process of an exemplary structural part geometry, wherein a typical fluctuation of material parameters and variation of local friction conditions was simulated. Subsequently, correlations between process disturbance and blank draw-in were elaborated, thus using local draw-in values as controlled variables for a closed loop system. Sim-ulation results showed that the manipulating parameter, i.e. the blank position prior deep draw-ing, reveals a significant influence on the draw-in and therefore on the component s quality. An essential finding of this study is the numerical proof of concept for this new deep drawing control strategy, demonstrated for different process conditions. Finally, disturbances in the deep drawing process considered could be successfully controlled by adapting the blank position.

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