Schnitt-, Stanz- und Ziehwerkzeuge

Oehler, Gerhard; Kaiser, Stefan

doi:10.1007/978-3-642-97498-4

Cited by 21 publications

(11 citation statements)

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“…The active adjustable zones are placed in the straight side zones of the deep-drawing flange with the active die in accordance with the requirements of [2,3,4] as an analogy to the rectangular cup and the active zones are triggered by piezoelectric actuators. These piezoelectric actuators were arranged in modular design in comparison to the work of Neugebauer [7,8] because the modular design make large-scale pressure patterns possible in the side zones.…”

Section: Design Of the Active Diementioning

confidence: 99%

“…Using the piezoelectric modules in the flange zone of the active bottom die enables us to actively shift the surface pressure in the flange zone. The side zones can be impinged with locally higher surface pressure as per the requirements of [2,3,4] by activating the piezoelectric actuator. Maximizing the surface pressure in the side zones reduces the surface pressure if the blankholder force remains the same in the corner zones which guarantees a higher level of material in the corner zones.…”

Section: Design Of the Active Diementioning

confidence: 99%

“…Correcting variables are known in the form of pressure distributions on the blankholder, drawbeads [2,3,4], blankholder distances [5] or tribological systems. Furthermore, the correcting variables listed above have to be well aligned to the forming process to create forming tools with reliable processes.…”

Section: The Initial Situationmentioning

confidence: 99%

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Integrated piezoelectric actuators in deep drawing tools

Neugebauer

Mainda

Drossel

et al. 2011

Industrial and Commercial Applications of Smart Structures Technologies 2011

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The production of car body panels are defective in succession of process fluctuations. Thus the produced car body panel can be precise or damaged. To reduce the error rate, an intelligent deep drawing tool was developed at the Fraunhofer Institute for Machine Tools and Forming Technology IWU in cooperation with Audi and Volkswagen. Mechatronic components in a closed-loop control is the main differentiating factor between an intelligent and a conventional deep drawing tool. In correlation with sensors for process monitoring, the intelligent tool consists of piezoelectric actuators to actuate the deep drawing process. By enabling the usage of sensors and actuators at the die, the forming tool transform to a smart structure. The interface between sensors and actuators will be realized with a closed-loop control. The content of this research will present the experimental results with the piezoelectric actuator. For the analysis a production-oriented forming tool with all automotive requirements were used. The disposed actuators are monolithic multilayer actuators of the piezo injector system. In order to achieve required force, the actuators are combined in a cluster. The cluster is redundant and economical. In addition to the detailed assembly structures, this research will highlight intensive analysis with the intelligent deep drawing tool

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Section: Design Of the Active Diementioning

confidence: 99%

Section: Design Of the Active Diementioning

confidence: 99%

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Integrated piezoelectric actuators in deep drawing tools

Neugebauer

Mainda

Drossel

et al. 2011

Industrial and Commercial Applications of Smart Structures Technologies 2011

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“…Thus, bending in two stages results in bending at an angle of 90° according to the "tractrix" principle. The idea of an unknown author has been developed and used for bending angles greater than 90° [1,2]. Although the name of the method contains the notion of the "tractrix" curve on the active edge of the punch, the respective curve was not used but only its approximation [1].…”

Section: Introductionmentioning

confidence: 99%

Prediction of technological parameters of sheet metal bending in two stages using feed forward neural network

et al. 2016

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Original scientific paper This paper describes sheet metal bending in two stages as well as predicting and testing of the final bend angle by means of a feed-forward neural network. The primary objective was to research the technological parameters of bending sheet metal in two stages and to develop an intelligent method that would enable the predicting of those technological parameters. The process of bending sheet metal in two stages is presented by demonstrating the various technological parameters and the test tool used to carry out tests and measurements. The results of the tests and measurements were of decisive guidance in the evaluation of individual technological parameters. Developed method for prediction of the final bend angle is based on a feed-forward neural network that receives signals at the input level. These signals then travel through the hidden level to the output level, where the responses to input signals are received. The input to the neural network is composed of data that affect the selection of the final bend angle. Only five different inputs are used for the total neural network. By choosing the desired final bend angle by means of the trained neural network, bending sheet metal in two stages is optimised and made more efficient. Keywords: bending in two stages; intelligent system; neural network; prediction of the final bend angle Predviđanje tehnoloških parametara savijanja lima u dvije faze pomoću usmjerene neuronske mrežeIzvorni znanstveni rad Članak prikazuje savijanje lima u dvije faze i predviđanje konačnog kuta savijanja pomoću usmjerene neuronske mreže. Glavni cilj je bio istražiti tehnološke parametre savijanja lima u dvije faze i razviti inteligentan način, koji će omogućiti predviđanje tih tehnoloških parametara. Prikazan je proces savijanja lima u dvije faze, gdje se prikazuju i razni tehnološki parametri i ispitni alati sa kojima su provedena ispitivanja i mjerenja. Rezultati ispitivanja i mjerenja su bili ključ u donošenju procjene pojedinih tehnoloških parametara. Opisano je predviđanje konačnog kuta savijanja lima korištenjem usmjerene neuronske mreže, koja prima signale na ulazu. Ti signali tada prolaze kroz skrivenu razinu do izlaza, gdje dobiju odgovor na ulazne signale. Za ulaz u neuronsku mrežu upotrebljavaju se podaci koji utječu na odabir kuta konačnog savijanja. Za neuronsku mrežu se koristi pet različitih inputa. Odabirom željenog kuta savijanja pomoću neuronske mreže, može se doprinijeti optimizaciji savijanja lima u dvije faze.Ključne riječi: inteligentni sustav; neuronske mreže; predviđanje konačnoga kuta savijanja; savijanje u dvije faze

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“…Sowohl zum Knickbauchen als auch zum „Fügen durch Knickbauchen“ finden sich lediglich vereinzelte Quellen. Grundlegende Hinweise beispielsweise zur Verfahrensdurchführung sind entsprechenden Literaturstellen zu entnehmen .…”

Section: Introductionunclassified

Ermittlung von Verfahrensgrenzen für das Fügen durch Knickbauchen anhand des Werkstoffes E235+N

Viehweger¹,

Sviridov²,

Grützner³

et al. 2015

Materialwissenschaft Werkst

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Through a systematic approach and the consistent comparison of the results between experimental and numerical investigations, a deep understanding of the bulging mechanisms has been first developed. From these investigations process limitations were derived and presented in the form of a working diagram for the material E235+N. With regard to a wide industrial use of upset bulging as a joining technology, a technologically, productively as well as economically appropriate method could be developed and validated by means of practical and numerical experiments.

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Schnitt-, Stanz- und Ziehwerkzeuge

Cited by 21 publications

References 0 publications

Integrated piezoelectric actuators in deep drawing tools

Integrated piezoelectric actuators in deep drawing tools

Prediction of technological parameters of sheet metal bending in two stages using feed forward neural network

Ermittlung von Verfahrensgrenzen für das Fügen durch Knickbauchen anhand des Werkstoffes E235+N

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