Systematic errors introduced by springback phenomena in metal-sheet stamping ask for part-process adaptations, involving blanks, die features, and process parameters. Springback simulations for a couple of common parts are presented, and the long trials for setting up realistic simulations are pointed out. A data-driven methodology is then suggested, based upon the combined use of FEM and Artificial Neural Networks (ANN) analyses. A test is given for a simple shaped part: starting from a small set of reliable simulated results, an ANN is trained and adopted to retrieve the springback distorted profile for different combinations of parameter values.


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    Title :

    Springback control in stamping car body parts


    Additional title:

    Steuerung des Rückfederns beim Stanzen von Karosserieteilen


    Contributors:
    Maddis, M. De (author) / Basuc, D. (author) / Lombardi, F. (author)


    Publication date :

    2004


    Size :

    6 Seiten, 9 Bilder, 11 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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