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Validation of Automatically Generated Forging Sequences by Using FE Simulations

Conference paper
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Part of the The Minerals, Metals & Materials Series book series (MMMS)

Abstract

To increase the economic efficiency in the production of geometrically complicated forgings, material efficiency is a determining factor. In this study, a method is being validated to automatically design a multi-staged forging sequence initially based on the CAD file of the forging. The method is intended to generate material-efficient forging sequences and reduce development time and dependence on reference processes in the design of forging sequences. Artificial neural networks are used to analyze the geometry of the forging and classify it into a shape class. Result of the analysis is information on component characteristics, such as bending and holes. From this, special operations such as a bending process in the forging sequence can be derived. A slicer algorithm is used to divide the CAD file of the forging into cutting planes and calculate the mass distribution around the center of gravity line of the forging. An algorithm approaches the mass distribution and cross-sectional contour step by step from the forging to the semi-finished product. Each intermediate form is exported as a CAD file. The algorithm takes less than 10 min to design a four-stage forging sequence. The designed forging sequences are checked by FE simulations. Quality criteria that are evaluated and investigated are form filling and folds. First FE simulations show that the automatically generated forging sequences allow the production of different forgings. In an iterative adaptation process, the results of the FE simulations are used to adjust the method to ensure material-efficient and process-reliable forging sequences.

Keywords

Automatic process design Forging FEA Resource efficiency CAD 

Notes

Acknowledgments

The research project “Design of efficient forging sequences with mass distribution around the center of gravity line for forging parts” (IGF project 19752) has been funded by the German Federation of Industrial Research Associations (AiF). The authors thank the AiF for its support.

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Copyright information

© The Minerals, Metals & Materials Society 2021

Authors and Affiliations

  1. 1.IPH-Institut Für Integrierte Produktion Hannover gGmbHHannoverGermany

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