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Effective Stochastic Simulation for the Optimization of Time, Costs and Quality in Cold Forging

  • Symposium MS01: Inverse analysis optimization and stochastic approaches
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ABSTRACT

In cold forging tool life is limited in most cases by fatigue and characterized by distinct scatter depending on the scatter of the process parameters. This fact is also obstructing the production of net shape parts. Due to the scatter, a single simulation run with average values is known to be not appropriate to predict the desired output quantities. This paper describes an innovative method using a mathematical model of the forging process with a deterministic and a statistical component. According to the strength versus load concept (SVL-concept), a combination of the parametric and the statistical model leads to an integrated statistical process model which enables tool life prediction by taking statistical effects into account. In order to improve tool life an approach of avoiding tensile stresses and strains in the die has been successfully used for steel and cemented carbide tools.

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REFERENCES

  1. Engel, U.: Strength vs Load - A General Concept to Estimate and to Improve the Reliability of Tools in Bulk Metal Forming. In: Kuzman, K.; Bali, J. (Eds.): ICIT’97 Conf. Proc. Vol. I, Slovenia: Celje 1997, 43–50

  2. Geiger, M.; Engel, U.; Völkl, R.: FE-Analysis Based Prediction of Tool Life in Cold Forging with the Consideration of Stochastic Process Characteristics. In: Production Engineering 12(2005)1, 111–114

  3. Manson, S.S.: Fatigue. A Complex Subject - Some simple Approximations. In: Exp. Mech, 5(1965), 193–226

  4. Geiger, M.; Hänsel, M.; Rebhan, T.: Improving the Fatigue Resistance of Cold Forging Tools by FESimulation and Computer Aided Die Shape Optimization. In: Journal of Engineering Manufacture, Part B, Proc. of the Institution for Mech. Engineers, 206(1992), 143–150

  5. Falk, B.; Engel, U.; Geiger, M.: Fundamental aspects for the evaluation of the fatigue behaviour of cold forging tools. In: Journal of Materials Processing Technology, 119(2001), 158–164

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Authors and Affiliations

  1. Chair of Manufacturing Technology, University of Erlangen-Nuremberg, Egerlandstr. 11, 91058, Erlangen, Germany

    J. Koch, R. Völkl & U. Engel

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  1. J. Koch
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  2. R. Völkl
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  3. U. Engel
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Correspondence to J. Koch.

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Koch, J., Völkl, R. & Engel, U. Effective Stochastic Simulation for the Optimization of Time, Costs and Quality in Cold Forging. Int J Mater Form 1 (Suppl 1), 9–12 (2008). https://doi.org/10.1007/s12289-008-0059-3

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  • DOI: https://doi.org/10.1007/s12289-008-0059-3

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