Statistically assisted identification of the material and friction parameters for modeling metal cutting processes using the FEA

Biermann, D.1, a; Hess, S.1, b; Tiffe, M.1, c; Wagner, T.1, d; Zabel, A.1, e

Institut für Spanende Fertigung, Technische Universität Dortmund, Baroper Str. 303, 44227 Dortmund

a); b); c); d); e)


In this work, a modern model-based approach for the calibration of a cutting simulation is presented. Based on orthogonal cutting experiments and simulations, the parameter calibration is performed using statistical design-of-experiments techniques. In order to properly consider the complexity of the FEA simulation, nonlinear modeling approaches from the design and analysis of computer experiments are used. The prediction capabilities of a simulation with respect to the cutting parameters feed f and cutting speed vc are integrated using an extended variant of the Kienzle equation. By these means, the sensitivity of the FEA model with respect to its parameters can be evaluated. Moreover, the uncertainty remaining in the parameters of the FEA model can be quantified.


Finite-Element-Analysis, Cutting Force, Parameter Identification, Johnson-Cook, Design and Analysis of Computer Experiments, Multiobjective Optimization, Uncertainty Quantification


In: Proceedings of the 1st International Conference on Thermo-Mechanically Graded Materials, 29.10.-30.10. 2012, Kassel, Germany, Heim, H.-P.; Biermann, D.; Maier, H.J. (Hrsg.), ISBN 978-3-942267-58-8, S. 25-30