Numerical modeling of machining processes exhibits a high potential for shortening process development times. When modeling the machining process, an accurate material model is essential for the success and reliability of the simulated results. Especially, the simulation results depend largely on the material model and on the material parameters. To identify the parameters for machining conditions, inverse methods are used, where results from simulations are matched iteratively with those obtained experimentally. This procedure is, however, time-consuming and a large number of iterations is needed. This paper presents a new methodology for the inverse identification of material parameters by an optimization algorithm.
Science Journal 