JOHNSON-COOK PARAMETER IDENTIFICATION FOR AISI-304 MACHINING THROUGH NELDER MEAD METHOD

The finite elements method (FEM) represents a useful tool for simulating ma- chining processes, nevertheless numerical models are very sensible to the adopted material model and related constants. The paper reports a novel approach for the identification of the material parameters of the Johnson-Cook (JC) plasticity model, which is currently utilized in modeling material behavior during machining operations thanks to its capa- bility to account for the material sensitivity to strain, strain rate, and temperature. The presented approach is based on the use of the Nelder Mead Method (NMM) to identify both the parameters of the simplified JC model and the friction factor of the Tresca law. NMM is a non-linear heuristic technique that affords to find local minima. Compared to the evolutionary approach typically used in parameter identification, the main benefit of this method consists in the low number of iterations necessary to achieve a good match between the experimental and numerical process outputs. The reference process is the Orthogonal Tube Cutting (OTC) test of AISI 304 thin tubes. Although the AISI 304 is a well-known material and many data are available in literature, its reported JC parameters are characterized by a large dispersion, making necessary to develop a robust parameter identification procedure to have reliable material data to cal- ibrate the numerical model. OTC tests were carried out on an instrumented lathe and their numerical model developed through the commercial FEM software DeformTM 2D v.10.1. The optimization problem was implemented in the language programming Ruby. The comparison between exper- iments and numerical results was made with regard to the cutting force, the tool-chip contact length, and the chip morphology.