Identification of Material Constitutive Parameters Using Orthogonal Cutting Tests and Genetic Algorithm

Identification of workpiece material constitutive parameters for their application in the simulation of metal cutting process has been a hot research spot for long. This paper proposes a methodology to address this problem using orthogonal cutting tests and Genetic Algorithm (GA). First, an analytical model which calculates the dynamic characteristics occurring in the primary shear zone is introduced; then, orthogonal cutting tests are carried out, to record the following mechanical characteristics with the analytical model: shear stresses, shear strains, strain rates, cutting temperatures; afterwards, GA is employed to obtain the constitutive parameters from these characteristics; at last, the finite element method (FEM) simulations of the cutting tests are performed to evaluate the predictive accuracies of the obtained parameters. In this paper, a Japanese brand steel SCM440H is used as the workpiece material, and the simulation results of its constitutive parameters show good agreements with the experimental data, which renders the feasibility of the proposed methodology.