Advances in plasticity-based analytical modeling and finite element methods (FEM) based numerical modeling of metal cutting have resulted in capabilities of predicting the physical phenomena in metal cutting such as forces, temperatures, and stresses generated. However, accuracy and reliability of these predictions rely on a work material constitutive model describing the flow stress, at which work material starts to plastically deform. This paper presents a methodology to determine deformation behavior of work materials in high-strain rate metal cutting conditions and utilizes evolutionary computational methods in identifying constitutive model parameters. The Johnson–Cook (JC) constitutive model and cooperative particle swarm optimization (CPSO) method are combined to investigate the effects of high-strain rate dependency, thermal softening and strain rate-temperature coupling on the material flow stress. The methodology is applied in predicting JC constitutive model parameters, and the results are compared with the other solutions. Evolutionary computational algorithms have outperformed the classical data fitting solutions. This methodology can also be extended to other constitutive material models.

In this paper, a predictive thermal and analytical modeling approach for orthogonal cutting process is introduced to conveniently calculate forces, stress, and temperature distributions. The modeling approach is based on the work material constitutive model, which depends on strain, strain rate, and temperature. In thermal modeling, oblique moving band heat source theory is utilized and analytically combined with modified Oxley’s parallel shear zone theory. Normal stress distribution on the tool rake face is modeled as nonuniform with a power-law relationship. Hence, nonuniform heat intensity at the tool-chip interface is obtained from the predicted stress distributions utilizing slip line field analysis of the modified secondary shear zone. Heat sources from shearing in the primary zone and friction at the tool-chip interface are combined, heat partition ratios are determined for temperature equilibrium to obtain temperature distributions depending on cutting conditions. Model validation is performed by comparing some experimental results with the predictions for machining of AISI 1045 steel, AL 6082-T6, and AL 6061-T6 aluminum. Close agreements with the experiments are observed. A set of detailed, analytically computed stress and temperature distributions is presented.