Simulation of the round insert face milling process of AISI 316LN stainless steel with machining-based plastic behavior modeling

Abstract

A proper plastic behavioral model is required to simulate metal cutting. Here, we model the plastic behavior of AISI 316LN stainless steel during face milling. We used a numerical approach to derive a plasticity model appropriate for machining; a two-dimensional cutting force prediction and a genetic algorithm were conducted for that. The force prediction was performed considering a geometrical relationship between the work material and cutting tool. We used the Johnson-Cook (JC) constitutive material model, and initial model parameters were obtained via tension testing at low strain rates (0.001–1 s−1). The genetic algorithm optimized the model parameters; the predictive accuracy with respect to cutting force was high in the model with optimized parameters. We used the optimized JC model for finite element analysis and simulated face milling with a round insert. We measured the cutting forces to validate our modeling approach; the simulated and measured principal forces were in good agreement (error rate ≤ 3.9% under all machining conditions). Our model improved the accuracy of plastic behavior prediction by 93.0% versus the original model. The high accuracy was retained even when the machining environment changed.