Accuracy and reliability of the numerical results is one of the most important challenges in the scientific community for finite element modeling (FEM) of cutting processes. It becomes more essential in machining of difficult-to-cut materials such as nickel-based alloys where high thermo-mechanical loads are induced into the workpiece. In this paper, new strategies were adopted to improve accuracy of FE modeling of cutting process of Inconel718 superalloy. Firstly, a novel hybrid strategy was established to simultaneously calibrate controllable simulation parameters. It was implemented based on the design of experiment, intelligent systems and FEM of cutting process. Using validation with experimental results, a great improvement was obtained for prediction of cutting forces, maximum temperature, and chip geometry compared with numerical results obtained previously by conventional calibration procedure. At the second stage of the paper, a grain size-based flow stress was developed by implementation of advanced FORTRAN user-subroutine in FE code to take into account the effect of changes in material properties during the chip formation. According to the results, implementation of grain size based flow stress has a significant effect on enhancement of simulation accuracy. Finally, it can be concluded that, the innovated strategies presented in this paper provide fundamental and useful approaches to improve precision in modeling of other manufacturing processes.
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