Simulation of cutting force using nonstationary Gaussian process

Cutting force signals exhibit a set of stochastic elements that repeat also in a stochastic manner. In this study, it is shown that nonstationary Gaussian processes (i.e., processes wherein the mean and the standard deviation of a normally distributed variable change with time) are able to model and simulate the stochastic elements of cutting force signals. The effectiveness of the proposed approach is demonstrated by comparing the simulated cutting force signal with real cutting force signal in terms of both frequency spectrum and correlation dimension. As realistic and user-friendly simulation of cutting force signals is needed for better process planning and monitoring of material removal processes, the use of the presented approach will help in this regard.