Effective Optimization Based on Equilibrium Optimizer for Dynamic Cutting Force Coefficients of the End-Milling Process

This study aims to develop an accurate dynamic cutting force model in the milling process. In proposed model, estimated tackles effect of self-excited vibration that causes machining instability during particular, square root residual between prediction and actual is considered as objective function for optimizing coefficients using equilibrium optimizer (EO) approach instead trial-and-error approach. The results confirm can provide higher accuracy when EO applied. addition, has a minimum integral error (ISE) around 1.12, while genetic algorithm (GA) ISE 1.14 method 2.4. Moreover, help investigate stability suspend chatter phenomenon by selecting optimal set parameters.