NAME Optimizing cutting conditions in the machining process

Optimization of cutting conditions in machining processes using Reinforcement Learning (RL) algorithms as a strategy to improve machining performance through the dynamic adaptation of parameters such as cutting speed, depth of cut, feed rate, and cutting force. The main objective is to maximize process efficiency, minimize tool wear, and improve the quality of machined parts, all while reducing costs and energy consumption.