Optimization of Machining Process Using an Adaptive Modeling and Genetic Algorithms(ll) - Cutting Experiment-

적응모델링과 유전알고리듬을 이용한 절삭공정의 최적화(II) - 절삭실험 -

In this study, we put our object to carry out adaptive modeling of cutting process in turning system, and to find out the optimal cutting conditions to maximize material removal rate under some constraints. We used a back-propagation neural network to model the cutting process adaptively and a genetic algorithm to find out optimal cutting conditions. The experimental results show that a back-propagation neural network could model the cutting process effciently, and optimized cutting conditions for maximizing the material removal rate were obtained through the adaptive process model and genetic algorithms. Therefore, the proposed approach can be applied to the real machining system.