مدلسازی مصنوعی بر روی شبکه عصبی مصنوعی بر روی کامپوزیت تنگستن مس

Tungsten-Copper (W-Cu) composite is a multifunctional material used in electrical and thermal applications. However, the microstructural properties of W-Cu composite make the cutting process more difficult. In this paper, the authors employed Wire Electrical Discharge Machining (WEDM) of W-Cu composite with the intention to model the process using Artificial Neural Network (ANN). This is achieved by performing the experiments according to central composite design approach of response surface methodology, developing the different ANN models for material removal rate and selecting the most appropriate model.Pulse on Time, Pulse off Time, Peak Current, Wire Tension and Spark Gap Set Voltage are considered as the process variables. The predicted results from ANN model are compared with experimental values and have been observed quite satisfactory.