Neural Network Modeling and Analysis for Surface Characteristics in Electrical Discharge Machining

• Main Authors: Khan, Md. Ashikur Rahman, M. M., Rahman, K., Kadirgama
• Format: Article
• Language: English
• Published: Elsevier Ltd 2014
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/8185/1/Neural_Network_Modeling_and_Analysis_for_Surface_Characteristics_in_Electrical_Discharge_Machining.pdf; http://umpir.ump.edu.my/id/eprint/8185/; http://dx.doi.org/10.1016/j.proeng.2014.11.783

The problem appeared owing to selection of parameters increases the deficiency of electrical discharge machining (EDM) process. Modelling can facilitate the acquisition of a better understanding of such complex process, save the machining time and make the process economic. Thus, the present work emphasizes the development of an artificial neural network (ANN) model for predicting the surface roughness (Ra). Training and testing are done with data that are found succeeding the experiment as design of experiments. The surface topography of the machined part was analysed by scanning electronic microscopy. The result shows that the ANN model can predict the surface roughness effectively. Low discharge energy level results in smaller craters and micro-cracks producing a suitable structure of the surface. This approach helps in economic EDM machining.