In the present paper Artificial Neural Networks (ANNs) models are proposed for the prediction of surface roughness in Electrical Discharge Machining (EDM). For this purpose two well-known programs, namely Matlab (R) with associated toolboxes, as well as Netlab (R), were employed. Training of the models was performed with data from an extensive series of EDM experiments on steel grades; the proposed models use the pulse current, the pulse duration, and the processed material as input parameters. The reported results indicate that the proposed ANNs models can satisfactorily predict the surface roughness in EDM. Moreover, they can be considered as valuable tools for the process planning for EDMachining.
机构:
Department of Mechanical and Computer-Aided Engineering, St. John’s University, No. 499, Sec. 4, TamKing Rd., Tamsui, New Taipei City,25135, TaiwanDepartment of Mechanical and Computer-Aided Engineering, St. John’s University, No. 499, Sec. 4, TamKing Rd., Tamsui, New Taipei City,25135, Taiwan
Chang, Ming-Kun
Chang, Wen-Jie
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机构:
Department of Mechanical and Computer-Aided Engineering, St. John’s University, No. 499, Sec. 4, TamKing Rd., Tamsui, New Taipei City,25135, TaiwanDepartment of Mechanical and Computer-Aided Engineering, St. John’s University, No. 499, Sec. 4, TamKing Rd., Tamsui, New Taipei City,25135, Taiwan
机构:
Production Technology Department, Faculty of Technology and Education, Helwan University, CairoProduction Technology Department, Faculty of Technology and Education, Helwan University, Cairo