期刊名称：Majalah Iptek = IPTEK : The Journal for Technology and Science
印刷版ISSN：0853-4098
电子版ISSN：2088-2033
出版年度：2014
卷号：25
期号：3
DOI：10.12962/j20882033.v25i3.527
语种：English
出版社：IPTEK
摘要：This study attempts to model and optimize the complicated electrical discharge machining (EDM) process using soft computing techniques. Artificial neural network (ANN) with back propagation algorithm is used to model the process. In this study, the machining parameters, namely pulse current, on time, off time and gap voltage are optimized with considerations of multiple performance characteristics such as metal removal rate (MRR) and surface roughness. As the output parameters are conflicting in nature so there is no single combination of cutting parameters, which provides the best machining performance. Genetic algorithm (GA) with properly defined objective functions was then adapted to the neural network to determine the optimal multiple performance characteristics.
