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  • 标题:An ANFIS-Based Approach for Predicting the Surface Roughness of Cold Work Tool Steel in WEDM
  • 本地全文:下载
  • 作者:Kemal Alda ; İskender Özkul ; Adnan Akkurt
  • 期刊名称:TEM Journal
  • 印刷版ISSN:2217-8309
  • 电子版ISSN:2217-8333
  • 出版年度:2013
  • 卷号:2
  • 期号:3
  • 页码:234-240
  • 语种:English
  • 出版社:UIKTEN
  • 摘要:Wire electrical discharge machining known as non-traditional machining processes,has a significant role in the manufacturing industry. Conductive materials,which can have intricate and complex forms,can be obtained regardless of hardness. In this study,the surface roughness of Sleipner cold work steel is evaluated under various machining process parameters in the WEDM process. In the experiments the feed rate,current,and pulse on time are used as independent variables. In order to predict the surface roughness,an Adaptive Neuro-Fuzzy Inference system was applied based on experimental data.
  • 关键词:ANFIS;WEDM;cold work tool steel;surface roughness.
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