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  • 标题:A surrogate modelling to predict surface roughness and surface texture when grinding AISI 1042 carbon steel
  • 本地全文:下载
  • 作者:K. Kadirgama ; M. M. Rahman ; A. R. Ismail
  • 期刊名称:Scientific Research and Essays
  • 印刷版ISSN:1992-2248
  • 出版年度:2012
  • 卷号:7
  • 期号:5
  • 页码:598-608
  • DOI:10.5897/SRE11.811
  • 语种:English
  • 出版社:Academic Journals
  • 摘要:The quality of the surface produced during carbon steel is important as it influences the performance of the finished part to a great extent. This paper discusses the optimization of cylindrical grinding when grinding carbon steel (AISI 1042) and effect of three variables (work speed, diameter of workpiece and depth of cut) towards surface roughness with aluminium oxide as grinding wheel. Surrogate modelling was used to minimize the number of experiments and developed mathematical model to predict surface roughness hence optimization of cutting variables was found. This model has been validated by the experimental results of aluminium oxide grinding. Prediction model show that diameter of the workpiece and work speed effect mostly compare with depth of cut. The optimum cutting parameters for minimum Ra are work speed 120 RPM; diameter 18 mm and depth of cut 20 µm. The theoretical analysis yielded values which agree reasonably well with the experimental results.
  • 关键词:Cylindrical grinding; surrogate; AISI 1042; surface roughness
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