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  • 标题:Multi-regression prediction model for surface roughness and tool wear in turning novel aluminum alloy (LM6)/fly ash composite using response surface and central composite design methodology
  • 本地全文:下载
  • 作者:Panda, S. ; Panda, S. ; Senapati, A.
  • 期刊名称:International Journal of Industrial Engineering Computations
  • 印刷版ISSN:1923-2926
  • 电子版ISSN:1923-2934
  • 出版年度:2017
  • 卷号:8
  • 期号:1
  • 页码:1-18
  • DOI:10.5267/j.ijiec.2016.8.001
  • 语种:English
  • 出版社:Growing Science Publishing Company
  • 摘要:Turning experiments were conducted on a novel aluminum alloy (LM6)/fly ash composite based on the response surface and face centered central composite design methodology. The effects of cutting parameters on surface roughness and tool wear were investigated. Multiple regression models were developed for the responses and the adequacies of the developed models were tested at 95% confidence interval using the analysis of variance (ANOVA) technique. Carbide inserts (Model: CNMG 120408-M5) were used for turning the specimens in a CNC turning machine (model: LT-16). The test for significance of the regression models, the test for significance on individual model coefficients and the lack-of-fit tests were performed using the statistical Design-Expert7.0v software environments. R2 indicated the model significance and the value was more than 97%, revealed that the relation between cutting responses and input parameters held good for more than 97% and the model was adequate.
  • 关键词:Aluminum alloy matrix; Fly ash; Turning; Response surface method; Central composite design
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