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  • 标题:Using RSM and GA to Predict Surface Roughness Based on Process Parameters in CNC Turning of AL7075-T6
  • 本地全文:下载
  • 作者:M.Subramanian ; R.Sivaperumal ; M.P.Siva
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2014
  • 期号:ICIET
  • 页码:1280
  • 出版社:S&S Publications
  • 摘要:Surface roughness is a commonindicator of the quality characteristics for machiningprocesses. The machining process is more complex,and therefore, it is very hard to determine the effects ofprocess parameters on surface quality in all turningoperations. The present work deals with the study anddevelopment of a regression model to predict surfaceroughness in terms of geometrical parameter, noseradius of cutting tool TNMG insert and machiningparameters, cutting speed and cutting feed rate formachining AL7075-T6, using Response SurfaceMethodology (RSM). The surface roughness ofmachined surface was measured by Mitutoyo SurftestSJ201. The second order mathematical model in termsof machining parameters was developed for predictingsurface roughness. The adequacy of the model waschecked by employing ANOVA. The direct andinteraction effects were graphically plotted which helpsto study the significance of these parameters on surfaceroughness. An attempt has also been made to optimizethe surface roughness prediction model using GeneticAlgorithm (GA) to optimize the objective function.
  • 关键词:Surface roughness; CNC turning;AL7075-T6; nose radius; Response Surface;Methodology; Genetic algorithm; optimization
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