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.