This work,examines the Surface Roughness(SR)of composite consisting Aluminium alloy(AA6061),Magnesium and Rock dust during turning process.To study the performance,three different test specimens with different constit...This work,examines the Surface Roughness(SR)of composite consisting Aluminium alloy(AA6061),Magnesium and Rock dust during turning process.To study the performance,three different test specimens with different constituents of Al 6061-T6,AZ31 and Rock dust were prepared by stir casting method.Turning experiments were carried out using MTAB Siemens-CNC lathe.The input parameters for machining are speed,depth of cut&feed and output response is surface roughness For each test specimen,there are 15 turning operations were performed using Box-Ben hen Design approach.To analyze the process parameters for SR,the models of ANOVA and Decision Tree(DT)algorithms were performed.Both algorithms are confirmed that,speed is the most significant factor for SR.The addition of AZ 31 with 1%and rock dust of 2%in AA6061 produced better surface finish.Regression models of linear regression,multilayer perception and support vector regression from data science were formulated to find the relationship between variables.Among these models multi layer perception produced minimum root mean square error.展开更多
文摘This work,examines the Surface Roughness(SR)of composite consisting Aluminium alloy(AA6061),Magnesium and Rock dust during turning process.To study the performance,three different test specimens with different constituents of Al 6061-T6,AZ31 and Rock dust were prepared by stir casting method.Turning experiments were carried out using MTAB Siemens-CNC lathe.The input parameters for machining are speed,depth of cut&feed and output response is surface roughness For each test specimen,there are 15 turning operations were performed using Box-Ben hen Design approach.To analyze the process parameters for SR,the models of ANOVA and Decision Tree(DT)algorithms were performed.Both algorithms are confirmed that,speed is the most significant factor for SR.The addition of AZ 31 with 1%and rock dust of 2%in AA6061 produced better surface finish.Regression models of linear regression,multilayer perception and support vector regression from data science were formulated to find the relationship between variables.Among these models multi layer perception produced minimum root mean square error.
