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IJSTR >> Volume 8 - Issue 10, October 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Modeling And Analysis Of Turning Process On Lathe Machine By Taguchi And Anova Approach

[Full Text]



Manoj Modi, Gopal Agarwal, V.Patil, Ashish Khare, Saloni Shukla, Advitiya Sankhala



Speed, Feed, Depth of Cut, Taguchi, ANOVA, and MRR.



In the today’s competitive era, it is very important to an edge over the others to survive and flourish. One of the easiest yet most complicated areas to expertise is ‘fast delivery’ and to obtain that the cycle time has to be reduced. Keeping this in mind certain investigations are carried out to increase the material removal rate. This research work explains the effects of certain lathe parameters namely Speed, Feed and Depth of Cut on the output parameter Material Removal Rate. A mild steel test piece is taken and different experiments are conducted on it by a nine foot conventional lathe machine by changing the input parameters using Taguchi methodology. Taguchi method is used to formulate the experimental layout. A Taguchi L9 design of experiment (DOE) and the analysis of variance (ANOVA) is applied to analyze the effect of each parameter on the response. Mathematical formula is also developed among the Speed, Feed and Depth of Cut and MRR. It will be found that these parameters have a significant influence on machining characteristic metal removal rate.



[1] Dragomir, C., & Surugiu, F. Implementing Lean in a Higher Education University. Constanta Maritime University's Annals, 18 , pp.279–282, 2013.
[2] Muammer Nalbant, H. Gökkaya, Gökhan Sur, Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning, Materials and Design December 2007, 28(4):1379-1385.
[3] Yang WH, Tarng YS (1998) Design optimisation of cutting parameters for turning operations based on Taguchi method. J Mater Process Technol 84:122–129.
[4] E. Daniel Kirby, Zhe Zhang, Joseph C. Chen, Jacob Chen, Optimizing surface finish in a turning operation using the Taguchi parameter design method
[5] Feng C-X, Wang X-F (2003) Surface roughness predictive modeling: neural networks versus regression. IIE Trans 35:11–27.
[6] Davim JP (2001) A note on the determination of optimal cutting conditions on the surface finish obtained in turning using design experiments. J Mater Process Technol 116(2/3):305–308
[7] Kopac J, Bahor M, SokoviC M (2002) Optimal machining parameters for achieving the desired surface roughness in fine turning of cold pre-formed steel workpieces. Int J Mach Tools Manuf 42(6):707–716.