inserts using soluble oil-water mixture lubricant under different machining conditions. Firstorder
and second-order cutting force prediction models were developed by using the
experimental data by applying response surface methodology combined with factorial design of
experiments. Analysis of variance (ANOVA) is also employed to check the adequacy of the
developed models. The established equations show that feed rate and depth of cut are the main
influencing factors on the cutting force followed by tool nose radius and cutting velocity. It
increases with increase in the feed rate, depth of cut and tool nose radius but decreases with an
increase in the cutting velocity. The predicted cutting force values of the samples have been
found to lie close to that of the experimentally observed values with 95% confident levels.
Moreover, the surface response counters have been generated from the model equations.
Desirability function is used for single response optimization.
How to cite this paper
Abhang, L & Hameedullah, M. (2011). Statistical modeling of main cutting force produced by wet turning using soluble oil-water mixture lubricant.Management Science Letters , 1(2), 167-180.
Refrences
Abhang L. B. & Hameedullah, M. ( 2009). Development of a Prediction model for Surface Roughness in Finish Turning of Alloy Steel, Mathematical and Computational Models: Recent Trends, Narosa Publishing House, New Delhi, India, 138-143
Alauddin, M. A., Mazid, M. A, EL Bardi, M. A. & Hashmi, M. S. J. (1998). Cutting forces in the end milling of Inconel 718. Materials Process Technology, 77, 153-159.
Bhattacharyya, A. (1996). Metal cutting theory and Practice. New Central Book Agency (P) Ltd. Calcutta, 68-85.
Box GEP, (1978). Statistics for Experiments, John Willy and Sons Inc.USA, 38-46.
Chen, W. Y. (2000). Cutting forces and surface finish when machining medium hardness steel using CBN tools. International Machine Tools and Manufacture, 40, 455-466.
Chandra, M. T. G. Komaraiah, M. Kamala V, Prashanth, J.P. & Bala, K. K. (2000). Condition monitoring of cutting force and power in a turning operation with tool wear, Sixteenth National Convention of Mechanical Engineers and National Seminar on Future Trends in Mechanical Engineering, 546-551.
David, J. P, & Reis, P, (2004). Machinability study on composite (polyetheretherketone reinforced with 30% of glass fiber- peek GF30) using polycrystalline diamond (PCD) and cemented carbide tools (K20). International Journal of Advanced Manufacturing Technology, 23, 412-418.
Gunay, M. H., Korkut, I. Aslan, E. & Seker, U., (2005). Experimental investigation of the effect of cutting tool rake angle on main cutting force. Journal of Material Processing Technology, 166, 44-49.
Kalpakjian, S. (1997). Manufacturing process for Engineering materials, Addison-Wesley, Menlo Park, California, USA, 3rd edition, 467-472
Komanduri R. (1982). Catastrophic shear instability in high speed machining of AISI 4330 steels. Transaction of ASME, Journal of Engineering, 104, 121-128.
Lin, W., Lee, B. & Wu, C. (2001). Modeling the surface roughness and cutting force for turning. Journal of Material Processing Technology, 108, 286-293.
Luo, T. (1998). A neural network approach for force and counter error control in multi-dimensional end milling operations. International Journal of Machine Tools and Manufacture, 38, 1343-1359.
Lo K C., & Chen N S S. (1977). Prediction of tool life in hot machining of alloy steels. International Journal of Production Research, 15, 47-63.
Minitab: Minitab version-15 Document, (2007), www.minitab.com.
Montgomery, D. C. (1991). Introduction to Quality Control, 2nd ed., New York : John Wiley & Sons.
Oraby, S. E. & Hayhurst, D. R. (2004). Tool life determination based on the measurement of wear and tool force ratio variation. Journal of machine Tools and Manufacture, 44, 1261-1269.
Petropoulos, G. I., Ntziantzias, & C Anghel, (2005). A predictive model of cutting force in turning using Taguchi and response surface techniques. First international conference at Athens, 6-9 July,178-186.
Shaw, G. M. C.(1998). Metal cutting principles, Oxford University, Press, London, 219-223.
Sidda Reddy, B, Padmanabhan, G. & Vijay kumar, K, (2008). Surface roughness prediction techniques for CNC turning, Asian Journal of Scientific Research 1(3), 256-264.
Trent, E. M. (1991). Metal cutting, Third Edition, Butterworth-Heinemann, Jordan Hill, 236-248.
Tzeng C-J. & Yang, Y-K. (2008). Determination of optimal parameters for SKD11CNC turning process. Materials and Manufacturing Process, 23:363-368.
Wang, W, Kowloon S. H, & Yang, S. H.(2005). A study on roughness of the micro end milling surface produced by a miniatured machine tool. Journal of Materials Processing Technology, 702-708.
Alauddin, M. A., Mazid, M. A, EL Bardi, M. A. & Hashmi, M. S. J. (1998). Cutting forces in the end milling of Inconel 718. Materials Process Technology, 77, 153-159.
Bhattacharyya, A. (1996). Metal cutting theory and Practice. New Central Book Agency (P) Ltd. Calcutta, 68-85.
Box GEP, (1978). Statistics for Experiments, John Willy and Sons Inc.USA, 38-46.
Chen, W. Y. (2000). Cutting forces and surface finish when machining medium hardness steel using CBN tools. International Machine Tools and Manufacture, 40, 455-466.
Chandra, M. T. G. Komaraiah, M. Kamala V, Prashanth, J.P. & Bala, K. K. (2000). Condition monitoring of cutting force and power in a turning operation with tool wear, Sixteenth National Convention of Mechanical Engineers and National Seminar on Future Trends in Mechanical Engineering, 546-551.
David, J. P, & Reis, P, (2004). Machinability study on composite (polyetheretherketone reinforced with 30% of glass fiber- peek GF30) using polycrystalline diamond (PCD) and cemented carbide tools (K20). International Journal of Advanced Manufacturing Technology, 23, 412-418.
Gunay, M. H., Korkut, I. Aslan, E. & Seker, U., (2005). Experimental investigation of the effect of cutting tool rake angle on main cutting force. Journal of Material Processing Technology, 166, 44-49.
Kalpakjian, S. (1997). Manufacturing process for Engineering materials, Addison-Wesley, Menlo Park, California, USA, 3rd edition, 467-472
Komanduri R. (1982). Catastrophic shear instability in high speed machining of AISI 4330 steels. Transaction of ASME, Journal of Engineering, 104, 121-128.
Lin, W., Lee, B. & Wu, C. (2001). Modeling the surface roughness and cutting force for turning. Journal of Material Processing Technology, 108, 286-293.
Luo, T. (1998). A neural network approach for force and counter error control in multi-dimensional end milling operations. International Journal of Machine Tools and Manufacture, 38, 1343-1359.
Lo K C., & Chen N S S. (1977). Prediction of tool life in hot machining of alloy steels. International Journal of Production Research, 15, 47-63.
Minitab: Minitab version-15 Document, (2007), www.minitab.com.
Montgomery, D. C. (1991). Introduction to Quality Control, 2nd ed., New York : John Wiley & Sons.
Oraby, S. E. & Hayhurst, D. R. (2004). Tool life determination based on the measurement of wear and tool force ratio variation. Journal of machine Tools and Manufacture, 44, 1261-1269.
Petropoulos, G. I., Ntziantzias, & C Anghel, (2005). A predictive model of cutting force in turning using Taguchi and response surface techniques. First international conference at Athens, 6-9 July,178-186.
Shaw, G. M. C.(1998). Metal cutting principles, Oxford University, Press, London, 219-223.
Sidda Reddy, B, Padmanabhan, G. & Vijay kumar, K, (2008). Surface roughness prediction techniques for CNC turning, Asian Journal of Scientific Research 1(3), 256-264.
Trent, E. M. (1991). Metal cutting, Third Edition, Butterworth-Heinemann, Jordan Hill, 236-248.
Tzeng C-J. & Yang, Y-K. (2008). Determination of optimal parameters for SKD11CNC turning process. Materials and Manufacturing Process, 23:363-368.
Wang, W, Kowloon S. H, & Yang, S. H.(2005). A study on roughness of the micro end milling surface produced by a miniatured machine tool. Journal of Materials Processing Technology, 702-708.