A Systematic Approach for Identifying Turning Center Capabilities with Vertical Machining Center in Milling Operation

Authors: J. Chen, N. Hundal

Abstract:

Conventional machining is a form of subtractive manufacturing, in which a collection of material-working processes utilizing power-driven machine tools are used to remove undesired material to achieve a desired geometry. This paper presents an approach for comparison between turning center and vertical machining center by optimization of cutting parameters at cylindrical workpieces leading to minimum surface roughness by using taguchi methodology. Aluminum alloy was taken to conduct experiments due to its unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. During testing, the effects of the cutting parameters on the surface roughness were investigated. Additionally, by using taguchi methodology for each of the cutting parameters (spindle speed, depth of cut, insert diameter, and feed rate) minimum surface roughness for the process of turn-milling was determined according to the cutting parameters. A confirmation experiment demonstrates the effectiveness of taguchi method.

Keywords: Surface roughness, taguchi parameter design, turning center, turn-milling operations, vertical machining center.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1092405

References:

[1] Information about Machining - Retrieved from http://en.wikipedia.org/wiki/Machining
[2] M.C. Shaw, P.A. Smith, N.H. Cook, The rotary cutting tool, Trans. ASME 74 (1952) 1065–1076
[3] Information about Turn-Milling technique - Retrieved from http://www.mmsonline.com/articles/applying-turn-milling
[4] CNC Programming: Principles and Applications (2009)By Michael W. Mattson, Mike Mattson, page 295
[5] J.T.Black, Ronald A. Kohser, Materials and processes in manufacturing, Eleventh edition: 665-673
[6] R. K Rajput, (2008) A Textbook of Manufacturing Technology: (manufacturing Processes), p 6
[7] D. Baji}, B. Lela, D. @ivkovi}, Modeling of machined surface roughness and optimization of cutting parameters in face milling, Metallurgy 47(2008) 4, 331-334.
[8] J. Z. Zhang, J. C. Chen, J. D. Kirby, Surface roughness optimization in an end-milling operation using Taguchi design method, Journal of Material Processing Technology, 184(2007), 233-239.
[9] T. Ozel, Y. Karpat, Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks, International Journal of Machine Tool and Manufacture 45(2005), 467-479.
[10] D. Baji, B. Lela, G. Cukor, Examination and modeling of the influence of cutting parameters on the cutting force and the surface roughness in longitudinal turning, Strojni{ki vestnik, Journal of mechanical engineering 54(2008) 5,322-333
[11] Phadke M.S. 1989, Quality engineering using robust design, Englewood Cliffs, NJ: Prentice-Hall.
[12] Antony, J & Kaye, M., (1999), Experimental quality –A Strategic approach to achieve and improve quality, Norwell, Massachusetts, Kluwer Academic Publishers.
[13] Cesarone, J. (2001). The Power of Taguchi: You've Heard of Design of Experiments and Taguchi Methods; Now Understand When It's Appropriate to Use Each Method. IIE Solutions, 33(11), 36-40.
[14] Ross P.J. 1996. Taguchi techniques for quality engineering: loss function, orthogonal experiments, parameter and tolerance design. 2nd Ed. New York, NY: McGraw-Hill.
[15] J.Z. Zhang, J. C. Chen, E. D. Kirby, Jacob Chen, Optimizing Surface finish in a turning operation using Taguchi parameter design method, Int J Adv Manuf Technol, (2006) 30: 1021-1029
[16] Ghani JA, Choudhury IA, Hassan HH (2004) Application of Taguchi method in the optimization of end milling parameters. J Mater Process Technol 145:84–92
[17] Montgomery, D C., (1997), Design and analysis of experiments (4th Ed.), New York, John Wiley & Sons.
[18] Taguchi, G. and Konishi, S. (1987), Orthogonal Arrays and Linear Graphs, ASI Press, Dearborn, MI.
[19] Torng, C. C., Chou, C. Y. & Liu, H. R., (1998), "Applying quality engineering technique to improve wastewater treatment”, National journal of Industrial Technology, 15(1), p.353-357
[20] Fowlkes, W. Y., & Creveling, C. M. (1995). Engineering Methods for Robust Product Design: Using Taguchi Methods in Technology and Product Development. Reading, MA: Addison-Wesley Publishing Company
[21] Ghani, A.K., I.A. Choudhury, Husni, "Study of Tool Life, Surface Roughness and Vibration in Machining Nodular Cast Iron with Ceramic Tool,” Journal of Materials Processing Technology, vol. 127, pp. 17-22, 2002
[22] Samanta, B., "Surface Roughness Prediction in Machining Using Soft Computing,” International Journal of Computer Integrated Manufacturing, vol. 22, no. 3, pp. 257-266, March 2009.
[23] Kadirgama, K., M.M. Noor, N.M. Zuki N.M., M.M. Rahman, M.R.M. Rejab, R. Daud, K.A. Abou-El- Hossein, "Surface Roughness Prediction Model of 6061-T6 Aluminum Alloy Machining Using Statistical Method,” European Journal of Scientific Research, vol. 25, no. 2, pp. 250-256, 2009.
[24] Mike S. Lou, Joseph C. Chen, Caleb M. Li, "Surface Roughness Prediction Technique for CNC End- Milling,” Journal of Industrial Technology, vol. 15, no. 1, Nov. 1998.
[25] Abdullah, A.B., L.Y. Chia, Z. Samad, "The Effect of Feed Rate and Cutting Speed to Surface Roughness,”Asian Journal of Scientific Research, vol. 1, no.1, pp. 12-21, 2008.
[26] Information about CNC turning center - Retrieved from http://www.haascnc.com/mt_spec1.asp?id=ST-20&webID=2AXIS_STD_LATHE
[27] Information about CNC vertical machiningcenter - Retrieved from http://www.haascnc.com/mt_spec1.asp?id=VF-2TR&webID=5AXIS_VMC
[28] Babus'Haq, R. F., Probert, D., Snaith, B., O'Callaghan, P. W., & George, H. E. (1990). Perceived and Real Roughness Variations Across Machined Surfaces. International Journal of Materials and Product Technology, 5(1), 12-24.