The Prediction of Surface Temperature in Drilling of Ti6Al4V

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Abstract

Titanium and its alloys are attractive materials due to their unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. The major application of titanium has been in the aerospace industry. However, the focus shift of market trends from military to commercial and aerospace to industry also been reported. On the other hand, titanium and its alloys are notorious for their poor thermal properties and are classified as difficult-to-machine materials. These properties limit the use of these materials especially in the markets where cost is much more of a factor than in aerospace. Machining is an important manufacturing process because it is almost always involved if precision is required and is the most effective process for small volume production. Due to the low machinability of the alloys under study, selecting the machining conditions and parameters is crucial. The range of feeds and cutting speeds, which provide a satisfactory tool life, is very limited. On the other hand, adequate tool, coating, geometry and cutting flow materials should be used: otherwise, the high wear of the tool, and the possible tolerance errors, would introduce unacceptable flaws in parts that require a high degree of precision.

In this study, heat changes of Ti6Al4V has been examined on the basis of cutting parameters such as depth of cut, feedrate and cutting speed during drilling. Heat changes of the material and tool was monitored by a thermal camera. Maximum temperatures of the experiments were taken to examine optimum cutting parameters. Obtained results have been used to generate a regression analysis and it is seen that regression has given accurate data.

[1] A.R. Zareena, M. Rahman, Y.S. Wong, High Speed Machining Of Aerospace Alloy Ti-6Al-4V, 33rd ISTC - Seattle, WA - November 5 - 8, 2001.

[2] R.R. Boyer, An overview on the use of titanium in the aerospace industry, Mater Sci Eng A 213(1-2), 103-114 (1996).

[3] E.O. Ezugwu, J. Bonney, Y. Yamane, An overview of the machinability of aeroengine alloys, J Mater Process Technol 134(2), 233-253 (2003).

[4] S. Sun, M. Brandt, M.S. Dargusch, Characteristics of cutting forces and chip formation in machining of titanium alloys, Int J Mach Tool Manuf 49(7-8), 561-568 (2009).

[5] J. Barry, G. Byrne, D. Lennon, Observations on chip formation and acoustic emission in machining Ti-6Al-4Valloy. Int J Mach Tool Manuf 41(7), 1055-1070 (2001).

[6] Rajiv Shivpuri, Advances In Numerical Modeling Of Manufacturing Processes: Application To Steel, Aerospace And Automotive Industries, Trans. Indian Inst. Met. 57, 4, 345-366 (2004).

[7] A. Modgil, Effects Of High Speed Machining On Surface Topography Of Titanium Alloy (Ti-6Al-4V), A Master Thesis, University of Florida (2003).

[8] E.O. Ezugwu, Z.M. Wang, Titanium alloys and their machinability-Areview, Journal of Materials Processing Technology 68, 262-274 (1997).

[9] E.O. Ezugwu, J. Bonney, Y. Yamane, An overview of the machinability of aeroengine alloys, Journal of Materials Processing Technology 134, 233-253 (2003).

[10] P.S. Sreejith, B.K.A. Ngoi, Dry machining: Machining of the future, Journal of Materials Processing Technology 101, 287-291 (2000).

[11] P.A. Dearnley, A.N. Grearson, Evaluation of principal wear mechanism of cemented carbides and ceramics used for machining titanium alloys IMI 318, Material Sciences and Technology 2, 47-58 (1986).

[12] J.L. Cantero, M.M. Tardıo, J.A. Canteli, M. Marcos, M.H. Miguelez, Dry drilling of alloy Ti-6Al-4V, International Journal of Machine Tools & Manufacture 45, 1246-1255 (2005).

[13] R.P. Zeilmann, W.L. Weingaertner, Analysis of temperature during drilling of Ti6Al4Vwith minimal quantity of lubricant, Journal of Materials Processing Technology 179, 124-127 (2006).

[14] L. Reissig, R. Volkl, M.J. Mills, U. Glatzel, Investigation of near surface structure in order to determine process-temperatures during different machining processes of Ti6Al4V, Scripta Materialia 50, 121-126 (2004).

[15] Bouzakis K-D, Michailidis N, Gerardis S, Katirtzoglou G, Lili E, Pappa M, Brizuela M, Garcia - Luis A, R. Cremer, Correlation of the impact resistance of variously doped CrAlN PVDcoatings with their cutting performance in milling aerospace alloys, Surf Coat Technol 203(5-7), 781-785 (2008).

[16] G. Krishna Mohana Rao, G. Rangajanard- haa, D. Hanumantha Rao, M. Sreenivasa Rao, Development of hybrid model and optimization of surface roughness in electric discharge machining using artificial neural networks and genetic algorithm, Journal of Materials Processing Technology 209, 3, 1512-1520 (2009).

[17] G. Casalino, F. Curcio, F. Memola Capece Minutolo, Investigation on Ti6Al4 Vlaser welding using statistical and Taguchi approaches, Journal of Materials Processing Technology 167, 2-3, 422-428 (2005).

[18] Weixin Yu, M.Q. Li, Jiao Luo, Shaobo Su, Changqing Li, Weixin Yu, Prediction of the mechanical properties of the post-forged Ti-6Al-4 Valloy using fuzzy neural network, Materials & Design 31, 7, 3282-3288 (2010).

[19] N.S. Reddy, You Hwan Lee, Chan Hee Park, Chong Soo Lee, N.S. Reddy, Prediction of flow stress in Ti-6Al-4V alloy with an equiaxed α + β microstructure by artificial neural Networks, Materials Science & Engineering: A 492, (1-2), 276-282 (2008).

[20] G. Sathyanarayanan, I.J. Lin, M. Chen, Neural network modelling and multiobjective optimization of creep feed grinding of superalloys, International Journal of Production Research 30(10), 2421-2438 (1992).

[21] P.V. Yee, S. Haykin, Regularized Radial Basis Function Networks: Theory and Applications, John Wiley, 18-24 (2001).

Archives of Metallurgy and Materials

The Journal of Institute of Metallurgy and Materials Science and Commitee on Metallurgy of Polish Academy of Sciences

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