International Journal of Materials Science and Applications
Volume 4, Issue 3, May 2015, Pages: 143-148
Received: Mar. 24, 2015;
Accepted: Apr. 8, 2015;
Published: Apr. 21, 2015
Views 4677 Downloads 216
Gundu David Terfa, Department of Mechanical Engineering, University of Agriculture, Makurdi, Nigeria
Tuleun Livinus Tyovenda, Department of Mechanical Engineering, University of Agriculture, Makurdi, Nigeria
Agber Jonathan Uhaa, Department of Electrical/Electronics Engineering, University of Agriculture, Makurdi, Nigeria
An experimental program was undertaken to extrude a lead alloy on ELECompact-1500 compression machine. Extrusion variables were extrude diameter (d), die bearing length (h), and included die entrant angle Ө = 90o. Using experimental values, numerical models were obtained to describe the relationship between extrusion variables and extrusion pressure and extrude deflection. The numerical models were then used to obtain the response pressure predictions for aluminum alloy. Results of validation tests indicated good correlation between predicted and experimental values. The predictions also compare favorably with values obtained by a similar second-order modified upper bound model frequently used in industry for estimating extrusion loads with prediction errors below 4%. Surface responses graphs of extrusion pressure and extrude deflection were also used to define the optimized field for interaction of extrusion parameters for minimizing extrusion loads and controlling extrudes deflection or bending. Owing to fewer input variables, the proposed models were considered convenient options for a quick estimate of extrusion loads and product curvature.
Gundu David Terfa,
Tuleun Livinus Tyovenda,
Agber Jonathan Uhaa,
Numerical and Response Surface Interactions for Optimizing Extrusion Parameters, International Journal of Materials Science and Applications.
Vol. 4, No. 3,
2015, pp. 143-148.
Chakrabarty, J.. Theory of plasticity. Int. Ed, McGraw-Hill, Inc., Singapore, 1987, 791p.
Dion, G. “Achieving extrusion excellence and increasing profitability through process analysis,” Aluminium Extrusion, 8(2): 30-32, 2003.
Qamar, S.Z., Sheikh, A.K., Arif, A.F.M., Pervez, T., Siddiqui, R.A. “Heat treatment of a hot work die steel,” Archives of Mater. Sci & Eng., 28(8): 503-508. 2007
Harris, C., Li, Q., Jolly, M.R. “Prediction of extruded microstructures using experimental and numerical modeling techniques,” in Aluminium Two Thousand, 5th World Congress, Rome, 31-35. 2003.
Clode, M.P. and Sheppard, T. “Formation of die lines during the extrusion of AA6063,” Mat. Sci. & Tech., 6: 755-763. 1990.
Onuh, S.O., Ekoja, M., Adeyemi, M.B. “Effects of die geometry and extrusion speed on cold extrusion of aluminium and lead alloys,” J. Mater. Proc. Tech., 132: 274-285. 2003.
Kawalek, A., Milenin, A. Dyja, H. (2005). “Analysis of the effect of die shape on the state of strain in the process of extrusion of thin-walled aluminium sections,” Metallurgija, 44(2): 97-101.
T. Gundu, L. Tuleun, O. Injor (2014). “Experimental investigations on the effects of pocket die bearing geometry on extrusion pressure and bending,” American Journal of Mechanical Engineering, 2014, 2(3): 65-69.
Carmai, S.J.J, Pitakthapanaphong, S., Sechjarern (2008). “3D finite element analysis of metal flow in hot aluminium extrusion of T-shaped profile with various offset pockets,” J. Achievements in Mater. and Manuf. Eng., 31(2): 463-468.
Bajimaya, S.M., Park, S.C., Wang, G.N. (2007). “Predicting extrusion process parameters using artificial neural networks,” .Int. J. Mech. Sys. Sci. & Eng. 1(3): 161-165.
Bourqui, B.C., Brunetti, A., Kahenbuhl, Y, S. (2002). “Integration of 3-D finite element flow modeling in extrusion tool conception and fabrication,”. Development Project Report Commission pour la Technologie et l’Innovation, www.m-td .com/101_DD179.pdf.
Narooei, A. and Karimi-Taheri, A. (2010). “A new model for the predicting the strain field and extrusion pressure in ECAE process of circular cross section,” Applied Math. Model. 34: 1901-1917.
Ulysse, P. “Optimal extrusion die design to achieveflow balance,” Int. J. Machine Tools & Manuf., 39: 1049-1064. 1999.
Byon, S.M., Hwang, S.M. “Die shape optimal design in cold and hot extrusion,” J. Mater. Proc. Tech. 138: 316-324. 2003.
Lof, J. “Elasto-viscoplastic FEM simulations of the aluminium flow in the die bearing area for extrusion of thin-walled sections,” J. Mater. Proc. Tech. 114: 174-183. 2001.
Golovko, O., Mamuzic, I., Grydin, O. (2006). “Method for pocket die design on the basis of numerical investigations of aluminium extrusion process,” Metallurgija 45(3): 155-161.
Noorani, A.M., Bakshi, J.M., Hosseinipour, S.J., Gorji, A. (2005). “Experimental and numerical study of optimal die profile in cold forward rod extrusion of aluminium,” J. Mater. Proc. Tech. 164-165: 1623-1632.
Yan, H. and Xia, J. (2006). “An approach to the optimal design of technological parameters in the profile extrusion process,” Sci. & Tech. Adv. Mater. 7:127-131.
Draganescu, F., Draganescu, B., Iliescu, M. (2002). “Statistic modeling of the maximum and average force coefficient in punching,” Poly. Univ. Lasi Bulletin, 37-40.
Sahoo, A.K., Rout, A.K. (2009). “Investigation of optimal parametric combination for minimum cutting force in turning: response surface methodology approach,” J. Eng. Innovation Res. 1: 6-13.
Tiernan, P., Draganescu, B., Hillery, M.T., (2005). “Modeling of extrusion force using the surface response method,” Int. J. Manuf. Tech. 27: 48-52.
Jurkovic, Z., Jurkovic, M., Buljan, S. (2006). “Optimization of extrusion force prediction model using different techniques,” J. Achieve. Mater. Manuf. Eng. 17:353-356.
Gundu, D.T. “Investigations and numerical modeling of material flow in forward extrusion using pocket die bearings,” Doctoral dissertation, University of Agriculture, Makurdi-Nigeria, 2010.
Haghadadi, N., Zarei-Hanzaki, A., Khalesian, A.R., and Abedi, H.R. (2013). “Artificial neural modeling to predict the hot deformation behavior of an A356 aluminium alloy,” Materials & Design.49: 386.
Mohanty, S., Madan Kjha, Ashawani K., Panda D.K. (2013). “Comparative evaluation of numerical model and artificial neural network for simulating groundwater flow in Kathajodi-Surua inter-basin of Odisha,” Indian J. Hydrology, 495: 38-51.