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Prediction of surface roughness by experimental design methodology in Electrical Discharge Machining (EDM)

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: This work models the Ra parameter as a function of current intensity (I), the electrode material and the work material. The surface is directly related to the average intensity (I) during machining. If the intensity is increased to 25 A, the roughness of the room rises dramatically to 15 microns. Design/methodology/approach: Machining with a copper tool produces a better surface than can be achieved by a graphite tool. Copper tool machining has been performed in an efficient way, eliminating the necessity of a large number of experiments. The statistical processing of the results enabled development of a mathematical model to calculate the machined surface quality according to the parameters of the cut used. Findings: The mathematical model, which precisely determines surface roughness, is a tool for cutting parameters and has been obtained by the experimental design method. It enables a high quality range in analysing experiments and achieving optimal exact values. A relatively small number of designed experiments are required to generate useful information and thus develop the predictive equations for surface roughness. Depending on the surface roughness data provided by the experimental design, a first-order predicting equation has been developed. Practical implications: The experimental design was proposed for predicting the relative importance of various factors (composition of the steels and electrical discharge machining (EDM) processing conditions) to obtain efficient pieces. This model gives detailed information on the effect of parameters of cut on the surface roughness. Originality/value: Experimental data was compared with modelling data to verify the adequacy of the model prediction. As shown in this work, the factor of intensity has the most important influence on the surface roughness.
Rocznik
Strony
150--157
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
  • ENIT, National School of Mechanical Engineering, MA2I, Tunisia
  • ISETN Higher Institute of Technology Studies of Nabeul, Tunisia
autor
  • ENIT, National School of Mechanical Engineering, MA2I, Tunisia
  • Supmeca/LISMMA-Paris, School of Mechanical and Manufacturing Engineering, France
autor
  • Supmeca/LISMMA-Paris, School of Mechanical and Manufacturing Engineering, France
Bibliografia
  • [1] Y. Chen, SM. Mahdivian, Analysis of electro-discharge machining process and its comparison with experiments. Journal of Materials Processing Technology 104/1 (2000) 150-157.
  • [2] S.H. Lee, X.P. Li, Study of the effect of machining parameters on the machining characteristics in electrical discharge machining of tungsten carbide, Journal of Materials Processing Technology 115 (2001) 344-58.
  • [3] S.H. Lee, X.P. Li, Study of the surface integrity of the machined workpiece in the EDM of tungsten carbide. Journal of Materials Processing Technology 139 (2003) 315-321.
  • [4] T. Ghrib, S. Ben Salem, Y. Noureddine, EDM effects on the thermal properties of 36NiCrMo16 steel, Tribology International 42/3 (2009) 391-396.
  • [5] M. Kiyak, O. Cakir, Examination of machining parameters on surface roughness in EDM of tool steel, Journal of Materials Processing Technology 191 (2007) 141-144.
  • [6] W. Tebni, M. Boujelbene, E. Bayraktar, S. Ben Salem, Parametric approach model for determining electrical discharge machining (EDM) conditions: effect of cutting parameters on the surface integrity, The Arabian Journal for Science and Engineering 34/1C (2009) 102-114.
  • [7] S. Shankar, S. Maheshwari, P.C. Pandey, Some investigations into the electric discharge machining of hardened tool steel using different electrode materials, Journal of Materials Processing Technology 149 (2004) 272-277.
  • [8] P.V. Ramarao, M.A. Faruqi, Characteristics of the surfaces obtained in electro-discharge machining, Precision Engineering 4 (1982) 111-113.
  • [9] C.C. Wang, B.H. Yan, H.M. Chow, Y. Suzuki, Cutting austempered ductile iron using an EDM sinker, Journal of Materials Processing Technology 88 (1999) 83-89.
  • [10] H.S. Halkaci, A. Erden, Experimental investigation of surface roughness in electric discharge machining (EDM) in ESDA, Proceedings of the 6th Biennial Conference, Istanbul, 2002, 1-6.
  • [11] Y.H. Guu, H. Hocheng, C.Y. Chou, C.S. Deng, Effect of electrical discharge machining on surface characteristics and machining damage of AISI D2 tool steel, Materials Science and Engineering A 358 (2003) 37-43.
  • [12] C. Cogun, B. Kocabas, A. Ozgedik, Experimental and theoretical investigation of workpiece surface roughness profile in EDM, Journal of Faculty of Engineering Archive 19 (2004) 97-106 (in Turkish).
  • [13] Y. Keskin, H.S. Halkaci, M. Kizil, An experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM), The International Journal of Advanced Manufacturing Technology 28 (2006) 1118-1121.
  • [14] A. Ozgedik, C. Cogun, An experimental investigation of tool wear in electric discharge machining, International Journal of Advanced Manufacturing Techniques 27 (2006) 488-500.
  • [15] L. Turnad, A.K.M. Ginta, A. H. Nurul, Tool life prediction by response surface methodology in end milling titanium alloy Ti-6Al-4V using uncoated WC-Co inserts, European Journal of Scientific Research 28/4 (2009) 533-541.
  • [16] W.G. Cockran, G.M. Cox, Experimental designs, Asia Publishing House, Delhi, 1977.
  • [17] A.B. Puri, B. Bhattacharyya, Modeling and analysis of white layer depth in a wire cut EDM process through response surface methodology, The International Journal of Advanced Manufacturing Technology 25/3-4 (2005) 301-307.
  • [18] L.A. Dobrzański, Synergic effects of the scientific cooperation in the field of materials and manufacturing engineering, Journal of Achievements in Materials and Manufacturing Engineering 15 (2006) 9-20.
  • [19] J. Kopac, High precision machining on high speed machines, Journal of Achievements in Materials and Manufacturing Engineering 24 (2007) 405-412.
  • [20] A. Bhattacharyya, Regression analysis for predicting surface-finish and its application in the determination of optimum machining conditions, Journal of Engineering Industry (1970) 711-714.
  • [21] G.E.P. Box, W.G. Hunter, J.S. Hunger, Statistics for Experimenters: an Introduction to Design. In Data Analysis and Model Building, John Wiley & Sons Inc., New York, 1978.
  • [22] G.P. Petropoulos, Multi-parameter analysis and modelling of engineering surface texture, Journal of Achievements in Materials and Manufacturing Engineering 24/1 (2007) 91-100.
  • [23] H. Singh, R. Garg, Effects of process parameters on material removal rate in WEDM, JAMME, Journal of Achievements in Materials and Manufacturing Engineering 32/1 (2009) 70-74.
  • [24] Montgomery D.C. in Design and Analysis of Experiments (4th ed.), John Wiley & Sons Inc., New York (1997).
  • [25] I. Arbizu Puertas, C.J. Perez Luis, Surface roughness prediction by factorial design of experiments in turning processes, Journal of Materials Processing Technology 143-144 (2003) 390-396.
  • [26] Y. Sahin, A.R. Motorcu, Surface roughness model for machining mild steel with coated carbide tool, Materials Design 26 (2005) 321-326.
  • [27] I.A. Choudhury, M.A. EI-Baradie, Surface roughness prediction in the turning of high-strength steel by factorial design of experiments, Journal of Materials Processing Technology 67 (1997) 55-61.
  • [28] T. Dzitkowski, A. Dymarek, Design and examining sensitivity of machine driving systems with required frequency spectrum, Journal of Achievements in Materials and Manufacturing Engineering 26 (2008) 49-56.
  • [29] A. Buchacz, Dynamical flexibility of torsionally vibrating mechatronic system, Journal of Achievements in Materials and Manufacturing Engineering 26 (2008) 33-40.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-33a944a8-6a97-4988-8725-1ea492f548dd
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