Optimization of wire electrical discharge machining of pure tungsten using neural network and response surface methodologyg

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Volumn 225, Issue 6, 2011, Pages 841-852

  Tzeng, C J ^a   Yang, Y K ^a   Hsieh, M H ^a   Jeng, M C ^b  

^a MINGHSIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b NATIONAL CENTRAL UNIVERSITY   (Taiwan)

Author keywords

Genetic algorithm; Neural network; Optimization; Pure tungsten; Response surface methodology; Wire electrical discharge machining

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; EFFECTIVE TOOL; HYBRID METHOD; MATERIAL REMOVAL RATE; OPTIMAL PARAMETER SETTINGS; OPTIMAL SETTING; ORTHOGONAL ARRAY; PROCESS PARAMETERS; PROCESSING CONDITION; PURE TUNGSTEN; RESPONSE SURFACE; RESPONSE SURFACE METHODOLOGY; SURFACE FINISHES; TAGUCHI; WIRE ELECTRICAL DISCHARGE MACHINING; WORK PIECES;

BACKPROPAGATION ALGORITHMS; ELECTRIC DISCHARGE MACHINING; ELECTRIC DISCHARGES; GENETIC ALGORITHMS; OPTIMIZATION; STRIPPING (REMOVAL); SURFACE PROPERTIES; SURFACES; TUNGSTEN; WIRE;

NEURAL NETWORKS;

EID: 80051915664     PISSN: 09544054     EISSN: 20412975     Source Type: Journal    
DOI: 10.1243/09544054JEM2021     Document Type: Article

References (28)

1. PLANSEE High Performance Materials. Tungsten and its alloys, 2010, available from http://www.plansee.com/ tungsten.htm
2. Huang, C. A., Shih, C. L., Li, K. C., and Chang, Y. Z. The surface alloying behavior of martensitic stainless steel cut with wire electrical discharge machine. Appl. Surf. Sci., 2006, 252(8), 2915-2926. (Pubitemid 43132779)
3. Sarkar, S., Sekh, M., Mitra, S., and Bhattacharyya, B. Modeling and optimization of wire electrical discharge machining of ? -TiAl in trim cutting operation. J. Mater. Process. Technol., 2008, 205(1-3), 376-387.
4. Bamberg, E. and Rakwal, D. Experimental investigation of wire electrical discharge machining of gallium-doped germanium. J. Mater. Process. Technol., 2008, 197(1-3), 419-427. (Pubitemid 350251169)
5. Rakwal, D. and Bamberg, E. Slicing, cleaning and kerf analysis of germanium wafers machined by wire electrical discharge machining. J. Mater. Process. Technol., 2009, 209(8), 3740-3751.
6. Liao, Y. S., Huang, J. T., and Su, H. C. A study on the machining parameters optimization of the wire electrical discharge machining. J. Mater. Process. Technol., 1997, 71(3), 487-493. (Pubitemid 127379862)
7. Kuriakose, S., Mohan, K., and Shunmugam, M. S. Data mining applied to wire-EDM process. J. Mater. Process. Technol., 2003, 142(1), 182-189.
8. Mahapatra, S. S. and Patnaik, A. Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method. Int. J. Adv. Mfg Technol., 2007, 34(9-10), 911-925. (Pubitemid 47482169)
9. Liu, Y. H., Ji, R. J., Li, X. P., Yu, L. L., and Zhang, H. F. Electric discharge milling of insulating ceramics. Proc. IMechE, Part B: J. Engineering Manufacture, 2008, 222(2), 361-366. DOI: 10.1243/09544054JEM970
10. Rao, R. V. and Pawar, P. J. Modelling and optimization of process parameters of wire electrical discharge machining. Proc. IMechE, Part B: J. Engineering Manufacture, 2009, 223(11), 1367-1506. DOI: 10.1243/09544054JEM1559
11. Yang, Y. K. and Chang, T. C. Experimental analysis and optimization of a photo resist coating process for photolithography in wafer fabrication. Microelectron. J., 2006, 37(8), 746-751.
12. Singh, R. and Khamba, J. S. Macromodel for ultrasonic machining of titanium and its alloys: designed experiments. Proc. IMechE, Part B: J. Engineering Manufacture, 2007, 221(2), 221-229. DOI: 10.1243/09544054JEM593 (Pubitemid 46980693)
13. Lin, C. T., Yang, L. D., and Chow, H. M. Study of magnetic abrasive finishing in free-form surface operations using the Taguchi method. Int. J. Adv. Mfg Technol., 2007, 34(1-2), 122-130.
14. Cao, X., Xiao, M., Jahazi, M., Fournier, J., and Alain, M. Optimization of processing parameters during laser cladding of ZE41A-T5 magnesium alloy castings using Taguchi method. Mater. Mfg Process., 2008, 23(4), 413-418. (Pubitemid 351502898)
15. Kurt, M., Bagci, E., and Kaynak, Y. Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes. Int. J. Adv. Mfg Technol., 2009, 40(5-6), 458-469.
16. Montgomery, D. C. Design and analysis of experiments, edition 6, 2005 (John Wiley and Sons Inc., New York, New York).
17. Kung, K. Y. and Chiang, K. T. Modeling and analysis of machinability evaluation in the wire electrical discharge machining (WEDM) process of aluminum oxide-based ceramic. Mater. Mfg. Process., 2008, 23(4), 241-250.
18. Tzeng, C. J. and Yang, Y. K. Determination of optimal parameters for SKD11 CNC turning process. Mater. Mfg Process., 2008, 23(4), 363-368.
19. Davim, J. P., Gaitonde, V. N., and Karnik, S. R. An investigative study of delamination in drilling of medium density fibre board (MDF) using response surface models. Int. J. Adv. Mfg Technol., 2008, 37(1-2), 49-57. (Pubitemid 351651598)
20. Chuang, M. T., Yang, Y. K., and Hsiao, Y. H. Modeling and optimization of injection molding process parameters for thin-shell plastic parts. Polym. Plast. Technol. Engng, 2009, 48(7), 745-753.
21. Shen, C. Y., Wang, L. X., and Li, Q. Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method. J. Mater. Process. Technol., 2007, 183(2-3), 412-418. (Pubitemid 46209648)
22. Razfar, M. R. and Zanjani Zadeh, M. R. Optimum damage and surface roughness prediction in end milling glass fibre-reinforced plastics, using neural network and genetic algorithm. Proc. IMechE, Part B: J. Engineering Manufacture, 2009, 223(6), 653-664. DOI: 10.1243/09544054JEM1409.
23. Rao, G. K. M., Rangajanardhaa, G., Rao, D. H., and Rao, M. S. Development of hybrid model and optimization of surface roughness in electric discharge machining using artificial neural networks and genetic algorithm. J. Mater. Process. Technol., 2009, 209(3), 1512-1520.
24. Deng, Z. H., Zhang, X. H., Liu, W., and Cao, H. A hybrid model using genetic algorithm and neural network for process parameters optimization in NC camshaft grinding. Int. J. Adv. Mfg Technol., 2009, 45(9), 859-866.
25. Lee, S. H. and Li, X. Study of the effect of machining parameters on the machining characteristics in electrical discharge machining of tungsten carbide. J. Mater. Process. Technol., 2001, 115(3), 334-358.
26. Tasi, K. M. and Wang, P. J. Comparison of neural network models on material removal rate in electrical discharge machining. J. Mater. Process. Technol., 2001, 117(1-2), 111-124.
27. Salonitis, K., Stournaras, A., Stavropoulos, P., and Chryssolouris, G. Thermal modelling of the material removal rate and surface roughness for EDM diesinking. Int. J. Adv. Mfg Technol., 2009, 40(3-4), 316-323.
28. Amri Lajis, M., Mohd Radzim, H. C. D., and Nurul Amin, A. K.M.Theimplementation of TaguchimethodonEDM process of tungsten carbide. Eur. J. Sci. Res., 2009, 26(4), 609-617.