Taguchi Method-GONNS integration: Complete procedure covering from experimental design to complex optimization

Expert Systems with Applications

Volumn 38, Issue 5, 2011, Pages 4780-4789

  Tansel, I N ^a   Gulmez S ^b   Demetgul, M ^c   Aykut, S ^d  

^a Florida International University   (United States)

^b KOCAELI UNIVERSITY   (Turkey)

^c MARMARA UNIVERSITY   (Turkey)

^d BITLIS EREN UNIVERSITY   (Turkey)

Author keywords

Cutting forces and surface roughness; Genetic algorithm; GONNS; Neural network; Surface milling; Taguchi technique; Titanium alloy

Indexed keywords

COMPLEX OPTIMIZATION; CUTTING DEPTH; CUTTING FORCES AND SURFACE ROUGHNESS; CUTTING SPEED; EMPIRICAL MODEL; EXPERIMENTAL DATA; EXPERIMENTAL DESIGN; FEED-RATES; GONNS; MANUFACTURING APPLICATIONS; OPTIMAL CONDITIONS; OPTIMAL CUTTING; OPTIMAL OPERATING CONDITIONS; OUTPUT PARAMETERS; PVD COATED INSERT; ROBUST PROCEDURES; SURFACE MILLING; TAGUCHI TECHNIQUE; TEST CONDITION; TI-6AL-4V;

ALLOYS; ESTIMATION; GENETIC ALGORITHMS; METAL ANALYSIS; MILLING (MACHINING); NEURAL NETWORKS; OPTIMIZATION; STATISTICS; SURFACE PROPERTIES; TAGUCHI METHODS; TITANIUM; TITANIUM ALLOYS;

SURFACE ROUGHNESS;

EID: 79151486175     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.09.170     Document Type: Article

References (53)

1. Y. Altinta Manufacturing automation 2000 Cambridge University Press USA (pp. 5-6)
2. I.P. Arbizu, and C.J.L. Pérez Surface roughness prediction by factorial design of experiments in turning processes Journal of Materials Processing Technology 2003 390 396
3. P.J. Arrazolaa, A. Garaya, L.M. Iriarte, M. Armendiaa, S. Maryab, and F. Le Maîtrec Machinability of titanium alloys (Ti6Al4V and Ti555.3) Journal of Materials Processing Technology 209 5 2009 2223 2230
4. Aykut, S. (2005). The investigation of effects of machinability on chip removal parameters for face milling of cobalt-based superalloy steels. PhD thesis, Marmara University Institute of Science and Technology, Istanbul, Turkey.
5. S. Aykut, M. Demetgul, and I.N. Tansel Selection of optimum cutting condition of cobalt based alloy with GONN Journal of Advanced Manufacturing 46 2010 957 967
6. R. Azouzi, and M. Guillot On-line prediction of surface finish and dimensional deviation in turning using neural network based sensor fusion International Journal of Machine Tools and Manufacture 37 9 1997 1201 1217
7. K. Baek, T.J. Ko, and H.S. Kim Optimization of feedrate in a face milling operation using a surface roughness model International Journal of Machine Tools and Manufacture 41 2001 451 462
8. E. Baci, and. Aykut A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt based alloy (stellite 6) The International Journal of Advanced Manufacturing Technology 29 2006 940 947
9. N. Baskar, P. Asokan, R. Saravanan, and G. Prabhaharan Optimization of machining parameters for milling operations using non-conventional methods International Journal of Advanced Manufacturing Technology 25 2005 1078 1088
10. P.G. Benardos, and G.C. Vosniakos Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments Robotics and Computer-Integrated Manufacturing 18 5-6 2002 343 354
11. P.G. Benardos, and G.C. Vosniakos Predicting surface roughness in machining: A review International Journal of Machine Tools and Manufacture 43 2003 833 844
12. C.E. Bezce, and M.A. Elbestawi A chip formation based analytic force model for oblique cutting International Journal of Machine Tools and Manufacture 42 2002 529 538
13. R.R. Boyer An overview on the use of titanium in the aerospace industry Materials Science and Engineering A 213 1996 103 114
14. R. Boyer, G. Welsch, and E.W. Collings Materials properties handbook: Titanium alloys 1994 ASM International Materials Park, OH
15. M. Calamaz, D. Coupard, and F. Girot A new material model for 2D numerical simulation of serrated chip formation when machining titanium alloy Ti-6Al-4V International Journal of Machine Tools and Manufacture 48 2008 275 288
16. D.L. Carroll Chemical laser modeling with genetic algorithms AIAA Journal 34 2 1996 338 346
17. Catalogue and Technical Guide (2003). SECO, Milling, Sweden.
18. A.E. Diniz, and J.C. Filho Influence of the relative positions of tool and workpiece on tool life, tool wear and surface in the face milling process Wear 232 1999 67 75
19. J.A. Ghani, I.A. Choudhury, and H.H. Hassan Application of Taguchi method in the optimization of end milling parameters Journal of Materials Processing Technology 145 2004 84 92
20. A. Ginting, and M. Nouari Experimental and numerical studies on the performance of alloyed carbide tool in dry milling of aerospace material International Journal of Machine Tools and Manufacture 46 2006 758 768
21. D.E. Goldberg Genetic algorithms in search, optimization and machine learning 1989 Addison-Wesley Reading, MA
22. Gülmez, S. (2003). Investigation of cutting forces and surface roughness of bor alloyed steel materials on surface milling. PhD thesis, Marmara University Institute of Science & Technology, Istanbul, Turkey.
23. C.H. Haron, and A. Jawaid The effect of machining on surface integrity of titanium alloy Ti-6%Al-4% V Journal of Materials Processing Technology 166 2005 188 192
24. ISO 8688-1 Tool Life Testing in Milling (1989). Part I, face milling (1st ed.).
25. M. Kurt, E. Bagci, and Y. Kaynak Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling progress International Journal of Advanced Manufacturing Technology 40 2009 458 469
26. R. Lia, P. Hegdeb, and A.J. Shiha High-throughput drilling of titanium alloys International Journal of Machine Tools and Manufacture 47 2007 63 74
27. S.P. Lo An adaptive-network based fuzzy inference system for prediction of workpiece surface roughness in end milling Journal of Materials Processing Technology 142 2003 665 675
28. M.S. Lou, J.C. Chen, and C.M. Li Surface roughness prediction technique for CNC end milling Journal of Industrial Technology 15 1 1999 1 6
29. Modgil, A. (2003). Effects of high speed machining on surface topography of titanium alloy (TI6AL4V). Master of science, University of Florida Institute of Science and Technology.
30. A. Molinari, C. Musquar, and G. Sutter Adiabatic shear banding in high-speed machining of Ti6Al4V: Experiments and modeling International Journal of Plasticity 18 2002 443 459
31. R.H. Myers, and D.C. Montgomery Response surface methodology process and product optimization using designed experiments 1995 John Wiley and Sons Inc. New York, USA
32. H. Oktem, T. Erzurumlu, and I. Uzman Application of Taguchi optimization technique in determining plastic injection molding process parameters for a thin-shell part Materials and Design 28 2007 1271 1278
33. J.P. Onders, P. Seshuy, and N.G. Naganathan Taguchi optimization of strain transfer in an induced strain actuator Smart Material Structure 5 1996 327 337
34. I.J. Polmear Light alloys: Metallurgy of the light metals 1989 Edward Arnold London
35. N.S.K. Reddy, and P.V. Rao Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling International Journal of Advanced Manufacturing Technology 26 2005 1202 1210
36. P.J. Ross Taguchi techniques for quality engineering 1988 McGraw-Hill New York, NY
37. D.E. Rumelhart, G. Hilton, and R.J. Williams Learning internal representations by error propagation E. Rumelhart, J.L. McClelland, Parallel distributed processing: Explorations in the microstructure of cognition vol. 1 1986 MIT Press 547
38. C. Sanjay, M.L. Neema, and C.W. Chin Modeling of tool wear in drilling by statistical analysis and artificial neural network Journal of Materials Processing Technology 170 2005 494 500
39. S.V. Shunmugam, R.T. Bhaskara, and T. Narendran Selection of optimum conditions in multi-pass face milling using a genetic algorithm International Journal of Machine Tools and Manufacture 40 2000 401 414
40. G. Taguchi Introduction to quality engineering 1986 Asian Productivity Organisation Tokyo
41. V. Tandon, H. El-Mounayri, and H. Kishawy NC end milling optimization using evolutionary computation International Journal of Machine Tools and Manufacture 42 2002 595 605
42. I.N. Tansel Neural network approach for representation and simulation of 3D-cutting dynamics Transactions of North American Metal Research Institute 1990 193 200
43. I.N. Tansel, T.T. Arkan, W.Y. Bao, N. Mahendrakar, B. Shisler, and D. Smith Tool wear estimation in micro-machining. Part I: Tool usage-cutting force relationship International Journal of Machine Tools and Manufacture 40 2000 599 608
44. I.N. Tansel, M. Demetgul, R.A. Leon, A. Yenilmez, and A. Yapici Design of energy scavengers of structural health monitoring systems using genetically optimized neural network systems Sensors and Materials 21 3 2009 141 153
45. I.N. Tansel, B. Ozcelik, W.Y. Bao, P. Chen, D. Rincon, and S.Y. Yang Selection of optimal cutting conditions by using GONNS International Journal of Machine Tools and Manufacture 46 2006 26 35
46. Y.H. Tsai, J.C. Chen, and S.J. Lou An in-process surface recognition system based on neural networks in end milling cutting operations International Journal of Machine Tools and Manufacture 39 1999 583 605
47. C.C. Tsao, and H. Hocheng Taguchi analysis of delamination associated with various drill bits in drilling of composite material International Journal of Machine Tools and Manufacture 44 2004 1085 1090
48. Y.F. Tzeng, and N.H. Chiu Two-phase parameter design for the optimization of the electrical-discharge machining process using a Taguchi dynamic experiment International Journal of Advanced Manufacturing Technology 21 2003 1005 1014
49. D. Umbrello Finite element simulation of conventional and high speed machining of Ti6Al4V alloy Journal of Materials Processing Technology 196 2008 79 87
50. Minitab User Manual Release 15. Making data analysis easier. State College, PA, USA: MINITAB Inc.
51. J.L. Yang, and J.C. Chen A systematic approach for identifying optimum surface roughness performance in end-milling operations Journal of Industrial Technology 17 2 2001 1 8
52. S.Y. Yang, V. Girivasan, N.R. Singh, I.N. Tansel, and C.V. Kropas-Hughes Selection of optimal material and operating conditions in composite manufacturing. Part II: Complexity, representation of characteristics and decision making International Journal of Machine Tools and Manufacture 43 2003 175 184
53. S.Y. Yang, I.N. Tansel, and C.V. Kropas-Hughes Selection of optimal material and operating conditions in composite manufacturing. Part I: Computational tool International Journal of Machine Tools and Manufacture 43 2003 169 173