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Volumn 46, Issue 5-8, 2010, Pages 445-464

Application of soft computing techniques in machining performance prediction and optimization: A literature review

Author keywords

Machining; Optimization; Process models; Soft computing

Indexed keywords

ANT-COLONY OPTIMIZATION; LITERATURE REVIEWS; MACHINING OPTIMIZATION; MACHINING PERFORMANCE; MACHINING PROCESS; MANUFACTURING PROCESS; PHYSICS-BASED MODELS; SOFT COMPUTING TOOLS; SOFTCOMPUTING TECHNIQUES;

EID: 74249115778     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-009-2104-x     Document Type: Article
Times cited : (315)

References (142)
  • 1
    • 0032296518 scopus 로고    scopus 로고
    • Interpretative look on 20th century research on modeling of machining
    • 10.1080/10940349808945666
    • ME Merchant 1998 Interpretative look on 20th century research on modeling of machining Mach Sci Technol 2 157 163 10.1080/10940349808945666
    • (1998) Mach Sci Technol , vol.2 , pp. 157-163
    • Merchant, M.E.1
  • 2
    • 0012167461 scopus 로고
    • Review of the metal-cutting analysis of the past hundred years
    • I Finnie 1956 Review of the metal-cutting analysis of the past hundred years Mech Eng 78 715 721
    • (1956) Mech Eng , vol.78 , pp. 715-721
    • Finnie, I.1
  • 4
    • 74249119882 scopus 로고    scopus 로고
    • Intelligent machining: Computational methods and optimization
    • J.P. Davim (eds). Springer London
    • Deb S, Dixit US (2008) Intelligent machining: computational methods and optimization. In: Davim JP (ed) Machining: fundamentals and recent advances. Springer, London
    • (2008) Machining: Fundamentals and Recent Advances
    • Deb, S.1    Dixit, U.S.2
  • 5
    • 59549085647 scopus 로고    scopus 로고
    • Optimization of multi-pass face-milling via harmony search algorithm
    • 10.1016/j.jmatprotec.2008.05.029
    • O Zarei M Fesanghary B Farshi R Jalili Saffar MR Razfar 2009 Optimization of multi-pass face-milling via harmony search algorithm J Mater Process Technol 209 2386 2392 10.1016/j.jmatprotec.2008.05.029
    • (2009) J Mater Process Technol , vol.209 , pp. 2386-2392
    • Zarei, O.1    Fesanghary, M.2    Farshi, B.3    Jalili Saffar, R.4    Razfar, M.R.5
  • 6
    • 25144483853 scopus 로고    scopus 로고
    • Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing
    • DOI 10.1016/j.ijmachtools.2005.03.009, PII S0890695505000775
    • ZG Wang M Rahman YS Wong J Sun 2005 Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing Int J Mach Tools Manuf 45 1726 1734 10.1016/j.ijmachtools.2005.03.009 (Pubitemid 41344914)
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , Issue.15 , pp. 1726-1734
    • Wang, Z.G.1    Rahman, M.2    Wong, Y.S.3    Sun, J.4
  • 7
    • 33645509900 scopus 로고    scopus 로고
    • Evolutionary optimization of machining processes
    • 10.1007/s10845-005-6637-z
    • JY Zang SY Liang J Yao JM Chen JL Hang 2006 Evolutionary optimization of machining processes J Intell Manuf 17 203 215 10.1007/s10845-005-6637-z
    • (2006) J Intell Manuf , vol.17 , pp. 203-215
    • Zang, J.Y.1    Liang, S.Y.2    Yao, J.3    Chen, J.M.4    Hang, J.L.5
  • 8
    • 84937425948 scopus 로고    scopus 로고
    • Meta heuristics: The state of art
    • 10.1007/3-540-45612-0-1
    • S Vo 2001 Meta heuristics: the state of art Lect Notes Comput Sci 2148 1 23 10.1007/3-540-45612-0-1
    • (2001) Lect Notes Comput Sci , vol.2148 , pp. 1-23
    • Vo, S.1
  • 9
    • 34248666540 scopus 로고
    • Fuzzy sets
    • 10.1016/S0019-9958(65) 90241-X 0139.24606 219427
    • LA Zadeh 1965 Fuzzy sets Inf Control 8 338 353 10.1016/S0019-9958(65) 90241-X 0139.24606 219427
    • (1965) Inf Control , vol.8 , pp. 338-353
    • Zadeh, L.A.1
  • 10
    • 0015558134 scopus 로고
    • Outline of a new approach to the analysis of complex systems and decision processes
    • 0273.93002 309582
    • LA Zadeh 1973 Outline of a new approach to the analysis of complex systems and decision processes IEEE Trans Syst Man Cybern 3 28 44 0273.93002 309582
    • (1973) IEEE Trans Syst Man Cybern , vol.3 , pp. 28-44
    • Zadeh, L.A.1
  • 13
    • 0030082551 scopus 로고    scopus 로고
    • The ant system: Optimization by a colony of co-operating agents
    • M Dorigo 1996 The ant system: optimization by a colony of co-operating agents IEEE Trans Syst Man Cybern Part B 26 1 13
    • (1996) IEEE Trans Syst Man Cybern Part B , vol.26 , pp. 1-13
    • Dorigo, M.1
  • 14
    • 34848884200 scopus 로고    scopus 로고
    • Ant colony optimization for continuous domains
    • DOI 10.1016/j.ejor.2006.06.046, PII S0377221706006333
    • K Socha M Dorigo 2008 Ant colony optimization for continuous domain Eur J Oper Res 185 1155 1173 10.1016/j.ejor.2006.06.046 1146.90537 2361750 (Pubitemid 47505285)
    • (2008) European Journal of Operational Research , vol.185 , Issue.3 , pp. 1155-1173
    • Socha, K.1    Dorigo, M.2
  • 16
    • 0024631951 scopus 로고
    • Learning and optimization of machining operations using computing abilities of neural networks
    • SS Rangwala DA Dornfeld 1989 Learning and optimization of machining operations using computing abilities of neural networks IEEE Trans Syst Man Cybern 19 299 314
    • (1989) IEEE Trans Syst Man Cybern , vol.19 , pp. 299-314
    • Rangwala, S.S.1    Dornfeld, D.A.2
  • 17
    • 0031233460 scopus 로고    scopus 로고
    • On-line prediction of surface finish and dimensional deviation in turning using neural network base sensor fusion
    • 10.1016/S0890-6955(97) 00013-8
    • R Azouzi M Guillot 1997 On-line prediction of surface finish and dimensional deviation in turning using neural network base sensor fusion Int J Mach Tools Manuf 37 1201 1217 10.1016/S0890-6955(97) 00013-8
    • (1997) Int J Mach Tools Manuf , vol.37 , pp. 1201-1217
    • Azouzi, R.1    Guillot, M.2
  • 18
    • 85016915578 scopus 로고
    • A comparison of statistical and AI approaches to the selection of process parameters in intelligent machining
    • G Chryssolouris M Guillot 1990 A comparison of statistical and AI approaches to the selection of process parameters in intelligent machining ASME J Eng Ind 112 112 131
    • (1990) ASME J Eng Ind , vol.112 , pp. 112-131
    • Chryssolouris, G.1    Guillot, M.2
  • 19
    • 0037233403 scopus 로고    scopus 로고
    • Surface roughness predictive modelling: Neural networks versus regression
    • 10.1080/07408170304433
    • C-X Feng X-F Wang 2003 Surface roughness predictive modelling: neural networks versus regression IIE Trans 35 11 27 10.1080/07408170304433
    • (2003) IIE Trans , vol.35 , pp. 11-27
    • Feng, C.-X.1    Wang, X.-F.2
  • 20
    • 0037427589 scopus 로고    scopus 로고
    • Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process
    • 10.1016/S0924-0136(02) 00920-2
    • KA Risbood US Dixit AD Sahasrabudhe 2003 Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process J Mater Process Technol 132 203 214 10.1016/S0924-0136(02) 00920-2
    • (2003) J Mater Process Technol , vol.132 , pp. 203-214
    • Risbood, K.A.1    Dixit, U.S.2    Sahasrabudhe, A.D.3
  • 21
    • 27744485019 scopus 로고    scopus 로고
    • Surface roughness prediction in turning using artificial neural network
    • DOI 10.1007/s00521-005-0468-x
    • SK Pal D Chakraborty 2005 Surface roughness prediction in turning using artificial neural network Neural Comput Appl 14 319 324 10.1007/s00521-005-0468- x (Pubitemid 41604362)
    • (2005) Neural Computing and Applications , vol.14 , Issue.4 , pp. 319-324
    • Pal, S.K.1    Chakraborty, D.2
  • 22
    • 12444249998 scopus 로고    scopus 로고
    • Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks
    • DOI 10.1016/j.ijmachtools.2004.09.007, PII S0890695504002299
    • T Ozel Y Karpat 2005 Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks Int J Mach Tools Manuf 45 467 479 10.1016/j.ijmachtools.2004.09.007 (Pubitemid 40142539)
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , Issue.4-5 , pp. 467-479
    • Ozel, T.1    Karpat, Y.2
  • 23
    • 11144328104 scopus 로고    scopus 로고
    • A neural-network-based methodology for the prediction of surface roughness in a turning process
    • DOI 10.1007/s00170-003-1810-z
    • A Kohli US Dixit 2005 A neural-network based methodology for the prediction of surface roughness in a turning process Int J Adv Manuf Technol 25 118 129 10.1007/s00170-003-1810-z (Pubitemid 40034736)
    • (2005) International Journal of Advanced Manufacturing Technology , vol.25 , Issue.1-2 , pp. 118-129
    • Kohli, A.1    Dixit, U.S.2
  • 25
    • 29344436678 scopus 로고    scopus 로고
    • The application of a radial basis function neural network for predicting the surface roughness in a turning process
    • DOI 10.1007/s00170-004-2258-5
    • DK Sonar US Dixit DK Ojha 2006 The application of radial basis function neural network for predicting the surface roughness in a turning process Int J Adv Manuf Technol 27 661 666 10.1007/s00170-004-2258-5 (Pubitemid 43004616)
    • (2006) International Journal of Advanced Manufacturing Technology , vol.27 , Issue.7-8 , pp. 661-666
    • Sonar, D.K.1    Dixit, U.S.2    Ojha, D.K.3
  • 26
    • 34748885549 scopus 로고    scopus 로고
    • Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked steel with a ceramic tool
    • S Basak US Dixit JP Davim 2007 Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked steel with a ceramic tool Proc Inst Mech Eng B J Eng Manuf 221 987 998
    • (2007) Proc Inst Mech Eng B J Eng Manuf , vol.221 , pp. 987-998
    • Basak, S.1    Dixit, U.S.2    Davim, J.P.3
  • 27
    • 34248214598 scopus 로고    scopus 로고
    • A comparison of dry and air-cooled turning of grey cast iron with mixed oxide ceramic tool
    • DOI 10.1016/j.jmatprotec.2007.02.049, PII S0924013607002981
    • DK Sarma US Dixit 2007 A comparison of dry and air-cooled turning of grey cast iron with mixed oxide ceramic tool J Mater Process Technol 190 160 172 10.1016/j.jmatprotec.2007.02.049 (Pubitemid 46719832)
    • (2007) Journal of Materials Processing Technology , vol.190 , Issue.1-3 , pp. 160-172
    • Sarma, D.K.1    Dixit, U.S.2
  • 28
    • 0028407979 scopus 로고
    • Predicting total machining performance in finish turning using integrated fuzzy-set models of the machinability parameters
    • 10.1080/00207549408956974 0901.90107
    • X Fang IS Jawahir 1994 Predicting total machining performance in finish turning using integrated fuzzy-set models of the machinability parameters Int J Prod Res 32 833 849 10.1080/00207549408956974 0901.90107
    • (1994) Int J Prod Res , vol.32 , pp. 833-849
    • Fang, X.1    Jawahir, I.S.2
  • 29
    • 33644780712 scopus 로고    scopus 로고
    • A knowledge-based system for the prediction of surface roughness in turning process
    • DOI 10.1016/j.rcim.2005.08.002, PII S0736584505000621
    • NR Abburi US Dixit 2006 A knowledge based system for the prediction of surface roughness in turning process Robot Comput Integr Manuf 22 363 372 10.1016/j.rcim.2005.08.002 (Pubitemid 43343781)
    • (2006) Robotics and Computer-Integrated Manufacturing , vol.22 , Issue.4 , pp. 363-372
    • Abburi, N.R.1    Dixit, U.S.2
  • 30
    • 27844472506 scopus 로고    scopus 로고
    • Fuzzy adaptive networks in machining process modeling dimensional error prediction for turning operations
    • 10.1080/00207540500031964
    • Y Jiao ZS Pei S Lei ES Lee GR Fisher 2005 Fuzzy adaptive networks in machining process modeling dimensional error prediction for turning operations Int J Prod Res 43 2931 2948 10.1080/00207540500031964
    • (2005) Int J Prod Res , vol.43 , pp. 2931-2948
    • Jiao, Y.1    Pei, Z.S.2    Lei, S.3    Lee, E.S.4    Fisher, G.R.5
  • 31
    • 10044288212 scopus 로고    scopus 로고
    • An expert system based on FBFN using a GA to predict surface finish in ultra-precision turning
    • 10.1016/j.jmatprotec.2004.04.408
    • AK Nandi DK Pratihar 2004 An expert system based on FBFN using a GA to predict surface finish in ultra-precision turning J Mater Process Technol 155-156 1150 1156 10.1016/j.jmatprotec.2004.04.408
    • (2004) J Mater Process Technol , vol.155-156 , pp. 1150-1156
    • Nandi, A.K.1    Pratihar, D.K.2
  • 32
    • 0029252416 scopus 로고
    • Tool-wear prediction using artificial neural networks
    • 10.1016/0924-0136(94) 01351-Z
    • EO Ezugwu SJ Arthur EL Hines 1995 Tool-wear prediction using artificial neural networks J Mater Process Technol 49 255 264 10.1016/0924-0136(94) 01351-Z
    • (1995) J Mater Process Technol , vol.49 , pp. 255-264
    • Ezugwu, E.O.1    Arthur, S.J.2    Hines, E.L.3
  • 33
    • 0033887646 scopus 로고    scopus 로고
    • Applicability of the modified back-propagation algorithm in tool condition monitoring for faster convergence
    • 10.1016/S0924-0136(99) 00295-2
    • RK Dutta S Paul AB Chattopadhyay 2000 Applicability of the modified back-propagation algorithm in tool condition monitoring for faster convergence J Mater Process Technol 98 299 309 10.1016/S0924-0136(99) 00295-2
    • (2000) J Mater Process Technol , vol.98 , pp. 299-309
    • Dutta, R.K.1    Paul, S.2    Chattopadhyay, A.B.3
  • 34
    • 1642335673 scopus 로고    scopus 로고
    • A study of tool life in hot machining using artificial neural networks and regression analysis method
    • 10.1016/S0924-0136(02) 00086-9
    • N Tosun L Ozler 2002 A study of tool life in hot machining using artificial neural networks and regression analysis method J Mater Process Technol 124 99 104 10.1016/S0924-0136(02) 00086-9
    • (2002) J Mater Process Technol , vol.124 , pp. 99-104
    • Tosun, N.1    Ozler, L.2
  • 35
    • 26644453746 scopus 로고    scopus 로고
    • An economic and reliable tool life estimation procedure for turning
    • DOI 10.1007/s00170-003-2049-4
    • DK Ojha US Dixit 2005 An economic and reliable tool life estimation procedure for turning Int J Adv Manuf Technol 26 726 732 10.1007/s00170-003- 2049-4 (Pubitemid 41442572)
    • (2005) International Journal of Advanced Manufacturing Technology , vol.26 , Issue.7-8 , pp. 726-732
    • Ojha, D.K.1    Dixit, U.S.2
  • 36
    • 42649138966 scopus 로고    scopus 로고
    • Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel
    • DOI 10.1007/s00170-007-0999-7
    • R Quiza L Figueira JP Davim 2008 Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel Int J Adv Manuf Technol 37 641 648 10.1007/s00170-007-0999-7 (Pubitemid 351601452)
    • (2008) International Journal of Advanced Manufacturing Technology , vol.37 , Issue.7-8 , pp. 641-648
    • Quiza, R.1    Figueira, L.2    Davim, J.P.3
  • 37
    • 33646192852 scopus 로고    scopus 로고
    • Application of particle swarm optimization in artificial neural network for prediction of tool life
    • 10.1007/s00170-004-2460-5
    • U Natarajan R Saravanan VM Periasamy 2006 Application of particle swarm optimization in artificial neural network for prediction of tool life Int J Adv Manuf Technol 28 1084 1088 10.1007/s00170-004-2460-5
    • (2006) Int J Adv Manuf Technol , vol.28 , pp. 1084-1088
    • Natarajan, U.1    Saravanan, R.2    Periasamy, V.M.3
  • 38
    • 0036664145 scopus 로고    scopus 로고
    • On-line and indirect tool wear monitoring in turning with artificial neural net works: A review of more than a decade of research
    • 10.1006/mssp. 2001.1460
    • B Sick 2002 On-line and indirect tool wear monitoring in turning with artificial neural net works: a review of more than a decade of research Mech Syst Signal Process 16 4 487 546 10.1006/mssp. 2001.1460
    • (2002) Mech Syst Signal Process , vol.16 , Issue.4 , pp. 487-546
    • Sick, B.1
  • 39
    • 0030194215 scopus 로고    scopus 로고
    • Evaluation of wear of turning carbide inserts using neural networks
    • 10.1016/0890-6955(95) 00089-5
    • S Das R Roy AB Chattopadhyay 1996 Evaluation of wear of turning carbide inserts using neural networks Int J Mach Tools Manuf 36 1639 1645 10.1016/0890-6955(95) 00089-5
    • (1996) Int J Mach Tools Manuf , vol.36 , pp. 1639-1645
    • Das, S.1    Roy, R.2    Chattopadhyay, A.B.3
  • 40
    • 0032021497 scopus 로고    scopus 로고
    • Tool wear monitoring of turning operations by neural network and expert system classification of a feature set generated from multiple sensors
    • 10.1006/mssp. 1997.0123
    • RG Silva RL Reuben KJ Baker SJ Wilcox 1998 Tool wear monitoring of turning operations by neural network and expert system classification of a feature set generated from multiple sensors Mech Syst Signal Process 12 2 319 332 10.1006/mssp. 1997.0123
    • (1998) Mech Syst Signal Process , vol.12 , Issue.2 , pp. 319-332
    • Silva, R.G.1    Reuben, R.L.2    Baker, K.J.3    Wilcox, S.J.4
  • 41
    • 33645975676 scopus 로고    scopus 로고
    • Neural network modeling of flank wear for tool condition monitoring in orthogonal cutting of hardened steel
    • Florida, USA
    • Nadgir A, Ozel T (2000) Neural network modeling of flank wear for tool condition monitoring in orthogonal cutting of hardened steel. 4th Int. Conf on Eng. Design and Automation. Florida, USA, pp 1-6
    • (2000) 4th Int. Conf on Eng. Design and Automation , pp. 1-6
    • Nadgir, A.1    Ozel, T.2
  • 42
    • 0036027397 scopus 로고    scopus 로고
    • On-line tool wear estimation in CNC turning operations using fuzzy neural network model
    • 10.1016/S0890-6955(01) 00096-7
    • C Chungchoo D Saini 2002 On-line tool wear estimation in CNC turning operations using fuzzy neural network model Int J Mach Tools Manuf 42 29 40 10.1016/S0890-6955(01) 00096-7
    • (2002) Int J Mach Tools Manuf , vol.42 , pp. 29-40
    • Chungchoo, C.1    Saini, D.2
  • 43
    • 74249085066 scopus 로고
    • A neural network approach to on-line monitoring of a turning process
    • RG Khanchustambham GM Zhang 1992 A neural network approach to on-line monitoring of a turning process IEEE Trans 2 889 894
    • (1992) IEEE Trans , vol.2 , pp. 889-894
    • Khanchustambham, R.G.1    Zhang, G.M.2
  • 44
    • 0029343099 scopus 로고
    • Modeling of the process damping force in chatter vibration
    • 10.1016/0890-6955(94) 00046-M
    • BY Lee YS Tarang SC Ma 1995 Modeling of the process damping force in chatter vibration Int J Mach Tools Manuf 35 951 962 10.1016/0890-6955(94) 00046-M
    • (1995) Int J Mach Tools Manuf , vol.35 , pp. 951-962
    • Lee, B.Y.1    Tarang, Y.S.2    Ma, S.C.3
  • 45
    • 0029314021 scopus 로고
    • A neural network system for predicting machining behaviour
    • 10.1016/0924-0136(94) 01626-C
    • LHS Luong TA Spedding 1995 A neural network system for predicting machining behaviour J Mater Process Technol 52 585 591 10.1016/0924-0136(94) 01626-C
    • (1995) J Mater Process Technol , vol.52 , pp. 585-591
    • Luong, L.H.S.1    Spedding, T.A.2
  • 46
    • 0343603511 scopus 로고    scopus 로고
    • Cutting force modeling using artificial neural networks
    • 10.1016/S0924-0136(99) 00183-1
    • T Szecsi 1999 Cutting force modeling using artificial neural networks J Mater Process Technol 92 344 349 10.1016/S0924-0136(99) 00183-1
    • (1999) J Mater Process Technol , vol.92 , pp. 344-349
    • Szecsi, T.1
  • 47
    • 0037303115 scopus 로고    scopus 로고
    • Multiple regression and neural networks analyses in composite machining
    • 10.1016/S0266-3538(02) 00232-4
    • JT Lin D Bhattacharya V Keeman 2003 Multiple regression and neural networks analyses in composite machining Compos Sci Technol 63 539 548 10.1016/S0266-3538(02) 00232-4
    • (2003) Compos Sci Technol , vol.63 , pp. 539-548
    • Lin, J.T.1    Bhattacharya, D.2    Keeman, V.3
  • 48
    • 20444464409 scopus 로고    scopus 로고
    • Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural network
    • DOI 10.1016/j.ijmachtools.2005.02.004, PII S0890695505000556
    • EO Ezugwu DA Fadare J Bonney RB Da Silva WF Sales 2005 Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural network Int J Mach Tools Manuf 45 1375 1385 10.1016/j.ijmachtools.2005.02.004 (Pubitemid 40821886)
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , Issue.12-13 , pp. 1375-1385
    • Ezugwu, E.O.1    Fadare, D.A.2    Bonney, J.3    Da Silva, R.B.4    Sales, W.F.5
  • 49
    • 33748081789 scopus 로고    scopus 로고
    • Prediction of cutting force for self-propelled rotary tool using artificial neural networks
    • DOI 10.1016/j.jmatprotec.2006.04.123, PII S0924013606005073
    • W Hao X Zhu X Li G Turagyenda 2006 Prediction of cutting force for self-propelled cutting tool by artificial neural networks J Mater Process Technol 180 23 29 10.1016/j.jmatprotec.2006.04.123 (Pubitemid 44301836)
    • (2006) Journal of Materials Processing Technology , vol.180 , Issue.1-3 , pp. 23-29
    • Hao, W.1    Zhu, X.2    Li, X.3    Turyagyenda, G.4
  • 50
    • 0035154004 scopus 로고    scopus 로고
    • Modeling the surface roughness and cutting force for turning
    • 10.1016/S0924-0136(00) 00835-9
    • WS Lin BY Lee CL Wu 2001 Modeling the surface roughness and cutting force for turning J Mater Process Technol 108 286 293 10.1016/S0924-0136(00) 00835-9
    • (2001) J Mater Process Technol , vol.108 , pp. 286-293
    • Lin, W.S.1    Lee, B.Y.2    Wu, C.L.3
  • 51
    • 0033661251 scopus 로고    scopus 로고
    • Feed cutting force estimation from the current measurement with hybrid learning
    • 10.1007/s001700070002
    • X Li PK Venuvinod MK Chen 2000 Feed cutting force estimation from the current measurement with hybrid learning Int J Adv Manuf Technol 16 859 862 10.1007/s001700070002
    • (2000) Int J Adv Manuf Technol , vol.16 , pp. 859-862
    • Li, X.1    Venuvinod, P.K.2    Chen, M.K.3
  • 52
    • 32844468514 scopus 로고    scopus 로고
    • Hard turning optimization using neural network modeling & swarm intelligence
    • Y Karpat T Ozel 2005 Hard turning optimization using neural network modeling & swarm intelligence Trans NAMRI/SME 33 179 186
    • (2005) Trans NAMRI/SME , vol.33 , pp. 179-186
    • Karpat, Y.1    Ozel, T.2
  • 53
    • 0001908183 scopus 로고
    • A neural network approach to multiple-objective cutting parameter optimization based on fuzzy preference information
    • 10.1016/0360-8352(93) 90303-F
    • J Wang 1993 A neural network approach to multiple-objective cutting parameter optimization based on fuzzy preference information Comput Ind Eng 25 389 392 10.1016/0360-8352(93) 90303-F
    • (1993) Comput Ind Eng , vol.25 , pp. 389-392
    • Wang, J.1
  • 54
    • 0033101579 scopus 로고    scopus 로고
    • An economic machining process model using fuzzy non-linear programming and neural network
    • 10.1080/002075499191553 0939.90523
    • YH Lee BH Yang KS Moon 1999 An economic machining process model using fuzzy non-linear programming and neural network Int J Prod Res 37 835 847 10.1080/002075499191553 0939.90523
    • (1999) Int J Prod Res , vol.37 , pp. 835-847
    • Lee, Y.H.1    Yang, B.H.2    Moon, K.S.3
  • 55
    • 0033615132 scopus 로고    scopus 로고
    • Fuzzy-logic based intelligent selection of machining parameters
    • 10.1016/S0924-0136(99) 00086-2
    • K Hashmi MA El Baradie M Ryan 1999 Fuzzy-logic based intelligent selection of machining parameters J Mater Process Technol 94 94 111 10.1016/S0924-0136(99) 00086-2
    • (1999) J Mater Process Technol , vol.94 , pp. 94-111
    • Hashmi, K.1    El Baradie, M.A.2    Ryan, M.3
  • 57
    • 50849083205 scopus 로고    scopus 로고
    • Real-coded genetic algorithm for machining condition optimization
    • 10.1007/s00170-007-1144-3
    • SS Kim IH Kim V Mani HJ Kim 2008 Real-coded genetic algorithm for machining condition optimization Int J Adv Manuf Technol 38 884 895 10.1007/s00170-007-1144-3
    • (2008) Int J Adv Manuf Technol , vol.38 , pp. 884-895
    • Kim, S.S.1    Kim, I.H.2    Mani, V.3    Kim, H.J.4
  • 58
    • 0030271088 scopus 로고    scopus 로고
    • A simulated annealing approach for optimization of multi-pass turning operation
    • 10.1080/00207549608905060 0929.90018
    • M-C Chen D-M Tasi 1996 A simulated annealing approach for optimization of multi-pass turning operation Int J Prod Res 34 2803 2825 10.1080/ 00207549608905060 0929.90018
    • (1996) Int J Prod Res , vol.34 , pp. 2803-2825
    • Chen, M.-C.1    Tasi, D.-M.2
  • 59
    • 0037053053 scopus 로고    scopus 로고
    • Novel algorithm approach to generate the 'number of passes' and ' depth of cuts' for the optimization routines of multi pass machining
    • 10.1080/00207540210147043
    • A Baykasoglu T Dereli 2002 Novel algorithm approach to generate the 'number of passes' and ' depth of cuts' for the optimization routines of multi pass machining Int J Prod Res 40 1549 1565 10.1080/00207540210147043
    • (2002) Int J Prod Res , vol.40 , pp. 1549-1565
    • Baykasoglu, A.1    Dereli, T.2
  • 60
    • 0035838747 scopus 로고    scopus 로고
    • Tabu search-based algorithm for the TOC product mix decision
    • DOI 10.1080/00207540010005736
    • GC Onwubolu T Kumalo 2001 Optimization of multi pass turning operations with genetic algorithm Int J Prod Res 39 3727 3745 10.1080/00207540010005736 1114.90360 (Pubitemid 35165582)
    • (2001) International Journal of Production Research , vol.39 , Issue.10 , pp. 2065-2076
    • Onwubolu, G.C.1
  • 61
    • 0242364684 scopus 로고    scopus 로고
    • Optimization of multi-pass turning operations with genetic algorithms: A note
    • 10.1080/0020754031000118143
    • MC Chen KY Chen 2003 Optimization of multi-pass turning operations with genetic algorithms: a note Int J Prod Res 41 3385 3388 10.1080/ 0020754031000118143
    • (2003) Int J Prod Res , vol.41 , pp. 3385-3388
    • Chen, M.C.1    Chen, K.Y.2
  • 62
    • 27844543848 scopus 로고    scopus 로고
    • Optimization of multi-pass turning operations using genetic algorithms for the selection of cutting conditions and cutting tools with tool-wear effect
    • 10.1080/13629390500124465 1082.90521
    • X Wang IS Jawahir 2005 Optimization of multi-pass turning operations using genetic algorithms for the selection of cutting conditions and cutting tools with tool-wear effect Int J Prod Res 43 3543 3559 10.1080/ 13629390500124465 1082.90521
    • (2005) Int J Prod Res , vol.43 , pp. 3543-3559
    • Wang, X.1    Jawahir, I.S.2
  • 63
    • 65049088891 scopus 로고    scopus 로고
    • Optimization of multi-pass turning using particle swarm intelligence
    • 10.1007/s00170-007-1320-5
    • J Srinivas R Giri SH Yang 2009 Optimization of multi-pass turning using particle swarm intelligence Int J Adv Manuf Technol 40 56 66 10.1007/s00170-007-1320-5
    • (2009) Int J Adv Manuf Technol , vol.40 , pp. 56-66
    • Srinivas, J.1    Giri, R.2    Yang, S.H.3
  • 64
    • 0141917462 scopus 로고    scopus 로고
    • Optimization of multi-pass turning operations using ant colony system
    • 10.1016/S0890-6955(03) 00081-6
    • K Vijayakumar G Prabhaharan P Asokan R Saravanan 2003 Optimization of multi-pass turning operations using ant colony system Int J Mach Tools Manuf 43 1633 1639 10.1016/S0890-6955(03) 00081-6
    • (2003) Int J Mach Tools Manuf , vol.43 , pp. 1633-1639
    • Vijayakumar, K.1    Prabhaharan, G.2    Asokan, P.3    Saravanan, R.4
  • 65
    • 34547652866 scopus 로고    scopus 로고
    • A note on 'optimization of multi-pass turning operations using ant colony system'
    • DOI 10.1016/j.ijmachtools.2007.03.001, PII S0890695507000430
    • YC Wang 2007 A note on 'Optimization of multi-pass turning operations using ant colony system' Int J Mach Tools Manuf 47 2057 2059 10.1016/j.ijmachtools.2007.03.001 (Pubitemid 47211760)
    • (2007) International Journal of Machine Tools and Manufacture , vol.47 , Issue.12-13 , pp. 2057-2059
    • Wang, Y.-C.1
  • 66
    • 66149179350 scopus 로고    scopus 로고
    • A soft computing based optimization of multi-pass turning processes
    • DK Ojha US Dixit JP Davim 2009 A soft computing based optimization of multi-pass turning processes Int J Mater Prod Technol 35 145 166
    • (2009) Int J Mater Prod Technol , vol.35 , pp. 145-166
    • Ojha, D.K.1    Dixit, U.S.2    Davim, J.P.3
  • 67
    • 33748019076 scopus 로고
    • A multi pass optimization strategy for CNC lathe operations
    • 10.1016/0925-5273(95) 00052-1
    • SH Yeo 1995 A multi pass optimization strategy for CNC lathe operations Int J Prod Econ 40 209 218 10.1016/0925-5273(95) 00052-1
    • (1995) Int J Prod Econ , vol.40 , pp. 209-218
    • Yeo, S.H.1
  • 68
    • 0141959043 scopus 로고    scopus 로고
    • An adaptive-network based fuzzy inference system for prediction of work piece surface roughness in end milling
    • 10.1016/S0924-013600687-3
    • SP Lo 2003 An adaptive-network based fuzzy inference system for prediction of work piece surface roughness in end milling J Mater Process Technol 142 665 675 10.1016/S0924-013600687-3
    • (2003) J Mater Process Technol , vol.142 , pp. 665-675
    • Lo, S.P.1
  • 69
    • 56349089474 scopus 로고    scopus 로고
    • Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi- genetic learning algorithm
    • 10.1016/j.eswa.2008.01.051
    • WH Ho JT Tasi BT Lin JH Chou 2009 Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi- genetic learning algorithm Expert Syst Appl 36 3216 3222 10.1016/j.eswa.2008.01.051
    • (2009) Expert Syst Appl , vol.36 , pp. 3216-3222
    • Ho, W.H.1    Tasi, J.T.2    Lin, B.T.3    Chou, J.H.4
  • 70
    • 10444269430 scopus 로고    scopus 로고
    • Prediction of surface roughness with genetic programming
    • 10.1016/j.jmatprotec.2004.09.004
    • M Brezocnik M Kovacic M Ficko 2004 Prediction of surface roughness with genetic programming J Mater Process Technol 157-158 28 36 10.1016/j.jmatprotec. 2004.09.004
    • (2004) J Mater Process Technol , vol.157-158 , pp. 28-36
    • Brezocnik, M.1    Kovacic, M.2    Ficko, M.3
  • 72
    • 27544452012 scopus 로고    scopus 로고
    • Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling
    • DOI 10.1007/s00170-004-2110-y
    • NSK Reddy PV Rao 2005 Selection of optimum geometry and cutting conditions using surface roughness prediction model for end milling Int J Adv Manuf Technol 26 1202 1210 10.1007/s00170-004-2110-y (Pubitemid 41539537)
    • (2005) International Journal of Advanced Manufacturing Technology , vol.26 , Issue.11-12 , pp. 1202-1210
    • Reddy, N.S.K.1    Venkateswara Rao, P.2
  • 73
    • 27344460096 scopus 로고    scopus 로고
    • Application of response surface methodology in the optimization of cutting conditions for surface roughness
    • DOI 10.1016/j.jmatprotec.2005.04.096, PII S0924013605004814
    • H Oktem T Erzurumlu H Kutaran 2005 Applications of response surface methodology in the optimization of cutting conditions for surface roughness J Mater Process Technol 170 11 16 10.1016/j.jmatprotec.2005.04.096 (Pubitemid 41526145)
    • (2005) Journal of Materials Processing Technology , vol.170 , Issue.1-2 , pp. 11-16
    • Oktem, H.1    Erzurumlu, T.2    Kurtaran, H.3
  • 74
    • 33645526483 scopus 로고    scopus 로고
    • Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms
    • 10.1007/s00170-004-2381-3
    • NSK Reddy PV Rao 2006 Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms Int J Adv Manuf Technol 28 463 473 10.1007/s00170-004-2381-3
    • (2006) Int J Adv Manuf Technol , vol.28 , pp. 463-473
    • Reddy, N.S.K.1    Rao, P.V.2
  • 75
    • 61849100434 scopus 로고    scopus 로고
    • Optimal cutting condition determination for desired surface roughness in end milling
    • 10.1007/s00170-008-1491-8
    • C Prakasvudhisarn S Kunnapapdeelert P Yenradee 2009 Optimal cutting condition determination for desired surface roughness in end milling Int J Adv Manuf Technol 41 440 451 10.1007/s00170-008-1491-8
    • (2009) Int J Adv Manuf Technol , vol.41 , pp. 440-451
    • Prakasvudhisarn, C.1    Kunnapapdeelert, S.2    Yenradee, P.3
  • 76
    • 0034808424 scopus 로고    scopus 로고
    • A fuzzy-net-based multilevel in-process surface roughness recognition system in milling operations
    • DOI 10.1007/s001700170132
    • JC Chen M Savage 2001 A fuzzy-net-based multilevel in-process surface roughness recognition system in milling operations Int J Adv Manuf Technol 17 670 676 10.1007/s001700170132 (Pubitemid 32914763)
    • (2001) International Journal of Advanced Manufacturing Technology , vol.17 , Issue.9 , pp. 670-676
    • Chen, J.C.1    Savage, M.2
  • 77
    • 33751429157 scopus 로고    scopus 로고
    • A fuzzy expert system for optimizing parameters and predicting performance measures in hard-milling process
    • DOI 10.1016/j.eswa.2006.02.003, PII S0957417406000790
    • A Iqbal N He L Li NU Dar 2007 A fuzzy expert system for optimizing parameters and predicting performance measures in hard-milling process Expert Syst Appl 32 1020 1027 10.1016/j.eswa.2006.02.003 (Pubitemid 44821792)
    • (2007) Expert Systems with Applications , vol.32 , Issue.4 , pp. 1020-1027
    • Iqbal, A.1    He, N.2    Li, L.3    Dar, N.U.4
  • 79
    • 0031166275 scopus 로고    scopus 로고
    • A fuzzy-nets in process (FNIP) systems for tool-breakage monitoring in end-milling operations
    • 10.1016/S0890-6955(96) 00023-5
    • JC Chen JT Black 1997 A fuzzy-nets in process (FNIP) systems for tool-breakage monitoring in end-milling operations Int J Mach Tools Manuf 37 6 783 800 10.1016/S0890-6955(96) 00023-5
    • (1997) Int J Mach Tools Manuf , vol.37 , Issue.6 , pp. 783-800
    • Chen, J.C.1    Black, J.T.2
  • 80
    • 0034633398 scopus 로고    scopus 로고
    • Fuzzy controlled backpropagation neural network for tool condition monitoring in face milling
    • DOI 10.1080/00207540050117404
    • RK Dutta S Paul AB Chattopadyay 2000 Fuzzy controlled back propagation neural network for tool condition monitoring in face milling Int J Prod Res 38 13 2989 3010 10.1080/00207540050117404 (Pubitemid 35401974)
    • (2000) International Journal of Production Research , vol.38 , Issue.13 , pp. 2989-3010
    • Dutta, R.K.1    Paul, S.2    Chattopadhyay, A.B.3
  • 81
    • 0037282530 scopus 로고    scopus 로고
    • Fuzzy logic based in-process tool wear monitoring system in face milling operations
    • V Susanto JC Chen 2003 Fuzzy logic based in-process tool wear monitoring system in face milling operations Int J Adv Manuf Technol 3 186 192
    • (2003) Int J Adv Manuf Technol , vol.3 , pp. 186-192
    • Susanto, V.1    Chen, J.C.2
  • 83
    • 33751164620 scopus 로고    scopus 로고
    • The efficacy of back propagation neural network with delta bar delta learning in predicting the wear of carbide inserts in face milling
    • DOI 10.1007/s00170-005-0230-7
    • RK Dutta S Paul AB Chattopadyay 2006 The efficacy of back propagation neural network with delta bar delta learning in predicting the wear of carbide inserts in face milling Int J Adv Manuf Technol 31 434 442 10.1007/s00170-005- 0230-7 (Pubitemid 44777572)
    • (2006) International Journal of Advanced Manufacturing Technology , vol.31 , Issue.5-6 , pp. 434-442
    • Dutta, R.K.1    Paul, S.2    Chattopadhyay, A.B.3
  • 84
    • 34548245991 scopus 로고    scopus 로고
    • The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel
    • DOI 10.1007/s00170-006-0630-3
    • C Ching-kao HS Lu 2007 The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel Int J Adv Manuf Technol 34 440 447 10.1007/s00170-006-0630-3 (Pubitemid 47326506)
    • (2007) International Journal of Advanced Manufacturing Technology , vol.34 , Issue.5-6 , pp. 440-447
    • Ching-Kao, C.1    Lu, H.S.2
  • 86
    • 9444285555 scopus 로고    scopus 로고
    • Tool cutting force modeling in ball end milling using multilevel perceptron
    • 10.1016/j.jmatprotec.2004.04.309
    • U Zuperl F Cus 2004 Tool cutting force modeling in ball end milling using multilevel perceptron J Mater Process Technol 153 154 268 275 10.1016/j.jmatprotec.2004.04.309
    • (2004) J Mater Process Technol , vol.153 , Issue.154 , pp. 268-275
    • Zuperl, U.1    Cus, F.2
  • 87
    • 14844364069 scopus 로고    scopus 로고
    • Milling force prediction using regression and neural networks
    • DOI 10.1007/s10845-005-4826-4
    • T Radhakrishnan U Nandan 2005 Milling force prediction using regression and neural networks J Intell Manuf 16 93 102 10.1007/s10845-005-4826-4 (Pubitemid 40356757)
    • (2005) Journal of Intelligent Manufacturing , vol.16 , Issue.1 , pp. 93-102
    • Radhakrishnan, T.1    Nandan, U.2
  • 88
    • 0036568755 scopus 로고    scopus 로고
    • Selecting an artificial neural network for efficient modeling and accurate simulation of the milling process
    • 10.1016/S0890-6955(02) 00008-1
    • JF Briceno H El-Mounayri S Mukhopadhyay 2002 Selecting an artificial neural network for efficient modeling and accurate simulation of the milling process Int J Mach Tools Manuf 42 663 674 10.1016/S0890-6955(02) 00008-1
    • (2002) Int J Mach Tools Manuf , vol.42 , pp. 663-674
    • Briceno, J.F.1    El-Mounayri, H.2    Mukhopadhyay, S.3
  • 89
    • 33646805419 scopus 로고    scopus 로고
    • A generalized neural network model of ball end milling force system
    • U Zuperl F Cus B Mursec T Ploi 2006 A generalized neural network model of ball end milling force system Int J Mach Tools Manuf 175 98 108
    • (2006) Int J Mach Tools Manuf , vol.175 , pp. 98-108
    • Zuperl, U.1    Cus, F.2    Mursec, B.3    Ploi, T.4
  • 90
    • 34248164412 scopus 로고    scopus 로고
    • Modeling of cutting forces as function of cutting parameters for face milling of satellite 6 using an artificial neural network
    • DOI 10.1016/j.jmatprotec.2007.02.045, PII S0924013607001872
    • S Aykut M Golcu S Semiz HS Ergur 2007 Modelling of cutting forces as function of cutting parameters for face milling of satellite 6 using artificial neural network J Mater Process Technol 190 199 203 10.1016/j.jmatprotec.2007.02. 045 (Pubitemid 46719829)
    • (2007) Journal of Materials Processing Technology , vol.190 , Issue.1-3 , pp. 199-203
    • Aykut, S.1    Golcu, M.2    Semiz, S.3    Ergur, H.S.4
  • 92
    • 0342732898 scopus 로고    scopus 로고
    • Selection of optimal conditions in multi-pass face-milling using a genetic algorithm
    • 10.1016/S0890-6955(99) 00063-2
    • MS Shunmugam SV Bhaskara Reddy TT Narendran 2000 Selection of optimal conditions in multi-pass face-milling using a genetic algorithm Int J Mach Tools Manuf 40 401 414 10.1016/S0890-6955(99) 00063-2
    • (2000) Int J Mach Tools Manuf , vol.40 , pp. 401-414
    • Shunmugam, M.S.1    Bhaskara Reddy, S.V.2    Narendran, T.T.3
  • 93
    • 33646812230 scopus 로고    scopus 로고
    • An intelligent system for monitoring and optimization of ball-end milling process
    • DOI 10.1016/j.jmatprotec.2005.04.041, PII S0924013605004462
    • F Cus M Milfelner J Balic 2006 An intelligent system for monitoring and optimization of ball-end milling process J Mater Process Technol 175 90 97 10.1016/j.jmatprotec.2005.04.041 (Pubitemid 43767677)
    • (2006) Journal of Materials Processing Technology , vol.175 , Issue.1-3 , pp. 90-97
    • Cus, F.1    Milfelner, M.2    Balic, J.3
  • 94
    • 33750024289 scopus 로고    scopus 로고
    • Optimization of cutting parameters in micro end milling operations in dry cutting condition using genetic algorithms
    • DOI 10.1007/s00170-005-0148-0
    • S Sreeram A Senthilkumar M Rahman MT Zaman 2006 Optimization of cutting parameters in micro end milling operations under dry cutting conditions using genetic algorithms Int J Adv Manuf Technol 30 1030 1039 10.1007/s00170-005-0148- 0 (Pubitemid 44570086)
    • (2006) International Journal of Advanced Manufacturing Technology , vol.30 , Issue.11-12 , pp. 1030-1039
    • Sreeram, S.1    Kumar, A.S.2    Rahman, M.3    Zaman, M.T.4
  • 95
    • 9944228654 scopus 로고    scopus 로고
    • Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing
    • 10.1007/s00170-003-1789-5
    • ZG Wang YS Wong M Rahman 2004 Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing Int J Adv Manuf Technol 24 727 732 10.1007/s00170-003-1789-5
    • (2004) Int J Adv Manuf Technol , vol.24 , pp. 727-732
    • Wang, Z.G.1    Wong, Y.S.2    Rahman, M.3
  • 96
    • 0000680147 scopus 로고    scopus 로고
    • Neural network modeling for tool path planning of rough cut in complex pocket milling
    • 10.1016/0278-6125(96) 84192-6
    • SH Suh YS Shin 1996 Neural network modeling for tool path planning of rough cut in complex pocket milling J Manuf Syst 15 295 304 10.1016/0278- 6125(96) 84192-6
    • (1996) J Manuf Syst , vol.15 , pp. 295-304
    • Suh, S.H.1    Shin, Y.S.2
  • 97
    • 0345533925 scopus 로고    scopus 로고
    • Surface roughness prediction of ground components using a fuzzy logic approach
    • 10.1016/S0924-0136(99) 00022-9
    • YM Ali LC Zhang 1999 Surface roughness prediction of ground components using a fuzzy logic approach J Mater Process Technol 89-90 561 568 10.1016/S0924-0136(99) 00022-9
    • (1999) J Mater Process Technol , vol.8990 , pp. 561-568
    • Ali, Y.M.1    Zhang, L.C.2
  • 98
    • 7544238854 scopus 로고    scopus 로고
    • Design of a genetic-fuzzy system to predict surface finish and power requirement in grinding
    • 10.1016/j.fss.2003.10.001
    • AK Nandhi DK Pratihar 2004 Design of a genetic-fuzzy system to predict surface finish and power requirement in grinding Fuzzy Sets Syst 148 487 504 10.1016/j.fss.2003.10.001
    • (2004) Fuzzy Sets Syst , vol.148 , pp. 487-504
    • Nandhi, A.K.1    Pratihar, D.K.2
  • 99
    • 41149124619 scopus 로고    scopus 로고
    • Evaluation of pre-estimation model to the in process surface roughness for grinding operations
    • GH Kim 2002 Evaluation of pre-estimation model to the in process surface roughness for grinding operations Int J Korean Soc Precis Eng 3 24 30
    • (2002) Int J Korean Soc Precis Eng , vol.3 , pp. 24-30
    • Kim, G.H.1
  • 100
    • 32844471488 scopus 로고    scopus 로고
    • Surface roughness in grinding: On-line prediction with adaptive neuro-fuzzy inference system
    • MS Samhouri BW Surgenor 2005 Surface roughness in grinding: On-line prediction with adaptive neuro-fuzzy inference system Trans NAMRI/SME 33 57 64
    • (2005) Trans NAMRI/SME , vol.33 , pp. 57-64
    • Samhouri, M.S.1    Surgenor, B.W.2
  • 101
    • 0026928374 scopus 로고
    • Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
    • DOI 10.1109/72.159070
    • LX Wang JM Mandel 1992 Fuzzy basis functions, universal approximation, and orthogonal least squares learning IEEE Trans Neural Netw 3 807 814 10.1109/72.159070 (Pubitemid 23555771)
    • (1992) IEEE Transactions on Neural Networks , vol.3 , Issue.5 , pp. 807-814
    • Wang Li-Xin1    Mendel Jerry, M.2
  • 102
    • 17844394975 scopus 로고    scopus 로고
    • FBF-NN-based modelling of cylindrical plunge grinding process using a GA
    • DOI 10.1016/j.jmatprotec.2005.02.080, PII S0924013605001664
    • AK Nandi MK Banerjee 2005 FBF-NN-based modeling of cylindrical plunge grinding process using a GA J Mater Process Technol 162-163 655 664 10.1016/j.jmatprotec.2005.02.080 (Pubitemid 40584451)
    • (2005) Journal of Materials Processing Technology , vol.162-163 , Issue.SPEC. ISS. , pp. 655-664
    • Nandi, A.K.1    Banerjee, M.K.2
  • 103
    • 0032598119 scopus 로고    scopus 로고
    • In-process monitoring of grinding burn in cylindrical grinding of steel
    • 10.1016/S0924-0136(98) 00408-7
    • R Deivanathan L Vijayaraghavan R Krishnamurthy 1999 In-process monitoring of grinding burn in cylindrical grinding of steel J Mater Process Technol 91 37 42 10.1016/S0924-0136(98) 00408-7
    • (1999) J Mater Process Technol , vol.91 , pp. 37-42
    • Deivanathan, R.1    Vijayaraghavan, L.2    Krishnamurthy, R.3
  • 104
    • 0035149341 scopus 로고    scopus 로고
    • Neural network detection of grinding burn from acoustic emission
    • 10.1016/S0890-6955(00) 00057-2
    • Z Wang P Willet PR Deaguiar J Webster 2001 Neural network detection of grinding burn from acoustic emission Int J Mach Tools Manuf 41 283 309 10.1016/S0890-6955(00) 00057-2
    • (2001) Int J Mach Tools Manuf , vol.41 , pp. 283-309
    • Wang, Z.1    Willet, P.2    Deaguiar, P.R.3    Webster, J.4
  • 105
    • 0442296307 scopus 로고    scopus 로고
    • A fuzzy model for predicting burns in surface grinding of steel
    • YM Ali LC Zhang 2004 A fuzzy model for predicting burns in surface grinding of steel J Mater Process Technol 44 563 571
    • (2004) J Mater Process Technol , vol.44 , pp. 563-571
    • Ali, Y.M.1    Zhang, L.C.2
  • 106
    • 13844320880 scopus 로고    scopus 로고
    • Fuzzy pattern recognition of AE signals for grinding burn
    • DOI 10.1016/j.ijmachtools.2004.11.002, PII S0890695504002743
    • Q Liu X Chen N Gindy 2005 Fuzzy pattern recognition of AE signals for grinding burn Int J Mach Tools Manuf 45 811 818 10.1016/j.ijmachtools.2004.11. 002 (Pubitemid 40259559)
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , Issue.7-8 , pp. 811-818
    • Liu, Q.1    Chen, X.2    Gindy, N.3
  • 107
    • 0035254604 scopus 로고    scopus 로고
    • An intelligent system for grinding wheel condition monitoring
    • 10.1016/S0924-0136(00) 00808-6
    • P Lezanski 2001 An intelligent system for grinding wheel condition monitoring J Mater Process Technol 109 258 263 10.1016/S0924-0136(00) 00808-6
    • (2001) J Mater Process Technol , vol.109 , pp. 258-263
    • Lezanski, P.1
  • 108
    • 0031199590 scopus 로고    scopus 로고
    • Force modeling and forecasting in creep feed grinding using improved BP neural network
    • 10.1016/S0890-6955(96)00012-0
    • KH Fuh SB Wang 1997 Force modeling and forecasting in creep feed grinding using improved BP neural network Int J Mach Tools Manuf 37 1167 1178 10.1016/S0890-6955(96)00012-0
    • (1997) Int J Mach Tools Manuf , vol.37 , pp. 1167-1178
    • Fuh, K.H.1    Wang, S.B.2
  • 109
    • 1842639334 scopus 로고    scopus 로고
    • Neural network approach for diagnosis of grinding operation by acoustic emission and power signals
    • 10.1016/j.jmatprotec.2003.11.016
    • JS Kawak MK Ha 2004 Neural network approach for diagnosis of grinding operation by acoustic emission and power signals J Mater Process Technol 147 65 71 10.1016/j.jmatprotec.2003.11.016
    • (2004) J Mater Process Technol , vol.147 , pp. 65-71
    • Kawak, J.S.1    Ha, M.K.2
  • 110
    • 0028518773 scopus 로고
    • A neural network approach for grinding processes: Modelling and optimization
    • 10.1016/0890-6955(94)90105-8?>
    • TW Liao LJ Chen 1994 A neural network approach for grinding processes: modelling and optimization Int J Mach Tools Manuf 34 919 937 10.1016/0890-6955(94)90105-8?>
    • (1994) Int J Mach Tools Manuf , vol.34 , pp. 919-937
    • Liao, T.W.1    Chen, L.J.2
  • 111
    • 20944437897 scopus 로고    scopus 로고
    • Neural modelling, control and optimisation of an industrial grinding process
    • DOI 10.1016/j.conengprac.2004.11.006, PII S0967066104002333
    • JJ Govindasamy SF McLoone GW Irwin JJ French RP Doyle 2005 Neural modeling, control and optimization of an industrial grinding process Control Eng Pract 13 1243 1258 10.1016/j.conengprac.2004.11.006 (Pubitemid 40870023)
    • (2005) Control Engineering Practice , vol.13 , Issue.10 , pp. 1243-1258
    • Govindhasamy, J.J.1    McLoone, S.F.2    Irwin, G.W.3    French, J.J.4    Doyle, R.P.5
  • 112
  • 113
    • 0034664161 scopus 로고    scopus 로고
    • Evolutionary modelling and optimization of grinding processes
    • DOI 10.1080/002075400411484
    • CW Lee YC Shin 2000 Evolutionary modeling and optimization of grinding process Int J Prod Res 38 12 2787 2813 10.1080/002075400411484 (Pubitemid 35401828)
    • (2000) International Journal of Production Research , vol.38 , Issue.12 , pp. 2787-2813
    • Lee, C.W.1    Shin, Y.C.2
  • 114
    • 0034808259 scopus 로고    scopus 로고
    • Genetic algorithm (GA) for multivariable surface grinding process optimisation using a multi-objective function model
    • DOI 10.1007/s001700170167
    • R Saravanan M Sachithanandam 2001 Genetic algorithm (GA) for multivariable surface grinding process optimisation using a multi-objective function model Int J Adv Manuf Technol 17 330 338 10.1007/s001700170167 (Pubitemid 32914797)
    • (2001) International Journal of Advanced Manufacturing Technology , vol.17 , Issue.5 , pp. 330-338
    • Saravanan, R.1    Sachithanandam, M.2
  • 115
    • 0042389492 scopus 로고    scopus 로고
    • Selection of optimum conditions for maximum material removal rate with surface finish and damage as constraints in SiC grinding
    • 10.1016/S0890-6955(03) 00165-2
    • AV Gopal PV Rao 2003 Selection of optimum conditions for maximum material removal rate with surface finish and damage as constraints in SiC grinding Int J Mach Tools Manuf 43 1327 1336 10.1016/S0890-6955(03) 00165-2
    • (2003) Int J Mach Tools Manuf , vol.43 , pp. 1327-1336
    • Gopal, A.V.1    Rao, P.V.2
  • 116
    • 1942505885 scopus 로고    scopus 로고
    • Ant colony algorithm approach for multi-objective optimization of surface grinding operations
    • 10.1007/s00170-002-1533-6
    • N Baskar R Saravanan P Asokan G Prabhaharan 2004 ant colony algorithm approach for multi-objective optimization of surface grinding operations Int J Adv Manuf Technol 23 311 317 10.1007/s00170-002-1533-6
    • (2004) Int J Adv Manuf Technol , vol.23 , pp. 311-317
    • Baskar, N.1    Saravanan, R.2    Asokan, P.3    Prabhaharan, G.4
  • 117
    • 0033132702 scopus 로고    scopus 로고
    • Neural-network approach for predicting hole quality in reaming
    • 10.1016/S0890-6955(98) 00061-3
    • PG Mathews MS Shunmugam 1999 Neural-network approach for predicting hole quality in reaming Int J Mach Tools Manuf 39 723 730 10.1016/S0890-6955(98) 00061-3
    • (1999) Int J Mach Tools Manuf , vol.39 , pp. 723-730
    • Mathews, P.G.1    Shunmugam, M.S.2
  • 118
    • 43849109630 scopus 로고    scopus 로고
    • Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network
    • 10.1016/j.jmatprotec.2006.04.126
    • CC Taso H Hochang 2008 Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network J Mater Process Technol 203 342 348 10.1016/j.jmatprotec.2006.04.126
    • (2008) J Mater Process Technol , vol.203 , pp. 342-348
    • Taso, C.C.1    Hochang, H.2
  • 119
    • 58249132418 scopus 로고    scopus 로고
    • A study of drilling performances with minimum quantity of lubricant using fuzzy logic rules
    • 10.1016/j.mechatronics.2008.08.004
    • AK Nandi JP Davim 2009 A study of drilling performances with minimum quantity of lubricant using fuzzy logic rules Mechatronics 19 218 232 10.1016/j.mechatronics.2008.08.004
    • (2009) Mechatronics , vol.19 , pp. 218-232
    • Nandi, A.K.1    Davim, J.P.2
  • 120
    • 0029309724 scopus 로고
    • Real-time fuzzy logic control for maximizing the tool life of small-diameter drills
    • 10.1016/0165-0114(94) 00261-5
    • FR Biglari XD Fang 1995 Real-time fuzzy logic control for maximizing the tool life of small-diameter drills Fuzzy Sets Syst 72 91 101 10.1016/0165-0114(94) 00261-5
    • (1995) Fuzzy Sets Syst , vol.72 , pp. 91-101
    • Biglari, F.R.1    Fang, X.D.2
  • 121
    • 0030129165 scopus 로고    scopus 로고
    • Drill wear monitoring using neural networks
    • SC Lin CJ Ting 1999 Drill wear monitoring using neural networks Int J Adv Manuf Technol 36 465 475
    • (1999) Int J Adv Manuf Technol , vol.36 , pp. 465-475
    • Lin, S.C.1    Ting, C.J.2
  • 122
    • 0033891712 scopus 로고    scopus 로고
    • In-process prediction of corner wear in drilling operations
    • HS Liu BY Lee YS Tarang 2000 In-process prediction of corner wear in drilling operations Int J Adv Manuf Technol 101 152 158
    • (2000) Int J Adv Manuf Technol , vol.101 , pp. 152-158
    • Liu, H.S.1    Lee, B.Y.2    Tarang, Y.S.3
  • 123
    • 0037402139 scopus 로고    scopus 로고
    • Drilling wear detection and classification using vibration signals and artificial neural network
    • 10.1016/S0890-6955(03) 00023-3
    • I Abu-Mahfouz 2003 Drilling wear detection and classification using vibration signals and artificial neural network Int J Mach Tools Manuf 43 707 720 10.1016/S0890-6955(03) 00023-3
    • (2003) Int J Mach Tools Manuf , vol.43 , pp. 707-720
    • Abu-Mahfouz, I.1
  • 124
    • 29144452580 scopus 로고    scopus 로고
    • Modeling of tool wear in drilling by statistical analysis and neural network
    • 10.1016/j.jmatprotec.2005.04.072
    • C Sanjay ML Neema CW Chin 2005 Modeling of tool wear in drilling by statistical analysis and neural network J Mater Process Technol 170 494 500 10.1016/j.jmatprotec.2005.04.072
    • (2005) J Mater Process Technol , vol.170 , pp. 494-500
    • Sanjay, C.1    Neema, M.L.2    Chin, C.W.3
  • 125
    • 32444448138 scopus 로고    scopus 로고
    • Drill wear monitoring using back propagation neural network
    • DOI 10.1016/j.jmatprotec.2005.10.021, PII S0924013605008939
    • SS Panda AK Singh PSK Chakraborty 2006 Drill wear monitoring using back propagation neural network J Mater Process Technol 172 283 290 10.1016/j.jmatprotec.2005.10.021 (Pubitemid 43227339)
    • (2006) Journal of Materials Processing Technology , vol.172 , Issue.2 , pp. 283-290
    • Panda, S.S.1    Singh, A.K.2    Chakraborty, D.3    Pal, S.K.4
  • 126
    • 34047262880 scopus 로고    scopus 로고
    • Artificial neural network based prediction of drill flank wear from motor current signals
    • DOI 10.1016/j.asoc.2006.06.001, PII S1568494606000482
    • K Patra SK Pal K Bhattacharyya 2007 Artificial neural network based on prediction of drill flank wear motor current signals Appl Soft Comput 7 927 935 10.1016/j.asoc.2006.06.001 (Pubitemid 46551928)
    • (2007) Applied Soft Computing Journal , vol.7 , Issue.3 , pp. 929-935
    • Patra, K.1    Pal, S.K.2    Bhattacharyya, K.3
  • 127
    • 34248996874 scopus 로고    scopus 로고
    • Evaluation of the performance of back propagation and radial basis function neural networks in predicting the drill flank wear
    • 10.1007/s00521-006-0065-7
    • S Garg SK Pal D Chakraborty 2007 Evaluation of the performance of back propagation and radial basis function neural networks in predicting the drill flank wear Neural Comput Appl 16 407 417 10.1007/s00521-006-0065-7
    • (2007) Neural Comput Appl , vol.16 , pp. 407-417
    • Garg, S.1    Pal, S.K.2    Chakraborty, D.3
  • 128
    • 35348863189 scopus 로고    scopus 로고
    • Prediction of drill failure using features extraction in time and frequency domains of feed motor current
    • DOI 10.1016/j.ijmachtools.2007.08.009, PII S089069550700140X
    • YJ Choi MS Park CN Chu 2008 Prediction of drill failure using features extraction in time and frequency domains of feed motor current Int J Mach Tools Manuf 48 29 39 10.1016/j.ijmachtools.2007.08.009 (Pubitemid 47576562)
    • (2008) International Journal of Machine Tools and Manufacture , vol.48 , Issue.1 , pp. 29-39
    • Choi, Y.J.1    Park, M.S.2    Chu, C.N.3
  • 129
    • 0027150408 scopus 로고
    • On multisensor approach in drill wear monitoring
    • 10.1016/S0007-8506(07)62394-4
    • AN Khajavi R Komanduri 1993 On multisensor approach in drill wear monitoring Ann CIRP 42 71 74 10.1016/S0007-8506(07)62394-4
    • (1993) Ann CIRP , vol.42 , pp. 71-74
    • Khajavi, A.N.1    Komanduri, R.2
  • 130
    • 0032205936 scopus 로고    scopus 로고
    • Intelligent detection of drill wear
    • 10.1006/mssp. 1998.0165
    • TI Liu WY Chen 1998 Intelligent detection of drill wear Mech Syst Signal Process 12 863 873 10.1006/mssp. 1998.0165
    • (1998) Mech Syst Signal Process , vol.12 , pp. 863-873
    • Liu, T.I.1    Chen, W.Y.2
  • 131
    • 0032867919 scopus 로고    scopus 로고
    • Drill wear monitoring based on current signals
    • DOI 10.1016/S0043-1648(99)00130-1, PII S0043164899001301
    • X Li SK Tso 1999 Drill wear monitoring based on current signals Wear 231 172 178 10.1016/S0043-1648(99)00130-1 (Pubitemid 29466701)
    • (1999) Wear , vol.231 , Issue.2 , pp. 172-178
    • Li, X.1    Tso, S.K.2
  • 132
    • 0030243351 scopus 로고    scopus 로고
    • A neural network thrust force controller to minimize delaminating during drilling of graphite-epoxy laminates
    • 10.1016/0890-6955(96) 00013-2
    • R Stone K Krishnamurthy 1996 A neural network thrust force controller to minimize delaminating during drilling of graphite-epoxy laminates Int J Mach Tools Manuf 36 985 1003 10.1016/0890-6955(96) 00013-2
    • (1996) Int J Mach Tools Manuf , vol.36 , pp. 985-1003
    • Stone, R.1    Krishnamurthy, K.2
  • 136
    • 0031999346 scopus 로고    scopus 로고
    • Modeling and optimization of drilling process
    • 10.1016/S0924-0136(97)00263-X
    • BY Lee HS Liu YS Tarang 1998 Modeling and optimization of drilling process J Mater Process Technol 74 149 157 10.1016/S0924-0136(97)00263-X
    • (1998) J Mater Process Technol , vol.74 , pp. 149-157
    • Lee, B.Y.1    Liu, H.S.2    Tarang, Y.S.3
  • 137
    • 0034512681 scopus 로고    scopus 로고
    • Fuzzy logic based data selection for the drilling process
    • 10.1016/S0924-0136(00) 00597-5
    • K Hashmi ID Graham B Mills 2000 Fuzzy logic based data selection for the drilling process J Mater Process Technol 108 55 61 10.1016/S0924-0136(00) 00597-5
    • (2000) J Mater Process Technol , vol.108 , pp. 55-61
    • Hashmi, K.1    Graham, I.D.2    Mills, B.3
  • 138
    • 33847103225 scopus 로고    scopus 로고
    • An ant algorithm for optimization of hole-making operations
    • DOI 10.1016/j.cie.2007.01.001, PII S0360835207000125
    • H Ghaiebi M Solimanpur 2007 An ant algorithm for optimization of hole-making operations Comput Ind Eng 52 308 319 10.1016/j.cie.2007.01.001 (Pubitemid 46282348)
    • (2007) Computers and Industrial Engineering , vol.52 , Issue.2 , pp. 308-319
    • Ghaiebi, H.1    Solimanpur, M.2
  • 139
    • 39449097797 scopus 로고    scopus 로고
    • Drilling path optimization by particle swarm optimization algorithm with global convergence characteristics
    • 10.1080/00207540601042480 2333532
    • GY Zhu WB Zhang 2007 Drilling path optimization by particle swarm optimization algorithm with global convergence characteristics Int J Prod Res 46 2299 2311 10.1080/00207540601042480 2333532
    • (2007) Int J Prod Res , vol.46 , pp. 2299-2311
    • Zhu, G.Y.1    Zhang, W.B.2
  • 140
    • 0029756425 scopus 로고    scopus 로고
    • Confidence interval prediction for neural network models
    • 10.1109/72.478409
    • G Chryssolouris M Lee A Ramsey 1996 Confidence interval prediction for neural network models IEEE Trans Neural Netw 7 229 232 10.1109/72.478409
    • (1996) IEEE Trans Neural Netw , vol.7 , pp. 229-232
    • Chryssolouris, G.1    Lee, M.2    Ramsey, A.3
  • 142
    • 46649105274 scopus 로고    scopus 로고
    • An application of physics-based and artificial neural network-based hybrid temperature prediction scheme in a hot strip mill
    • (5 pages)
    • WM Geerdes MAT Alvardo 2008 An application of physics-based and artificial neural network-based hybrid temperature prediction scheme in a hot strip mill J Manuf Sci Eng 130 014501 (5 pages)
    • (2008) J Manuf Sci Eng , vol.130 , pp. 014501
    • Geerdes, W.M.1    Alvardo, M.A.T.2


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