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Volumn 19, Issue 2, 2008, Pages 233-240

Application of artificial neural network for determination of standard time in machining

Author keywords

Machining; Neural network; Sensitivity analysis; Standard time

Indexed keywords

MACHINING; MATHEMATICAL MODELS; SENSITIVITY ANALYSIS;

EID: 40849100013     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-008-0076-6     Document Type: Article
Times cited : (25)

References (35)
  • 1
    • 3242706865 scopus 로고    scopus 로고
    • Application of neural networks to heuristic scheduling algorithms
    • Akyol D. (2004). Application of neural networks to heuristic scheduling algorithms. Computers and Industrial Engineering 46, 679-696
    • (2004) Computers and Industrial Engineering , vol.46 , pp. 679-696
    • Akyol, D.1
  • 2
    • 4344709594 scopus 로고    scopus 로고
    • Pattern recognition of control charts using artificial neural networks-analyzing the effect of training parameters
    • Barghash M., Santarisi N. (2004). Pattern recognition of control charts using artificial neural networks-analyzing the effect of training parameters. Journal of Intelligent Manufacturing 15, 635-644
    • (2004) Journal of Intelligent Manufacturing , vol.15 , pp. 635-644
    • Barghash, M.1    Santarisi, N.2
  • 4
    • 23044501999 scopus 로고    scopus 로고
    • A neuro-genetic approach to design and planning of manufacturing cell
    • Cakar T., Yildrim M. (2005). A neuro-genetic approach to design and planning of manufacturing cell. Journal of Intelligent Manufacturing 16, 453-462
    • (2005) Journal of Intelligent Manufacturing , vol.16 , pp. 453-462
    • Cakar, T.1    Yildrim, M.2
  • 6
    • 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
    • Ezugwu E.O., Fadare D.A., Bonney J., Da Silva R.B., Sales W.F. (2005). Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural network. International Journal of Machine Tools and Manufacture 45, 1375-1385
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , pp. 1375-1385
    • Ezugwu, E.O.1    Fadare, D.A.2    Bonney, J.3    Da Silva, R.B.4    Sales, W.F.5
  • 8
    • 0036611175 scopus 로고    scopus 로고
    • Digitising uncertainty modelling for reverse engineering applications: Regression versus neurla networks
    • Feng C., Wang X. (2002). Digitising uncertainty modelling for reverse engineering applications: regression versus neurla networks. Journal of Intelligent Manufacturing 13, 189-199
    • (2002) Journal of Intelligent Manufacturing , vol.13 , pp. 189-199
    • Feng, C.1    Wang, X.2
  • 9
    • 0033221564 scopus 로고    scopus 로고
    • A neural network approach to characterize pattern parameters in process control charts
    • Guh R.S., Tannock J.D. (1999). A neural network approach to characterize pattern parameters in process control charts. Journal of Intelligent Manufacturing 10, 449-462
    • (1999) Journal of Intelligent Manufacturing , vol.10 , pp. 449-462
    • Guh, R.S.1    Tannock, J.D.2
  • 12
    • 0038789161 scopus 로고    scopus 로고
    • A fuzzy neural network approach to machine condition monitoring
    • Javadpour R., Knapp G. (2003). A fuzzy neural network approach to machine condition monitoring. Computers and Industrial Engineering 45, 323-330
    • (2003) Computers and Industrial Engineering , vol.45 , pp. 323-330
    • Javadpour, R.1    Knapp, G.2
  • 13
    • 0032130978 scopus 로고    scopus 로고
    • An approach to integrating intelligent diagnostics and supervision of machine tools
    • Jedrzejewski J., Kwaśny W. (1998). An approach to integrating intelligent diagnostics and supervision of machine tools. Journal of Intelligent Manufacturing 9, 295-302
    • (1998) Journal of Intelligent Manufacturing , vol.9 , pp. 295-302
    • Jedrzejewski, J.1    Kwaśny, W.2
  • 14
    • 0035272432 scopus 로고    scopus 로고
    • Dynamic planning model for determining cutting parameters using neural networks in feature-based process planning
    • Joo J., Yi G., Cho H., Choi Y. (2001). Dynamic planning model for determining cutting parameters using neural networks in feature-based process planning. Journal of Intelligent Manufacturing 12, 13-29
    • (2001) Journal of Intelligent Manufacturing , vol.12 , pp. 13-29
    • Joo, J.1    Yi, G.2    Cho, H.3    Choi, Y.4
  • 15
    • 0036681782 scopus 로고    scopus 로고
    • Manufacturing cost estimation for machined parts based on manufacturing features
    • Jung J. (2002). Manufacturing cost estimation for machined parts based on manufacturing features. Journal of Intelligent Manufacturing 13, 227-238
    • (2002) Journal of Intelligent Manufacturing , vol.13 , pp. 227-238
    • Jung, J.1
  • 20
    • 0034292123 scopus 로고    scopus 로고
    • A neural network approach for defect identification and classification on leather fabric
    • Kwak C., Ventura J., Tofang-Sazi K. (2000). A neural network approach for defect identification and classification on leather fabric. Journal of Intelligent Manufacturing 11, 485-499
    • (2000) Journal of Intelligent Manufacturing , vol.11 , pp. 485-499
    • Kwak, C.1    Ventura, J.2    Tofang-Sazi, K.3
  • 21
    • 0034207429 scopus 로고    scopus 로고
    • Intelligent setup planning in manufacturing by neural networks based approach
    • Ming X., Mak K. (2000). Intelligent setup planning in manufacturing by neural networks based approach. Journal of Intelligent Manufacturing 11, 311-331
    • (2000) Journal of Intelligent Manufacturing , vol.11 , pp. 311-331
    • Ming, X.1    Mak, K.2
  • 23
    • 0032598808 scopus 로고    scopus 로고
    • Manufacturing features recognition using backpropagation neural networks
    • Onwubolu G. (1999). Manufacturing features recognition using backpropagation neural networks. Journal of Intelligent Manufacturing 10, 289-299
    • (1999) Journal of Intelligent Manufacturing , vol.10 , pp. 289-299
    • Onwubolu, G.1
  • 24
    • 3543131353 scopus 로고    scopus 로고
    • Hybrid neural network and genetic algorithm based machining recognition
    • Ozturk N., Ozturk F. (2004). Hybrid neural network and genetic algorithm based machining recognition. Journal of Intelligent Manufacturing 15, 287-298
    • (2004) Journal of Intelligent Manufacturing , vol.15 , pp. 287-298
    • Ozturk, N.1    Ozturk, F.2
  • 25
    • 34547291495 scopus 로고    scopus 로고
    • Neural network with genetic algorithms for the monthly electric energy consumption and peak power middle-term forecasting
    • Piotrowski P. (2002). Neural network with genetic algorithms for the monthly electric energy consumption and peak power middle-term forecasting. Journal of Applied Computer Science 10, 105-115
    • (2002) Journal of Applied Computer Science , vol.10 , pp. 105-115
    • Piotrowski, P.1
  • 27
    • 0032598803 scopus 로고    scopus 로고
    • Artificial intelligence and expert systems applications in new product development-a survey
    • Rao S., Nahm A., Shi Z., Deng X., Syamil A. (1999). Artificial intelligence and expert systems applications in new product development-a survey. Journal of Intelligent Manufacturing 10, 231-244
    • (1999) Journal of Intelligent Manufacturing , vol.10 , pp. 231-244
    • Rao, S.1    Nahm, A.2    Shi, Z.3    Deng, X.4    Syamil, A.5
  • 28
    • 0342845324 scopus 로고    scopus 로고
    • The performance of workload rules for order acceptance in batch chemical manufacturing
    • Reeymakers W., Bertrand W., Fransoo J. (2000). The performance of workload rules for order acceptance in batch chemical manufacturing. Journal of Intelligent Manufacturing 11, 217-228
    • (2000) Journal of Intelligent Manufacturing , vol.11 , pp. 217-228
    • Reeymakers, W.1    Bertrand, W.2    Fransoo, J.3
  • 29
  • 30
    • 14844354357 scopus 로고    scopus 로고
    • The training of neural networks to model manufacturing processes
    • Suthomaya W., Tannock J. (2005). The training of neural networks to model manufacturing processes. Journal of Intelligent Manufacturing 16, 39-51
    • (2005) Journal of Intelligent Manufacturing , vol.16 , pp. 39-51
    • Suthomaya, W.1    Tannock, J.2
  • 31
    • 0038341744 scopus 로고    scopus 로고
    • Fuzzy neural networks for intelligent design retrieval using associative manufacturing features
    • Tsai C., Chang A. (2003). Fuzzy neural networks for intelligent design retrieval using associative manufacturing features. Journal of Intelligent Manufacturing 14, 183-195
    • (2003) Journal of Intelligent Manufacturing , vol.14 , pp. 183-195
    • Tsai, C.1    Chang, A.2
  • 32
    • 21144434131 scopus 로고    scopus 로고
    • Manufacturing process performance prediction by integrating crisp and granular information
    • Ullah S., Harib K. (2005). Manufacturing process performance prediction by integrating crisp and granular information. Journal of Intelligent Manufacturing 16, 317-330
    • (2005) Journal of Intelligent Manufacturing , vol.16 , pp. 317-330
    • Ullah, S.1    Harib, K.2
  • 33
    • 0033892552 scopus 로고    scopus 로고
    • Towards intelligent setting of process parameters for layered manufacturing
    • Wang W., Conley J., Yan Y. (2000). Towards intelligent setting of process parameters for layered manufacturing. Journal of Intelligent Manufacturing 11, 65-74
    • (2000) Journal of Intelligent Manufacturing , vol.11 , pp. 65-74
    • Wang, W.1    Conley, J.2    Yan, Y.3
  • 34
    • 0036536909 scopus 로고    scopus 로고
    • A feedforward multi-layer neural network for machine cell formation in computer integrated manufacturing
    • Willow C. (2002). A feedforward multi-layer neural network for machine cell formation in computer integrated manufacturing. Journal of Intelligent Manufacturing 13, 75-87
    • (2002) Journal of Intelligent Manufacturing , vol.13 , pp. 75-87
    • Willow, C.1
  • 35
    • 0034516536 scopus 로고    scopus 로고
    • Tool condition monitoring using reflectance of chip surface and neural network
    • Yeo S., Khoo L., Neo S. (2000). Tool condition monitoring using reflectance of chip surface and neural network. Journal of Intelligent Manufacturing 11, 507-514
    • (2000) Journal of Intelligent Manufacturing , vol.11 , pp. 507-514
    • Yeo, S.1    Khoo, L.2    Neo, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.