메뉴 건너뛰기




Volumn 36, Issue 3, 2004, Pages 253-263

Data mining techniques applied to predictive modeling of the knurling process

Author keywords

[No Author keywords available]

Indexed keywords

ASSEMBLY; CUSTOMER SATISFACTION; DATA MINING; MAINTENANCE; MATHEMATICAL MODELS; NEURAL NETWORKS; PRODUCT DESIGN; REGRESSION ANALYSIS;

EID: 1142305317     PISSN: 0740817X     EISSN: None     Source Type: Journal    
DOI: 10.1080/07408170490274214     Document Type: Article
Times cited : (15)

References (35)
  • 1
  • 2
    • 1142271875 scopus 로고    scopus 로고
    • Form Roll Die Corp, Worcester, MA
    • Anon (not dated) Technical Publication K-3.1, Form Roll Die Corp, Worcester, MA.
    • Technical Publication K-3.1
  • 3
    • 0343682041 scopus 로고
    • Reed Rolled Thread Die Company, Worcester, MA
    • Anon (1978) Technical Data for Knurl, Reed Rolled Thread Die Company, Worcester, MA.
    • (1978) Technical Data for Knurl
  • 4
  • 5
    • 0041584086 scopus 로고    scopus 로고
    • Minitab Inc., State College, PA
    • Anon. (2000) Meet Minitab, Minitab Inc., State College, PA.
    • (2000) Meet Minitab
  • 10
    • 0033294087 scopus 로고    scopus 로고
    • A study of the impact of knurling parameters of knurl quality with the design of experiments approach, in conceptual and innovative design for manufacturing
    • Billatos, S.B. and Kim, B.S. (eds.); ASME Press, New York
    • Feng, C.-X. and Tran, C. (1999) A study of the impact of knurling parameters of knurl quality with the design of experiments approach, in Conceptual and Innovative Design for Manufacturing, Billatos, S.B. and Kim, B.S. (eds.), DE-Vol. 103, Proceedings of the 1999 ASME Mechanical Engineering Congress & Exposition, Nashville, TN, ASME Press, New York, pp. 15-26.
    • (1999) Proceedings of the 1999 ASME Mechanical Engineering Congress & Exposition, Nashville, TN , vol.DE-103 , pp. 15-26
    • Feng, C.-X.1    Tran, C.2
  • 11
    • 0036611175 scopus 로고    scopus 로고
    • Digitizing uncertainty modeling for reverse engineering applications: Regression versus neural network
    • Feng, C.-X. and Wang, X.-F. (2002a) Digitizing uncertainty modeling for reverse engineering applications: regression versus neural network. Journal of Intelligent Manufacturing, 13(3), 189-200.
    • (2002) Journal of Intelligent Manufacturing , vol.13 , Issue.3 , pp. 189-200
    • Feng, C.-X.1    Wang, X.-F.2
  • 12
    • 0040081739 scopus 로고    scopus 로고
    • Subset selection in predictive modeling of the CMM digitization uncertainty
    • Feng, C.-X. and Wang, X.-F. (2002b) Subset selection in predictive modeling of the CMM digitization uncertainty. SME Journal of Manufacturing Systems, 21(6), 419-439.
    • (2002) SME Journal of Manufacturing Systems , vol.21 , Issue.6 , pp. 419-439
    • Feng, C.-X.1    Wang, X.-F.2
  • 13
    • 0037233403 scopus 로고    scopus 로고
    • Surface roughness predictive modeling: Neural networks versus regression
    • Feng, C.-X. and Wang, X.-F. (2003) Surface roughness predictive modeling: neural networks versus regression. IIE Transactions, 35(1), 11-27.
    • (2003) IIE Transactions , vol.35 , Issue.1 , pp. 11-27
    • Feng, C.-X.1    Wang, X.-F.2
  • 14
    • 0040482037 scopus 로고    scopus 로고
    • Neural networks predictive modeling of honing surface roughness parameters defined by ISO13565
    • Feng, C.-X., Wang, X.-F. and Yu, Z. (2002) Neural networks predictive modeling of honing surface roughness parameters defined by ISO13565. SME Journal of Manufacturing Systems, 21(5), 395-408.
    • (2002) SME Journal of Manufacturing Systems , vol.21 , Issue.5 , pp. 395-408
    • Feng, C.-X.1    Wang, X.-F.2    Yu, Z.3
  • 15
    • 77956014698 scopus 로고    scopus 로고
    • Neural networks predictive modeling of turning surface roughness parameters defined by ISO13565
    • Society of Manufacturing Engineers, Dearborn, MI, Technical paper MS03-202
    • Feng, C.-X. and Yu, Z. (2003) Neural networks predictive modeling of turning surface roughness parameters defined by ISO13565, in Transactions of NAMRI/SME, Society of Manufacturing Engineers, Dearborn, MI, Technical paper MS03-202.
    • (2003) Transactions of NAMRI/SME
    • Feng, C.-X.1    Yu, Z.2
  • 29
    • 0002215771 scopus 로고    scopus 로고
    • Optimum design based on mathematical model and neural network to predict weld parameters for fillet joints
    • Moon, H.-S. and Na, S.-J. (1997) Optimum design based on mathematical model and neural network to predict weld parameters for fillet joints. Journal of Manufacturing Systems, 16(1), 13-23.
    • (1997) Journal of Manufacturing Systems , vol.16 , Issue.1 , pp. 13-23
    • Moon, H.-S.1    Na, S.-J.2
  • 30
    • 0031706783 scopus 로고    scopus 로고
    • A neural network process model for abrasive flow machining operations
    • Petri, K.L., Billo, R.E. and Bidanda, B. (1998) A neural network process model for abrasive flow machining operations. Journal of Manufacturing Systems, 17(1), 52-64.
    • (1998) Journal of Manufacturing Systems , vol.17 , Issue.1 , pp. 52-64
    • Petri, K.L.1    Billo, R.E.2    Bidanda, B.3
  • 31
    • 0031336193 scopus 로고    scopus 로고
    • Cost estimation predictive modeling: Regression versus neural network
    • Smith, A.E. and Mason, A.K. (1997) Cost estimation predictive modeling: regression versus neural network. The Engineering Economist, 42(2), 137-161.
    • (1997) The Engineering Economist , vol.42 , Issue.2 , pp. 137-161
    • Smith, A.E.1    Mason, A.K.2
  • 32
    • 0032140934 scopus 로고    scopus 로고
    • Bias and variance of validation methods for function approximation neural networks under conditions of sparse data
    • Twomey, J.M. and Smith, A.E. (1998) Bias and variance of validation methods for function approximation neural networks under conditions of sparse data. IEEE Transactions on Systems, Man and Cybernetics, Part C, 28(3), 417-430.
    • (1998) IEEE Transactions on Systems, Man and Cybernetics, Part C , vol.28 , Issue.3 , pp. 417-430
    • Twomey, J.M.1    Smith, A.E.2
  • 34
    • 0034627923 scopus 로고    scopus 로고
    • Prediction of die casting process parameters by using an artificial neural network model for zinc alloy
    • Yarlagadda, P.K.D.V. (2000) Prediction of die casting process parameters by using an artificial neural network model for zinc alloy. International Journal of Production Research, 38(1), 119-134.
    • (2000) International Journal of Production Research , vol.38 , Issue.1 , pp. 119-139
    • Yarlagadda, P.K.D.V.1
  • 35
    • 0000414908 scopus 로고
    • Applications of neural network applications in manufacturing: A state-of-the-art survey
    • Zhang, H.-C. and Huang, S.H. (1995) Applications of neural network applications in manufacturing: a state-of-the-art survey. International Journal of Production Research, 33, 705-728.
    • (1995) International Journal of Production Research , vol.33 , pp. 705-728
    • Zhang, H.-C.1    Huang, S.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.