An automated fault diagnosis for manufacturing process monitoring and control

International Journal of Modelling and Simulation

Volumn 16, Issue 4, 1996, Pages 200-209

  Leem, Choon Seong ^a  

^a Yonsei University   (South Korea)

Author keywords

Adaptive feature scaling; Feature analysis; Neural networks; Process monitoring and control

Indexed keywords

EID: 2942686556     PISSN: 02286203     EISSN: None     Source Type: Journal    
DOI: 10.1080/02286203.1996.11760300     Document Type: Article

References (21)

1. V.P. Nelson & B.D. Carroll, Tutorial: Fault-tolerant computing (IEEE Computer Society Press, 1987).
2. H. Pham, Introduction, in Fault-tolerant software systems: Techniques and applications, ed. H, Pham (IEEE Computer Society Press, 1992).
3. Y. Ito, Conceptualizing the future factory system, Manufacturing Review, 1(4), 1988, 252-258.
4. H.K. Tonshoff, J.P. Wulfsberg, H.J.J. Kals, & W. Koenig, Developments and trends in monitoring and control of machining processes, Annals of the CIRP, 32(2), 1988, 611-622.
5. R. Tanner & N. Loh, A taxonomy of multi-sensor fusion, J. Manufacturing Systems, 11(5), 1992, 314-325.
6. D.A. Dornfeld, Sensor fusion, in Handbook of intelligent sensor for industrial automation, ed. N. Zuech (Reading: Addison-Wesley, 1992).
7. R.C. Luo & M.G. Kay, Multisensor integration and fusion in intelligent systems, IEEE Trans. on Systems, Man, and Cybernetics, 19(5), 1989, 901-931.
8. S. Spiewak, A predictive monitoring and diagnosis system for manufacturing, Annals of the CIRP, 40(1), 1991, 401-404.
9. G. Chryssolouris & M. Domroese, Experimental study of strategies for integrating sensor information in machining, Annals of the CIRP, 38(1), 1989, 425-428.
10. J. Lee & B.M. Kramer, Analysis of machine degradation using a neural network based pattern discrimination model, J. Manufacturing Systems, 12(5), 1993, 379-387.
11. L.I. Burke & S. Rangwala, Tool condition monitoring in metal cutting: A neural network approach, J. Intelligent Manufacturing, 2, 1991, 269-280.
12. D. Rumelhart, G. Hinton, & R. Williams, Learning representations by backpropagating errors, Nature, 323, 1986, 533-536.
13. D. Rumelhart & D. Zipser, Feature discovery by competitive learning, Cognitive Science, 9, 1985, 75-112.
14. J. Hertz, A. Krogh, & R.G. Palmer, Introduction to the theory of neural computation (Redwood City: Addison-Wesley, 1991).
15. C.S. Leem, D.A. Domfeld, & S.E. Dreyfus, A customized neural network for sensor fusion in on-line monitoring of cutting tool wear, ASME J. Engineering for Industry, 117, 1994, 152-159.
16. R.A. Fisher, The use of multiple measurements in taxonomic problems, Annals of Eugenics, 7, 1936, 179-188.
17. F. Rosenblatt, Principles of neurodynamics (Washington, DC: Spartan, 1962).
18. C.S. Leem, Attentional control through feature analysis for competitive-learning-based pattern classification, IEEE Trans. on Systems, Man, and Cybernetics, forthcoming.
19. J.B. MacQueen, Some methods for classification and analysis of multivariate observations, Proc. 5th MSP Symp., 1, Berkeley, CA, 1965, 281-297.
20. H. Duda & P. Hart, Pattern classification and scene analysis (New York: John Wiley, 1973).
21. S. Weiss & C. Kulikowski, Computer systems that learn (San Mateo, CA: Morgan Kaufmann, 1991).