A hybrid intelligent system for fault diagnosis of advanced manufacturing system

REFERENCES

• BAFFES , P. T. 1989 , Nets User‘s Guide ( Lyndon B. Johnson Space Center ).
   Google Scholar
• BAIJPAI , A. 1988 , An expert system model for general-purpose diagnostics of manufacturing equipment . Manufacturing Review , 1 , 180 – 186 .
   Google Scholar
• BENNETT , J. S. , and HOLLANDER , C. R. 1981 , DART An expert system for computer fault diagnosis . Proceedings of the International Joint Conference on Artificial Intelligence , I , 843 – 845 .
   Google Scholar
• BUCHANAN , B. , and SHORTLIFFE , E. 1984 , IT>Rule-Based Expert Systems The MYCIN Experiments of the Stanford Heuristic Programming Project ( Reading , MA Addison-Wesley ).
   Google Scholar
• COHEN , S. M. , MITCHELL , C. M. , and GOVINDARAJ , T. , Analysisaiding the human operator in electronics assembly. In Design for Manufacturability A System Approach to Concurrent Engineering and Ergonomics, edited by M. Helander and M. Nugainachi ( London Taylor & Francis ), pp. 361 – 376 .
   Google Scholar
• KNAPP , G. M. , and WANG , H.-P. 1992 , Machine fault classification A neural network approach . International Journal of Production Research, 30 ( 4 ), 811 – 823 .
   Google Scholar
• NARUO , N. , LEHTO , M. , and SALVENDY , G. 1990 , Development of a knowledge-based decision support systems for diagnosing malfunctions of advanced production equipment . International Journal of Production Research , 28 ( 12 ), 2259 – 2276 .
   Web of Science ®Google Scholar
• PENG , Y. , and REGGIA , J. A. 1990 , Abductive Inference Models for Diagnostic Problem Solving ( New York Springer-Verlag ).
   Google Scholar
• RASMUSSEN , J. 1986 , Information Processing and Human-Machine Interaction An Approach to Cognitive Engineering ( Amsterdam Elsevier ).
   Google Scholar
• RASMUSSEN , J. , and ROUSE , W. B. , 1981 , Human DetectionDiagnosis of System Failures ( New York Plenum Press ).
   Google Scholar
• SEJNOWSKI , T. J. , and ROSENBERG , C. R. 1987 , Parallel networks that learn to pronounce English text . Complex Systems , 1 , 145 – 168 .
   Google Scholar
• SHERIDAN , T. B. 1987 . Supervisory control . In Handbook of Human Factors, edited by G. Salvendy ( New York Wiley ), 1243 – 1268 .
   Google Scholar
• Su , Y.-L. D. 1985 , Modeling fault diagnosis performance on a marine powerplant simulator. PhD thesis School of Industrial and System Engineering , Georgia Institute of Technology , Atlanta , Georgia .
   Google Scholar
• VENKATASUBRAMANIAN , V. , and CHAN , K. 1989 , A neural network methodology for process fault diagnosis . AIChE , 35 ( 12 ), 1993 – 2002 .
   Web of Science ®Google Scholar
• WATANABE , K. , MATSURA , A. M. , KUBOTA , M. , HIMMELBLAU , D. M. , 1989 , Incipient fault diagnosis of chemical process via artificial neural networks . AIChE , 35 ( 11 ), 1803 – 1812 .
   Web of Science ®Google Scholar
• YE , N. , and SALVENDY , G. 1991 , Cognitive engineering based knowledge representation in neural networks . Behaviour & Information Technology , 10 ( 1 ), 403 – 418 .
   Google Scholar
• YE , N. , ZHAO , B. , and SALVENDY , G. 1993 , Neural-networks-aided fault diagnosis in supervisory control of advanced manufacturing systems . International Journal of Advanced Manufacturing Technology , 8 ( 4 ), 200–209.
   Web of Science ®Google Scholar