Skip to main content
SpringerLink
Log in

Industrial Applications of Model-Based Approaches to Fault Diagnosis

  • Chapter
Proceedings of the Thirtieth International MATADOR Conference

Summary

This paper describes the research undertaken to determine the impact that model-based approaches to fault diagnosis have made in the industrial environment. To verify the hypothesis that few if any model-based approaches were finding practical applications, an investigation was conducted. The results of the investigation indicated that whilst most systems had been applied to genuine, rather than hypothetical, devices only one system had been implemented in the workplace. Furthermore, this paper identifies some of the reasons for the lack of practical applications of the model-based approach. The reasons for the successful industrial implementation of one model-based diagnostic system (MIDAS) are presented. Finally, it is concluded that there is a genuine need to develop and evaluate model-based systems in an industrial context to determine whether their potential benefits can be realised in practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. E. TURBAN (1988) Decision Support and Expert Systems, Macmillan, New York.

    Google Scholar 

  2. J. McDERMOTT (1982) R1: A Rule Based Configurer of Computer Systems, Artificial Intelligence, Vol. 9, No. 1, pp 39–88.

    Article  Google Scholar 

  3. R. KERR (1991) Knowledge-based Manufacturing Management, Addison-Wesley, Singapore.

    Google Scholar 

  4. B.G. BUCHANAN, D. BARSTOW, R. BECHTEL, J. BENNET, W. CLANCEY, C. KUL1KOWSKI, T. MITCHELL and D.A. WATERMAN (1983) Constructing an Expert System, in Building Expert Systems, (Eds) Hayes-Roth, F., Waterman, D.A. and Lenet, D.B., Addison-Wesley, Reading

    Google Scholar 

  5. C. PRICE (1992) Practical Model-based Reasoning, AI Intelligence, February, pp 16–17.

    Google Scholar 

  6. D.G. BOBROW (1984) Qualitative Reasoning about Physical Systems: An Introduction, Artificial Intelligence, Vol. 24, No. 3, pp 1–5.

    Article  Google Scholar 

  7. G. GUIDA (1985) Reasoning about Physical Systems: Shallow versus Deep Models, in Expert Systems and Optimization in Process Control, (Eds) Mamandini, A., and Efstathiou, J., Technical Press.

    Google Scholar 

  8. C.J. PRICE (1988) Developing a Qualitative Representation of Mechanical Devices for use in Diagnosis, Engineering Applications of Al, Vol. 1, June, pp 87–96.

    Google Scholar 

  9. P. TORASSO and L. CONSOLE (1989) Diagnostic Problem Solving, North Oxford Academic Publishers.

    Google Scholar 

  10. C.J. PRICE and M. LEE (1988) Applications of Deep Knowledge, Artificial Intelligence in Engineering, Vol. 3, No. 1, pp 12–17.

    Article  Google Scholar 

  11. K. KEMPF (1988), in Intelligent Manufacturing, (Ed) M. Oliff, Benjamin Cummings.

    Google Scholar 

  12. J.C. KUNZ, M.J. STELZNER and M.D. WILLIAMS (1989) From Classic Expert Systems to Models: Introduction to a Methodology for Building Model-based Systems, in Topics in Expert Systems Design, (Eds) Guida, G. and Tasso, C., Elsevier North Holland.

    Google Scholar 

  13. C. PRICE and J. HUNT (1990) Automating FMEA through Multiple Models, UCW Technical Report No. UCW-TR-173-91, University College Wales.

    Google Scholar 

  14. B. DRABBLE and C. WILLIAMS (1991), Qualitative Reasoning in Engineering, Artificial Intelligence Applications Institute, February (1991).

    Google Scholar 

  15. R. DAVIS and W. HAMSCHER (1988)Model-based Reasoning, in Exploring A.1., (Ed) Shrobe H.E., Morgan Kauffman.

    Google Scholar 

  16. R. DAVIS (1984) Diagnostic Reasoning based upon Structure and Behaviour, Artificial Intelligence, Vol. 24, No. 3, pp 347–410.

    Article  Google Scholar 

  17. M.R. GENESERETH (1984) The use of Design Descriptions in Automated Diagnosis, Artificial Intelligence, Vol. 24, No. 3, pp 411–436.

    Article  MathSciNet  Google Scholar 

  18. J. De KLEER, and B.C. WILLIAMS (1987) Diagnosing Multiple Faults, Artificial Intelligence, Vol. 32, No. 1, pp 97–130.

    Article  MATH  Google Scholar 

  19. R. REITER (1987) A Theory of Diagnosis from First Principles, Artificial Intelligence, Vol. 32, No. 1, pp 57–96.

    Article  MathSciNet  MATH  Google Scholar 

  20. R. MILNE (1989) The Theory of Responsibilities, SIGART Newsletter, No. 93, pp 25–29.

    Google Scholar 

  21. P.K. FINK and J.C. LUSTH (1987) Expert Systems and Diagnostic Expertise in the Mechanical and Electrical Domains, IEEE Transactions on Systems, Man and Cybernetics, Vol. 17, No. 3, pp 340–349.

    Article  Google Scholar 

  22. J.E. HUNT (1989) A Qualitative Diagnostician for Mechanical Devices, Engineering Applications of Artificial Intelligence, Vol. 2, March, pp 28–39.

    Article  Google Scholar 

  23. C. KOUKOULIS (1985) A Frame-based Method for Fault Diagnosis, in Expert Systems and Optimization in Process Control, (Eds) Mamandini, A., and Efstathiou, J., Technical Press.

    Google Scholar 

  24. J.J. LEARY and P.J. GAWTHROP (1987) Process Fault Detection using Constraint Suspension, IEE Proceedings, Vol. 134, Pt. D, No. 4, pp 264–271.

    Article  MATH  Google Scholar 

  25. M.A. BRAMER, D. MUIRDEN, J. PIERCE, J.C. PLATTS, and D.L. VIPOND (1988) FAUST — An Expert System for Diagnosing Faults in an Electricity Supply System, in Research & Development in Expert Systems 5, (Eds) Kelly, B. and Rector, A., Cambridge University Press.

    Google Scholar 

  26. T.F. PETTI, J. KLEIN and P.S. DHURJATI (1990) Diagnostic Model Processor:using Deep Knowledge for Process Fault Detection, Comput. Chem. Eng., Vol. 12, pp. 891–902.

    Google Scholar 

  27. J.J KELLY, AND K.M. FORD (1990) Diagnosis using Model-based Reasoning by Constraint Propagation: A Preliminary Report on Monitoring NASA Space Shuttle Liquid Hydrogen Loading, International Journal of Expert Systems, Vol. 3, No. 2., pp 87–104.

    Google Scholar 

  28. R. MILNE (1991) Second Generation Expert Systems: The Applications Gap, Avignon’ 91 Second Generation Expert Systems Conference.

    Google Scholar 

  29. N.F. DOHERTY (1992) Knowledge-based Approaches to Fault Diagnosis, Ph. D. Thesis, University of Bradford.

    Google Scholar 

  30. K. OLDHAM, R.P. MAIN, J.M. COOPER, and N.F. DOHERTY (1991) “DIPLOMA — The Seal of Approval”, Applications of A.I. in Engineering 6, (Eds) Rzevski, G. and Adey, R.A., Elsevier, Barking.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Loughborough University Business School, L.U.T., UK

    N. F. Doherty

  2. Manufacturing Division, Dept. of Mech. Eng., UMIST, UK

    A. K. Kochhar

Authors
  1. N. F. Doherty
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. K. Kochhar
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Manufacturing Division, Department of Mechanical Engineering, UMIST, UK

    A. K. Kochhar (Lucas Professor of Manufacturing Systems Engineering) (Lucas Professor of Manufacturing Systems Engineering)

Copyright information

© 1993 Department of Mechanical Engineering University of Manchester Institute of Science and Technology

About this chapter

Cite this chapter

Doherty, N.F., Kochhar, A.K. (1993). Industrial Applications of Model-Based Approaches to Fault Diagnosis. In: Kochhar, A.K. (eds) Proceedings of the Thirtieth International MATADOR Conference. Palgrave, London. https://doi.org/10.1007/978-1-349-13255-3_42

Download citation

  • DOI: https://doi.org/10.1007/978-1-349-13255-3_42

  • Publisher Name: Palgrave, London

  • Print ISBN: 978-1-349-13257-7

  • Online ISBN: 978-1-349-13255-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation