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Cognition, Technology & Work

, Volume 5, Issue 2, pp 67–81 | Cite as

Making sense of the abstraction hierarchy in the power plant domain

  • Morten Lind
Original Article

Abstract

The paper discusses the abstraction hierarchy proposed by Rasmussen [(1986) Information processing and human-machine interaction, North-Holland] for design of human-machine interfaces for supervisory control. The purpose of the abstraction hierarchy is to represent a work domain by multiple levels of means-end and part-whole abstractions. It is argued in the paper that the abstraction hierarchy suffers from both methodological and conceptual problems. A cluster of selected problems are analyzed and illustrated by concrete examples from the power plant domain. It is concluded that the semantics of the means-end levels and their relations are vaguely defined and therefore should be improved by making more precise distinctions. Furthermore, the commitment to a fixed number of levels of means-end abstractions should be abandoned and more attention given to the problem of level identification in the model-building process. It is also pointed out that attempts to clarify the semantics of the abstraction hierarchy will invariably reduce the range of work domains where it can be applied.

Keywords

Abstraction hierarchies Automation design Cognitive engineering Plant modeling Supervisory control 

Notes

Acknowledgements

The Danish Foundation for Basic Research supported the present work through a contract with the Center for Human-Machine Interaction (CHMI).

References

  1. Bisantz AM, Vicente KJ (1994) Making the abstraction hierarchy concrete. Int J Hum-Comput Stud 40:83–117Google Scholar
  2. Bunge M (1989) Ethics: the good and the right. Treatise on basic philosophy, vol 8. Reidel, DordrechtGoogle Scholar
  3. Fang M, Lind M (1995) Model based reasoning using MFM. In: Proceedings of Pacific-Asian conference on expert systems, Huangshan, China, 15–18 May 1995Google Scholar
  4. Gofuku A, Lind M (1994) Combining multilevel flow modelling and hybrid phenomena theory for efficient design of engineering systems. In: Proceedings of the 2nd IFAC workshop on computer structures integrating AI/KBS systems in process control, Lund, Sweden, 10–12 August 1994Google Scholar
  5. Jørgensen SS (1993) Generic MFM models for use in fault diagnosis of ship system's machinery. PhD thesis (part I), Institute of Automatic Control Systems, Technical University of DenmarkGoogle Scholar
  6. Keeney RL (1992) Value focused thinking. Harvard University Press, Cambridge, MAGoogle Scholar
  7. Larsen MN (1993) Deriving action sequences for start-ups using multilevel flow models. PhD thesis, Institute of Automatic Control Systems, Technical University of DenmarkGoogle Scholar
  8. Larsson JE (1996) Diagnosis based on explicit means-end models. Artif Intell 80:29–93CrossRefGoogle Scholar
  9. Lind M (1993) Functional architectures for systems management and control. In: Lind M et al (eds) Interactive planning for integrated supervision and control in complex plant. Final report from CEC JRC project: 4937-92-08-ED ISP DKGoogle Scholar
  10. Lind M (1994) Modelling goals and functions of complex industrial plant. J Appl Artif Intell 8:259–283Google Scholar
  11. Lind M (1996a) Interpretation problems in modelling complex artifacts for diagnosis. In: Proceedings of cognitive system engineering for process control, CSEPC'96, Kyoto, Japan, 12–15 November 1996Google Scholar
  12. Lind M (1996b) Status and challenges of intelligent plant control. Annu Rev Control 20:22–31Google Scholar
  13. Lind M (1999a) Making sense of the abstraction hierarchy. In: Proceedings of cognitive science approaches to process control, CSAPC´99, Villeneuve d'Ascq, France, 21–24 September 1999Google Scholar
  14. Lind M (1999b) Plant modelling for human supervisory control. Transactions of the Institute of Measurement and Control, Vol 21. No 4/5, pp 177–180Google Scholar
  15. Mellor DH (1995) The facts of causation. Routledge, LondonGoogle Scholar
  16. Miller A, Sanderson P (2000) Modelling "deranged" physiological systems for ICU information system design. In: Human Factors and Ergonomics Society (HFES/IEA 2000), San Diego, CA. 30 July–4 August 2000Google Scholar
  17. Nagel E (1961) The structure of science: problems in the logic of scientific explanation. Harcourt, Brace, New YorkGoogle Scholar
  18. Pedersen CR (1999) A systematic approach to design of process displays. PhD thesis. Department of Automation, Technical University of DenmarkGoogle Scholar
  19. Petersen J. (2000a) Knowledge based support for situation assessment in human supervisor control. PhD thesis, Department of Automation, Technical University of DenmarkGoogle Scholar
  20. Petersen J (2000b) Focus and causal reasoning in disturbance management of complex dynamic systems. In: Proceedings of the 19th European annual conference on human decision making and manual control, Ispra, Italy, 26–28 June 2000Google Scholar
  21. Rasmussen J (1986) Information processing and human-machine interaction. North-Holland, New YorkGoogle Scholar
  22. Rasmussen J, Lind M (1981) Coping with complexity. In: European conference on human decision making and manual control, Delft, Holland (Also published as Risø-M-2293. Risø National Laboratory, Denmark, 1981)Google Scholar
  23. Rasmussen J, Pejtersen AM, Goodstein LP (1994) Cognitive systems engineering. Wiley, New YorkGoogle Scholar
  24. Rescher N (1966) Aspects of action. In: Rescher N (ed) The logic of decision and action. University of Pittsburgh Press, PittsburghGoogle Scholar
  25. Rescher N (1996) Process metaphysics: an introduction to process philosophy. State University of New York Press, New YorkGoogle Scholar
  26. Sørensen M (1997) Object based large scale reuse in industrial systems design. PhD thesis, Department of Automation, Technical University of DenmarkGoogle Scholar
  27. Van Passen R (1996) Visualisation of process means-ends hierarchies for advanced man-machine interfaces. Final report project ERBBRE2CT943085, Universität Gesamthochschule KasselGoogle Scholar
  28. Vicente KJ (1999) Cognitive work analysis: towards safe productive and healthy computer-based work. Erlbaum, Mahwah, NJGoogle Scholar
  29. Vicente KJ, Rasmussen J (1992) Ecological interface design: theoretical foundations. IEEE Trans Syst Man Cybernet SMC-22:589–606Google Scholar
  30. Von Wright GH (1963) Norm and action. Routledge & Kegan Paul, LondonGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2003

Authors and Affiliations

  1. 1.Center for Human-Machine Interaction, Ørsted DTU, AutomationTechnical University of DenmarkLyngbyDenmark

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