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Making control systems visible

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Abstract

In this paper we discuss how to support interface design of automatic control systems in a systematic way, that is, how to identify the information that should be displayed in a cognitive relevant way and how to visualize this information content in the interface efficiently. First, a means-ends hierarchical structure is adopted to build the functional model of a control system. Then, a set of functional primitives is proposed, and their behavioural explanations are given. These primitives are used to describe the functions in a functional model of a control system. Based on the functional model, the necessary information to be visualized in the interface can then be identified. Third, a library of graphical presentations for the set of functional primitives is set up. To overcome the problem of display complexity and improve operators’ cognitive workload, the concept of “functional macro” is adopted. Furthermore, several principles are proposed to explain how to map a functional model to interface displays. Finally, how to use this approach to support interface design of automatic control systems is explained in detail by using the electrical and hydraulic controller (EHC) of a nuclear power plant (NPP) as an example. A simple experiment showed that the display design of EHC in this study could be more helpful to identify the modes of EHC than a SSSI design. Reusability of the set of functional primitives and their graphical presentations make this approach possible to support designing displays of various control systems.

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References

  • Bainbridge L (1987) Ironies of automation. In: Rasmussen J, Duncan K, Leplat J (eds) New technology and human error. Wiley, New York

  • Bennett KB, Flach JM (1992) Graphical displays: implications for divided attention, focused attention, and problem solving. Hum Fact 34:513–533

    CAS  Google Scholar 

  • Bennett KB, Toms ML, Woods DD (1993) Emergent features and graphical elements: designing more effective configural displays. Hum Fact 35:71–97

    Google Scholar 

  • Birky GJ, McAvoy TY, Modarres M (1988) An expert system for distillation control design. Comput Chem Eng 12:1045–1063

    Article  CAS  Google Scholar 

  • Dorf RC (1992) Modern control systems. Addison-Wesley, Reading, MA

  • Endsley MR (1996) Automation and situation awareness. In: Parasuraman R, Mouloua M (eds) Automation and human performance: theory and applications. Lawrence Erlbaum, New Jersey, pp 183–200

  • Endsley MR, Karber DB (1999) Level of automation effects on performance, situation awareness and workload in a dynamic control task. Ergonomics 42:462–492

    Article  CAS  PubMed  Google Scholar 

  • Endsley MR, Kiris E (1995) The out-of-the-loop performance problem and level of control in automation. Hum Fact 37:381–394

    Google Scholar 

  • Goodstein LP (1985) Functional alarming and information retrieval. Technical report Risø-M-2511. Risø National Laboratory, Roskilde, Denmark

  • Guerlain S, Jamieson GA, Bullemer P, Blair R (2002) The MPC elucidator: a case study in the design for human–automation interaction. IEEE Trans Syst Man Cybernet A 32:25–40

    Article  Google Scholar 

  • Klatzky (1978) Human memory: structures and process. Freeman, San Francisco

    Google Scholar 

  • Lambert M, Biera B, Martel G (1999) Application of functional analysis technique to supervisory systems. Reliab Eng Syst Safe 64:209–224

    Article  Google Scholar 

  • Lind M (1994) Modeling goals and functions of complex industrial plants. Appl Art Intell 8:259–284

    Google Scholar 

  • Lind M (1999) Plant modeling for human supervisory control. Trans Inst Meas Contr 21:171–180

    Google Scholar 

  • Liu Q, Nakata K, Furuta K (2002) Display design of process systems based on functional modeling. Cognit Technol Work 4:48–63

    Article  Google Scholar 

  • Moray M (1986) Monitoring behavior and supervisory control. In: Boff K, Kaufman L, Thomas J (eds) Handbook of perception and human performance, vol 2, Cognitive processes and performance. Wiley, New York, pp 40.1–40.51

  • Norman D (1989) The psychology of everyday things. Basic, New York

  • Norman D (1990) The “problem” with automation: inappropriate feedback and interaction, not “overautomation”. In: Broadbent D, Baddeley A, Reason J (eds) Human factors in hazardous situations. Clarendon, Oxford, pp 569–576

  • Ogata K (1990) Modern control engineering, 2nd edn. Prentice Hall, New Jersey

  • Parasuraman R, Sheridan TB, Wickens CD (2000) A model for types and levels of human interaction with automation. IEEE Trans Syst Man Cybernet A 30:286–297

    Article  CAS  Google Scholar 

  • Pedersen CR, Lind M (1999) Conceptual design of industrial process displays. Ergonomics 42:1531–1548

    Article  CAS  PubMed  Google Scholar 

  • Ranson DS, Woods DD (1996) Animating computer agents. In: Proceedings of the 3rd annual symposium on human interaction with complex systems, Dayton, USA, pp 268–275

  • Rasmussen J (1985) The role of hierarchical knowledge representation in decision making and system management. IEEE Trans Syst Man Cybernet 15:243–243

    Google Scholar 

  • Rasmussen J, Lind M (1981) Coping with complexity. Technical report Risø-M-2293. Risø National Laboratory, Roskilde, Denmark

  • Rasmussen J (1983) Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Trans Syst Man Cybernet 13:257–266

    Google Scholar 

  • Reason J (1990) Human error. Cambridge University Press, New York

  • Sarter NB, Woods DD (1995) How in the world did we ever get into that mode? Mode error and awareness in supervisory control. Hum Fact 37:5–19

    Google Scholar 

  • Sauer J, Wastell DG, Hockey GRJ, Crawshaw CM, Ishak M, Downing JC (2002) Effects of display design on performance in a simulated ship navigation environment. Ergonomics 45:329–347

    Article  PubMed  Google Scholar 

  • Sheridan TB (1997) Supervisory control. In: Salvendy G (ed) Handbook of human factors. Wiley, New York, pp 1295–1327

  • Skjerve ABM, Strand S, Saarni R (2002) Human-centered automation—experimental studies of two human–machine interface designs. In: Proceedings of the 2002 IEEE 7th conference on human factors and power plants, pp 4.10–4.17

  • Sørensen MU (1999) Application of functional modeling in the design of indusrial control systems. Reliab Eng Syst Safe 64:301–315

    Article  Google Scholar 

  • Vicente KJ, Rasmussen J (1990) The ecology of human-machine systems II: mediating “direct perception” in complex work domains. Ecol Psychol 2:207–249

    Google Scholar 

  • Vicente KJ, Rasmussen J (1992) Ecological interface design: theoretical foundations. IEEE Trans Syst Man Cybernet 22:589–606

    Article  Google Scholar 

  • Warm JS, Dember WN, Hancock PA (1996) Vigilance and workload in automated systems. In: Parasuraman R, Mouloua M (eds) Automation and human performance: theory and applications. Lawrence Erlbaum, New Jersey, pp 183–200

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Acknowledgements

This work was performed under a contract with Tokyo Electrical Power Company. The authors would like to thank Dr. Furuhama for fruitful discussions and comments on this work. The authors are also indebted to the reviewers for their valuable suggestions, which helped to improve this paper.

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Authors and Affiliations

  1. Department of Quantum Engineering and Systems Science, Graduate School of Engineering, University of Tokyo, Tokyo, Japan

    Qiao Liu

  2. Institute of Environmental Studies, Graduate School of Frontier Sciences, University of Tokyo, Japan

    Keiichi Nakata & Kazuo Furuta

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  1. Qiao Liu
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  2. Keiichi Nakata
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  3. Kazuo Furuta
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Correspondence to Kazuo Furuta.

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Liu, Q., Nakata, K. & Furuta, K. Making control systems visible. Cogn Tech Work 6, 87–106 (2004). https://doi.org/10.1007/s10111-003-0148-5

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