Skip to main content

Supervisory Control Principles for Dynamic Operations Management of Manufacturing Shop Floors

  • Chapter
  • 196 Accesses

Abstract

In intelligent real-time scheduling and control of advanced manufacturing systems, two trends can be observed: one is the full automation of these processes with the elimination of human agents, and the other is the semi-automation of these processes with explicit integration of humans through implementation of the supervisory control paradigm. Discussion in the paper is devoted to the second alternative with the main concepts, principles, models and design considerations that enable a supervisory control system to contribute to dynamic operation management of manufacturing shop floors with their many uncertainties. Discussion is also extended to an example system (called SUPREACT) that focuses on the reactive — and proactive — scheduling functions involved in the system as the major intelligent supervisory control functions besides learning.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Albus, J. S. (1992): RCS: A reference model architecture for intelligent control. IEEE Computer, p. 56–59.

    Google Scholar 

  • Ammons, J.C., Govindaraj, T., Mitchell, C. M. (1986): Decision models for aiding FMS scheduling and control. IEEE Transactions on Systems, Man, and Cybernetics, 18:5, p. 744–756.

    Google Scholar 

  • Ammons, J.C., Govindaraj, T., Mitchell, C. M. (1988): Human aided scheduling for FMS: A paradigm for human-computer interaction in real-time scheduling and control. In: Stecke, K.E., Suri, R. (Eds.): Proceedings of the 2d ORSA/TIMS Conference on Flexible Manufacturing Systems: Operations Research models and applications. Elsevier, Amsterdam, p. 443–454.

    Google Scholar 

  • Atabakhsh, H. (1991): A survey of constraint based scheduling systems using an artificial intelligence approach. Artificial Intelligence in Engineering, 6:2, 58–73.

    Article  Google Scholar 

  • Barfield, W., Hwang, S-L., Chang, T-C. (1986): Human-computer supervisory performance in the operation and control of FMSs, In: Kusiak, A. (Ed.): Flexible Manufacturing Systems: Methods and Studies. Elsevier, Amsterdam, p. 377–408.

    Google Scholar 

  • Benson, CR., Govindaraj, T., Mitchell, CM., Krosner, S.P. (1989): Effectiveness of direct manipulation interaction in the supervisory control of FMS part movement. IEEE, p. 947–952.

    Google Scholar 

  • Bullinger, H.-J. (1992), Neue Produktionsparadigmen als betriebliche Herausforderung. In: Warnecke, H.-J., Bullinger, H.-J. (Eds.): Innovative Unternehmensstrukturen Springer, Berlin.

    Google Scholar 

  • Bullinger, H.-J. et al. (1994): Human-computer interaction and Lean Production: The shop floor example. Int. Journal of Human-Computer Interaction, 6:2, p. 121–154.

    Article  Google Scholar 

  • Chu, Y.Y., Rouse, W.B. (1979): Adaptive allocation of decision making responsibility between human and computer in multi-task situations. IEEE Transactions Systems, Man and Cybernetics, 9, p. 769–778.

    Article  Google Scholar 

  • Davis, W.Jones, A, Saleh, A, (1992): Generic architecture for intelligent control systems. Computer-Integrated Manufacturing Systems, 5, p. 105–113.

    Article  Google Scholar 

  • Dunkler, O., et al. (1988): The Effectiveness of supervisory control strategies in scheduling flexible manufacturing systems. IEEE Transactions on Systems, Man, and Cybernetics, 18:2, p. 223–237.

    Google Scholar 

  • Edison, T. (1991): Intelligent support system for continuous improvement in a dynamic manufacturing environment. Computer-Integrated Manufacturing Systems, 4:4, p. 229–238.

    Article  Google Scholar 

  • Gandibleux, X., Crevis, I., Millot, P. (1993): Man-machine cooperation in real-time control: Two case studies for future control systems. In: Yoshikawa, H., Gossenaerts, J. (Eds.): Information Infrastructure Systems for Manufacturing, IFIP Transactions B-14. Elsevier, Amsterdam.

    Google Scholar 

  • Gerhardt, L. (1997): The integration of intelligence in the 21st century: Human and machine. Keynote speech. Proceedings of the 4th IF AC Workshop on Intelligent Manufacturing Systems’ IMS’97. Seoul, Korea.

    Google Scholar 

  • Goodman, B.A., Litman, D.J. (1990): Plan recognition for intelligent interfaces. IEEE, p. 297–303.

    Google Scholar 

  • Guimaraes, T, Owen, J.E., Martensson, N., (1997): Assessing the importance of manufacturing system complexity and moderating variables. In: Monostori, L. (Ed.): Proceedings of the Second World Congress on Intelligent Manufacturing Processes & Systems. Springer, Berlin, p. 263–271.

    Google Scholar 

  • Harmonosky, CM., Robohn, S.F. (1991): Real-time scheduling in computer integrated manufacturing: A review of recent research. Int. J. Computer Integrated Manufacturing, 4:6, p. 331–340.

    Article  Google Scholar 

  • Hettenbach, DA., Mitchell, CM., Govindaraj, T. (1989): Decision making in supervisory control of flexible manufacturing system. IEEE, p. 953–985.

    Google Scholar 

  • Hollnagel, E., Mancini, G., Woods, D.D. (Eds.) (1986): Intelligent decision aids in process environments. Springer, New York.

    Google Scholar 

  • Holloway, L.E., et al. (1991): Integration of behavioral fault detection models and an intelligent reactive scheduler. Proceedings of IEEE Int. Symposium on Intelligent Control. Arlington, VA. p. 134–139.

    Google Scholar 

  • Horte, S.V., Lindberg, P. (1992): Performance effects human and organizational development and technological development. Int. Journal of Human Factors in Manufacturing, 4:3, p. 243–259.

    Google Scholar 

  • Hwang, S.-L., Salvendy, G. (1988): Operator performance and subjective response in control of flexible manufacturing systems. Work and Stress, 2:1, p. 27–39.

    Article  Google Scholar 

  • Hwang, S.-L., Sharit, J., Salvendy, G. (1984): Management strategies for the design, control, and operation of flexible manufacturing systems. Proceedings of the Human Factors Society, 27th Annual Meeting, Norfolk, VA. The Human Factors Society, Santa Monica, CA p. 297–301.

    Google Scholar 

  • Kadar, B., Monostori, L., Szelke, E. (1997): An object oriented framework for developing distributed manufacturing architectures. In: Monostori, L. (Ed): Intelligent Manufacturing Systems. Springer, Berlin, p. 548–555.

    Google Scholar 

  • Karwowski, W., Rahimi, M. (Eds.) (1990): Ergonomics of Hybrid Automated Systems III. Elsevier, Amsterdam.

    Google Scholar 

  • Karwowski, W., Salvendy, G. (1994): Integrating people, organization, and technology in advanced manufacturing: A position paper based on the joint view of industrial managers, engineers, consultants and researchers. Int. Journal of Human Factors in Manufacturing, 4:1, p. 1–19.

    Google Scholar 

  • Kempf, F., Rüssel, B., Sidhu, S., Barett, S. (1991): AI-based schedulers in manufacturing practice. AI Magazine, 11:5, p. 46–56.

    Google Scholar 

  • Kidd, P.T. (1990): Human Factors, CIM-EUROPE and the ESPRIT Research Programme. Int. Journal of Industrial Ergonomics, 5, p. 105–112.

    Google Scholar 

  • Kim, S. (1995): Advanced design and manufacturing systems through knowledge integration. In: Monostori, L. (Ed.): Proceedings of the First World Congress on Intelligent Manufacturing Processes and Systems’, Vol. One. Puerto Rico. CIRP-IEEE Publications, p. 13–22.

    Google Scholar 

  • Kolonder, J.L. (1991): Improving human decision making through case-based decision aiding. AI Magazin, p. 52–68.

    Google Scholar 

  • Krebs, J.E., Platzman, L.K., Mitchell, CM. (1989): A real-time AGV scheduling system that combines human decision-making with integer-programming algorithms. IEEE, p. 965–970.

    Google Scholar 

  • Martensson, L., Stahre, J. (1992): Operator roles in advanced manufacturing. In: Brödner, P., Karwowski, W. (Eds.): Aspects of Advanced Manufacturing and Hybrid Automation. Elsevier, Amsterdam, p. 155–162.

    Google Scholar 

  • Mitchell, CM., Salsi, D.L., (1987) Use of model-based qualitative icons and adaptive windows in workstations for supervisory control systems. IEEE Transactions on Systems, Man and Cybernetics, 17:4, p. 573–593.

    Google Scholar 

  • Mitchell, CM. (1988): Supervisory control: Human information processing in manufacturing systems. In: Concise Encyclopedia of Information Processing in Systems and Organizations. Pergamon Press, New York.

    Google Scholar 

  • Mitchell, CM., Miller, RA. (1986): A discrete control model of operator function: A methodology for information display design. IEEE Transactions on Systems, Man and Cybernetics. 16:3, p. 353–369.

    Google Scholar 

  • Miyashita, K, Sycara, K.P. (1994): Adaptive schedule repair. In: Szelke, E., Kerr, R. (Eds.): Knowledge based reactive scheduling, IFIP Transactions B-15. Elsevier, Amsterdam, p. 107–124.

    Google Scholar 

  • Monostori, F., Szelke, E., Radar, B. (1997): Management of changes and disturbances in manufacturing systems. Preprints of the IF AC Workshop on Manufacturing Systems: Modelling, management and control MIM’97. Vienna, p. 27–38.

    Google Scholar 

  • Na, H.S. (1990): Artificial intelligence in today’s factory. Robotics & Computer-Integrated Manufacturing, 7, 315–320.

    Article  Google Scholar 

  • Nakamura, N., Salvendy, G. (1994): Human planner and scheduler. In: Design of work and development of personnel in advanced manufacturing. Wiley, New York.

    Google Scholar 

  • Norman, DA. (1986): Cognitive engineering. In: Norman, DA., Draper, S. (Eds.): User-centered system design: New perspectives in human-computer interaction. Lawrence Erbaum Associates, Hillsdale, p. 86–124.

    Google Scholar 

  • O’ Grady, P.J. (1987): Controlling automated manufacturing systems. Kogan Page/Chapman & Hall, London.

    Google Scholar 

  • Owen, J. V., Sprow, E.E. (1994): Shop Floor ’94 - The challenge of change. Manufacturing Engineering, 112, 33–46.

    Google Scholar 

  • Passino, K.M. (1995): Intelligent control for autonomous systems. IEEE Spectrum, p. 55–62.

    Google Scholar 

  • Rasmussen, J. (1986): Information processing and human-machine interaction. North-Holland, New York.

    Google Scholar 

  • Rasmussen, J. (1990): A model for the design of computer integrated manufacturing systems: Identification of information requirements of decision makers. Int. Journal of Industrial Ergonomics, 5, p. 5–16.

    Article  Google Scholar 

  • Rissland, E. (1982): Ingredients of intelligent user interfaces. Int. Journal of Man-Machine Studies, 2, p. 377–388.

    Google Scholar 

  • Rook, F.W., Donnel, M.L. (1993): Human cognition and the expert system interface: Mental models and inference explanations. IEEE Transactions on System, Man and Cybernetics, 23:6, p. 1649–1661.

    Google Scholar 

  • Rouse, W.B. (1981): Human-computer interaction in the control of dynamic systems. Computing Surveys, 13, p. 71–99.

    Article  Google Scholar 

  • Rouse, W.B. (1985): Supervisory control and display systems. In: Zeidner, J. (Ed.): Human Productivity Enhancement. Prager, New York.

    Google Scholar 

  • Rouse, W.B. (1988a): The human role in advanced manufacturing systems. In: Dale, W. (Ed.): Design and analysis of integrated manufacturing systems. National Academy Press, Washington, p. 148–165.

    Google Scholar 

  • Rouse, W.B. (1988b): Intelligent decision support for advanced manufacturing systems. Manufacturing Review, 1:4, p. 236–243.

    Google Scholar 

  • Rouse, W.B., Geddes, N.D., Curry, R. E. (1987): An architecture for intelligent interfaces: Outline of an approach to supporting operators of complex systems. Human Computer Interaction, 3, p. 87–122.

    Article  Google Scholar 

  • Ruge, I., Bachhuber, W., Bamberg, S., Schenk, M. (1995): Coping with complexity. Siemens Review, 62:6, p. 26–29.

    Google Scholar 

  • Sanderson, P.M. (1988): Human supervisory control in discrete manufacturing: Translating the paradigm. In: Karwowski, W., Parsaei, H.R., Wilhelm, M.R. (Eds.): Ergonomics of hybrid automated systems. Elsevier, Amsterdam.

    Google Scholar 

  • Schneiderman, B. (1992): Designing the User Interface - Strategies for effective human-computer interaction. 2nd ed. Addison-Wesley, New York.

    Google Scholar 

  • Sharit, J. (1985): Supervisory control of a flexible manufacturing system. Human Factors,27:1, p. 47–59.

    Google Scholar 

  • Sheridan, T.B. (1976): Toward a general model of supervisory control. In: Sheridan, T.B., Johannsen, J. (Eds.): Monitoring behavior and supervisory control. Plenum Press, New York. p. 271–281.

    Google Scholar 

  • Sheridan, T.B. (1987): Supervisory control, Chapter 9.6, In: Salvendy, G. (Ed.): Handbook of Human Factors. Wiley, New York. p. 1243–1267.

    Google Scholar 

  • Sheridan, T.B., Ferrell, W.R. (1974): Man-machine systems. M.I.T. Press, Cambridge.

    Google Scholar 

  • Sheridan, T.B., Fischoff, B., Posner, M., Pew, R.W. (1983): Supervisory control systems. In: Research needs in human factors. National Academy Press, Washington.

    Google Scholar 

  • Sheridan, T.B., Hennessy, R.T. (Eds.) (1984): Modeling of supervisory control behavior: report of a workshop. National Academy Press, Washington.

    Google Scholar 

  • Sheridan, T.B., Johannsen, G. (Eds.) (1976): Monitoring behavior and supervisory control. Plenum Press, New York.

    Google Scholar 

  • Shukla, C.S., Chen, F.F. (1996): The state of the art in intelligent real-time FMS control: A comprehensive survey. Journal of Intelligent Manufacturing, 7, p. 441–455.

    Article  Google Scholar 

  • Stahre, J. (1994): Evaluating human/machine interaction problems in advanced manufacturing. Computer integrated manufacturing systems. Butterworth-Heineman.

    Google Scholar 

  • Stahre, J., Johansson, A. (1994): Decision Support for Flexible Manufacturing. In: Kídd, P., Karwowski, W. (Eds.): Advances in agile manufacturing - Integrating technology, organization and people. IOS Press, Oxford, p. 405–408.

    Google Scholar 

  • Steinberg, S., Gitomer, D.H. (1993): Cognitive task analysis and interface design in a technical troubleshooting domain. Knowledge-Based Systems, 6:4, p. 249–257.

    Article  Google Scholar 

  • Sullivan, J.W., TYLER. S.W. (1991): Intelligent User Interfaces. ACM Press.

    Google Scholar 

  • Szelke, E., Markus, G. (1995): A blackboard based perspective of reactive scheduling. In: Kerr, R., Szelke, E. (Eds.): Artificial Intelligence in Reactive Scheduling. Chapman & Hall, London, p. 60–77.

    Google Scholar 

  • Szelke, E., Markus, G. (1997): A learning reactive scheduler using CBR/L. Computers in Industry (In print).

    Google Scholar 

  • Szelke, E., Kerr, R.M. (1994): Knowledge based reactive scheduling. Production Planning and Control, 5:2, p. 124–145.

    Article  Google Scholar 

  • Szelke, E., Markus, G. (1993a): Intelligent interface design to supervisory control of dynamic discrete-part manufacturing processes. In: REX, J., Schlechtendahl, E.G. (Eds.): Interfaces in Industrial Systems for Production and Engineering, IFIP Transactions B-10. Elsevier, Amsterdam, p. 159–173.

    Google Scholar 

  • Szelke, E., Markus, G. (1993b): Human integration in intelligent supervisory control for dynamic discrete manufacturing processes. In: Tatsiopoulos, LP., Pappas, I.A. (Eds.): Advances in production management systems, IFIP Transactions B-14. Elsevier, Amsterdam, p. 81–90.

    Google Scholar 

  • Szelke, E., Markus, G. (1994a): Reactive scheduling - An intelligent supervisor function. In: Szelke, E., Kerr, R.M. (Eds.): Knowledge based reactive scheduling, IFIP Transactions B-15. Elsevier, Amsterdam, p. 125–145.

    Google Scholar 

  • Szelke, E., Markus, G. (1994b): Contingency and performance driven reactive scheduling in discrete event dynamic environment. In: Walter, C, Kliemann, F.J., de Oliveira, J.P.M. (Eds.): Evaluation of production management methods, IFIP Transactions B-19. Elsevier, Amsterdam, p. 225–233.

    Google Scholar 

  • Szelke, E., Markus, G. (1994C): A cognitive engineering approach with AI techniques to reactive scheduling in the supervision of dynamic manufacturing processes. In: LUNZE, J., LEITCH, R., STRUSS, P. (Eds.): Proceedings of the IEE 2nd Int. Conference on Intelligent Systems Engineering, IEE Publication No. 395, London, p. 425–433.

    Google Scholar 

  • Szelke, E., Meszaros, I. (1990): CIM related intelligent supervisory control for FMS. In: Eloranta, E. (Ed.): Advances in Production Management Systems. Elsevier, Amsterdam, p. 271–281.

    Google Scholar 

  • Szelke, E., Monostori, L. (1995): Reactive and proactive scheduling with learning in reactive operation management. In: Storch, R.M. (Ed.): Proceedings of the IFIP WG 5.7 Int. Working Conference on Managing Concurrent Manufacturing to Improve Industrial Performance. Washington University, Seattle, p. 456–483.

    Google Scholar 

  • Szelke, E., Monostori, L. (1997): Reactive scheduling in real time production control. In: Villa, A., Brandimarte, P. (Eds.): The IFAC Handbook on ‘Manufacturing Modelling, Management and Control’. Springer, London.

    Google Scholar 

  • Tzafestas, S.G. (Ed.) (1989): Knowledge-based diagnosis, supervision, and control. Applied Information Technology Series. Plenum Press, New York.

    Google Scholar 

  • Valkenaers, P., Bonneville, F., Van Brussel, H., Wyns, J. (1994): Results of the holonic system benchmark at KU Leuven. Proceedings of the 4th Int. Conference on Computer Integrated Manufacturing and Automation Technology, Troy, NY. p. 128–133.

    Google Scholar 

  • Villa, A. (1991): Hybrid control systems in manufacturing. Gordon and Breach, London.

    Google Scholar 

  • Wall, TT., Clegg, C.W., Kemp, N.J. (1987): The human side of advanced manufacturing. Wiley, New York.

    Google Scholar 

  • Warnecke, HJ. (1993): The Fractal Company: A revolution in corporate culture. Springer-, Berlin.

    Google Scholar 

  • Wiendahl, H-P., Scholtissek, P. (1994): Management and control of complexity in manufacturing. Annals of CIRP, 43:2, p. 533–540.

    Article  Google Scholar 

  • Wiers, V.C.S. (1997): Human computer interaction in production scheduling. Ph.D. Thesis, Institute for Business Engineering and Technology Application, Eindhoven University.

    Google Scholar 

  • Woods, D.D. (1986): Joint cognitive system paradigm for intelligent decision support. In: Hollnagel, E., Mancini, G., Woods, D. (Eds.): Intelligent decision aids. Springer, New York.

    Google Scholar 

  • Woods, D.D., Roth, E.M., Benett, K. (1990): Explorations in joint human-machine cognitive systems. In: Robertson, S., Zachary, A, Black, J.B. (Eds.): Cognition, computing and co-operation. N.J. Ablex, Norwood.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Szelke, E. (1998). Supervisory Control Principles for Dynamic Operations Management of Manufacturing Shop Floors. In: Scherer, E. (eds) Shop Floor Control — A Systems Perspective. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60313-6_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-60313-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64349-1

  • Online ISBN: 978-3-642-60313-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics