Distributed planning and control for manufacturing operations

  • Qing Ge
  • Nicholas V. Findler
Parallel Processing And Distributed AI
Part of the Lecture Notes in Computer Science book series (LNCS, volume 406)


Intelligent manufacturing planning and control provide an interesting environment for distributed artificial intelligence research and application. In this paper, we examine the domain of distributed manufacturing operations and present a distributed problem solving system developed for it. Certain issues that are crucial to overall system performance are investigated such as the timing problem, the network perception problem, the connection problem and communication minimization. Different approaches to these issues are discussed. The "perceive-plan-act" loop is employed as an essential operational cycle at each problem solving node to enhance global coherence. Some experimental results are shown.

Keywords and phrases

distributed artificial intelligence distributed planning manufacturing operations network perception timing node cooperation global coherence 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. (1).
    Smith, R.G. and R. Davis: Framework for Cooperation in Distributed Problem Solving (IEEE Transactions on Systems, Man, and Cybernetics, SMC-11, pp. 61–70, 1981).Google Scholar
  2. (2).
    Davis, R. and R.G. Smith: Negotiation as a metaphor for distributed problem solving (Artificial Intelligence, 20, pp. 63–109, 1983).Google Scholar
  3. (3).
    Findler, N.V. and J. Gao: Dynamic Hierarchical Control for Distributed Problem Solving (Data and Knowledge Engineering, 2, pp. 285–301, 1987).Google Scholar
  4. (4).
    Ge, Q. and N. Findler: Perceiving And Planning Before Acting — An Approach To Enhance Global Network Coherence (To appear in International Journal of Intelligence Systems).Google Scholar
  5. (5).
    Parunak, H.V.D.: Manufacturing Experience with the Contract Net, in: Huhns, M.N. (Ed): Distributed Artificial Intelligence (Morgan Kaufmann Publishers, Inc.: Los Altos, CA, 1987).Google Scholar
  6. (6).
    Parunak, H.V.D., J.F. White, P.W. Lozo, R. Judd, B.W. Irish and J. Kindrick: An Architecture for Heuristic Factory Control (Proceedings of the American Control Conference, Seattle, WA, pp. 548–558, 1986).Google Scholar
  7. (7).
    Durfee, E.H., V.R. Lesser and D.D. Corkill: Increasing Coherence In A Distributed Problem Solving Network (Proc. IJCAI-85, vol. 2, pp. 1025–1030, 1985).Google Scholar
  8. (8).
    Findler, N.V. and R. Lo: An examination of distributed planning in the world of air traffic control (Journal of Parallel and Distributed Computing, 3, pp. 411–431, 1986).Google Scholar
  9. (9).
    Lansky, A.L. and D.S. Fogelsong: Localized representation and planning methods for parallel domains (Proc. AAAI-87, Seattle, WA, pp. 240–245, 1987).Google Scholar
  10. (10).
    Durfee, E.H. and V.R. Lesser: Using Partial Global Plans to Coordinate Distributed Problem Solvers (Proc. IJCAI-87, pp. 875–883, 1987).Google Scholar
  11. (11).
    Barr, A. and E.A. Feigenbaum (Eds): The Handbook of Artificial Intelligence (William Kaufmann, Inc.: Los Altos, CA, 1981).Google Scholar
  12. (12).
    Woods, W.A.: Important Issues in Knowledge Representation (Proc. of IEEE, 74, pp. 1322–1334, 1986).Google Scholar
  13. (13).
    Smith, R.G.: A Framework for Distributed Problem Solving (Ann Arbor, Michigan: UMI Research Press, 1981).Google Scholar
  14. (14).
    Corkill, D.D.: A framework for organizational self-design in distributed problem solving networks (Doctoral dissertation and COINS Technical Report 82-33, Department of Computer and Information Science, University of Massachusetts at Amherst, 1982).Google Scholar
  15. (15).
    Findler, N.V.: Some artificial intelligence contributions to air traffic control (Proc. Fourth Jerusalem Conference on Information Technology, pp. 470–475, 1984).Google Scholar
  16. (16).
    Chapman, D.: Nonlinear planning: a rigorous reconstruction (Proc. IJCAI-85, pp. 1022–1024, 1985).Google Scholar
  17. (17).
    Yang, J.D., M.N. Huns and L.M. Stephens: An architecture for control and communications in distributed artificial intelligence system (IEEE Transactions on Systems, Man and Cybernetics, SMC-15, pp. 316–326, 1985).Google Scholar
  18. (18).
    Lesser, V.R. and D.D. Corkill: Functionally accurate, cooperative distributed systems (IEEE Transactions on Systems, Man, and Cybernetics, SMC-11, pp. 81–96, 1981).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Qing Ge
    • 1
  • Nicholas V. Findler
    • 2
  1. 1.BASS TICKETS LTD.TorontoCanada
  2. 2.Computer Science Department Artificial Intelligence LaboratoryArizona State UniversityTempeU.S.A.

Personalised recommendations