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A Stable, Distributed Routing Policy for Flexible Manufacturing Systems

  • J. Fenchel
  • Y. H. Chen
Part of the Advanced Manufacturing book series (ADVMANUF)

Abstract

Consider a multi-machine Flexible Manufaturing System (FMS) FMS, where a set of n input part types (PTs) is processed subject to processing and system constraints. The m servers are arranged in a parallel fashion, with identical operating conditions for a particular part type (PT), but nonidentical processing capabilities. In other words, there is no preference between servers for processing of a PT, whenever the particular PT can be processed on the server. This gives rise to processing constraints, namely routing decisions during system operation. All policies developed share the following set of assumptions: (1) process times, buffer bounds, and routing conditions are known in advance and deterministic, (2) no job preemption, (3) the machines allow for model processing breakdowns, (4) no precedence relations between PTs of one class exist, and (5) there are implicit setup times between PTs. For the considered type of model an activated breakdown incurs processing discontinuation of a particular PT model, resulting in unprocessed parts of a batch being transfered back into the input inventory buffers. This allows other models of a PT to be processed even though a certain PT model currently cannot be manufactured.

Keywords

Inventory Level Flexible Manufacture System Part Type Input Buffer Economic Order Quantity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Baker, K.R., 1974, Introduction to Sequencing and Scheduling, Wiley, New York.Google Scholar
  2. [2]
    Chen, Y.H., 1992, Real-Time Scheduling of Flexible Manufacturing Systems, Journal of Intelligent and Robotic Systems, Vol. 6, pp. 51–63.MATHCrossRefGoogle Scholar
  3. [3]
    Chow, Y.-C. and Kohler W.H., 1979, Models for Dynamic Load Balancing in a Heterogeneous Multiple Processor System, IEEE Transactions on Computers, Vol. c–28, pp. 354–361.MathSciNetCrossRefGoogle Scholar
  4. [4]
    Chuah, M.C., 1994, Analysis of Networks of Queues via Projection Technique, IEEE Transactions on Automatic Control, Vol. 39, pp. 1588–1599.MathSciNetMATHCrossRefGoogle Scholar
  5. [5]
    Cruz, R.L., and Chuah, M.C., 1991, A Minimax Approach to a simple Routing Problem, IEEE Transactions on Automatic Control, Vol. 36, pp. 1424–1435.MathSciNetMATHCrossRefGoogle Scholar
  6. [6]
    Fenchel, J., 1995, Stable, Distributed Real-Time Scheduling of Flexible Manufacturing Systems: An Energy Approach, Ph.D. Thesis Georgia Insititute of Technology.Google Scholar
  7. [7]
    Kreyszig, E., 1978, Introductory Functional Analysis with Applications, Wiley, New York.Google Scholar
  8. [8]
    Luo, Z.-Q., and Tseng, P., 1994, On the Rate of Convergence of a Distributed Asynchronous Routing Algorithm, IEEE Transactions on Automatic Control, Vol. 39, pp. 1123–1129.MathSciNetMATHCrossRefGoogle Scholar
  9. [9]
    Morton, T. and Pentico, D., 1993, Heuristic Scheduling Systems, Wiley, New York.Google Scholar
  10. [10]
    Passino, K.M., Michel, A.N., and Antsaklis, P.J., 1994, Lyapunov Stability of Discrete Event Systems, IEEE Transactions on Automatic Control, Vol. 39, pp. 269–279.MathSciNetMATHCrossRefGoogle Scholar
  11. [11]
    Perkins, J.R., and Kumar, P.R., 1989, Stable, Distributed, Real-Time Scheduling of Flexible Manufacturing/ Assembly/ Disassembly Systems, IEEE Transactions on Automatic Control, Vol. 34, pp. 139–148.MathSciNetMATHCrossRefGoogle Scholar
  12. [12]
    Perkins, J.R., and Kumar, P.R., 1990, Dynamic Instabilities and Stabilization Methods in Distributed Real-Time Scheduling of Manufacturing Systems, IEEE Transactions on Automatic Control, Vol. 35, pp. 289–298.CrossRefGoogle Scholar
  13. [13]
    Perkins, J.R., Humes, C., and Kumar P.R., 1994, Distributed Scheduling of Flexible Manufacturing Systems: Stability and Performance, IEEE Transactions on Robotics and Automation, Vol. 10, pp. 133–141.CrossRefGoogle Scholar
  14. [14]
    Sparaggis, P.D., Towsley, D., and Cassandras, C.G., 1994, Routing with Limited State Information in Queueing Systems with Blocking, IEEE Transactions on Automatic Control, Vol. 39, pp. 1492–1497.MathSciNetMATHCrossRefGoogle Scholar
  15. [15]
    Towsley, D., Sparaggis, P.D., and Cassandras, C.G., 1994, Optimal Routing and Buffer Allocation for a Class of Finite Capacity Queueing Systems, IEEE Transactions on Automatic Control, Vol. 37, pp. 1446–1451.MathSciNetCrossRefGoogle Scholar
  16. [16]
    Tsitsiklis, J.N., and Bertsekas, D.P., 1986, Distributed Asynchronous Optimal Routing in Data Networks, IEEE Transactions on Automatic Control, Vol. AC–31, pp. 325–332.MathSciNetCrossRefGoogle Scholar
  17. [17]
    Walrand, J., 1989, An Introduction to Queueing Networks, Prentice Hall, Englewood Cliffs, New Jersey.Google Scholar

Copyright information

© Springer-Verlag London Limited 1997

Authors and Affiliations

  • J. Fenchel
  • Y. H. Chen

There are no affiliations available

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