Discrete Event Dynamic Systems

, Volume 1, Issue 2, pp 149–175 | Cite as

Dynamic setup scheduling and flow control in manufacturing systems

  • Ali Sharifnia
  • Michael Caramanis
  • Stanley B. Gershwin


We propose a method for flow control of parts in a manufacturing system with machines that require setups. The setup scheduling problem is investigated in the context of a multilevel hierarchy of discrete events with distinct frequencies. The higher level of the hierarchy calculates a target trajectory in the surplus/backlog space of the part types which must be tracked at the level of setups. We consider a feedback setup scheduling policy which usescorridors in the surplus/backlog space of the part types to determine the timing of the set-up changes in order to guide the trajectory in the desired direction. An interesting case in which the trajectory leads to a target point (e.g., a hedging point) is investigated in detail. It is shown that in this case the surplus/backlog trajectory at the setup level can lead to a limit cycle. Conditions for linear corridors which result in a stable limit cycle are determined.

Key Words

dynamic stup scheduling dynamic lot-sizing production scheduling 


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  1. Akella, R. and Kumar, P.R. 1986. Optical control of production rate in a failure prone manufacturing system.IEEE Trans. Automatic Control AC-31: 116–126.Google Scholar
  2. Algoet, P.H. 1989. Flow balance for the steady-state distribution of a flexible manufacturing system.IEEE Trans. Automatic Control 34: 917–921.Google Scholar
  3. Bielecki, T. and Kumar, P.R. 1988. Optimality of zero-inventory policies for unreliable manufacturing systems.Oper. Res. 36: 532–541.Google Scholar
  4. Caramanis, M. and Liberopoulos, G. 1988. Perturbation analysis for the design of flexible manufacturing systems flow controllers. Laboratory for Manufacturing Systems and Productivity, Manufacturing Engineering Department, Boston University Technical Report BU-LMSP-88-007.Google Scholar
  5. Caramanis, M. and Sharifnia, A. 1989. Design of near optimal low controllers for flexible manufacturing systems.Proc. 3rd ORSA/TIMS Special Interest Conf. on FMS Aug.: Cambridge, MA. K.E. Stecke and R. Suri (eds.), Elsevier, Amsterdam.Google Scholar
  6. Carreno, J.J. 1990. Economic lot scheduling for multiple products on parallel identical processors.Management Sci. 36: 348–358.Google Scholar
  7. Chase, C. and Ramdage, P.J. 1989. On real time scheduing policies for flexible manufacturing systems. Preprint, Department of Electrical Engineering, Princeton University.Google Scholar
  8. Dobson, G. 1987. The economic lot scheduling problem: Achieving feasibility using time-varying lot sizes.Oper. Res. 35: 764–771.Google Scholar
  9. Elmaghraby, S.E. 1978. The economic lot scheduling problem (ELSP): Review and Extensions.Management Sci. 24: 587–598.Google Scholar
  10. Gershwin, S.B. 1987a. A hierarchical framework for discrete event scheduling in manufacturing systems.Discrete Event Systems: Models and Applications, IIASA Conf. Sopron, Hugary, (Aug.) Varaya and Kurzhanski (eds.), No. 103 in the series Lecture Notes in Control and Information Sciences, Springer-Verlag.Google Scholar
  11. Gershwin, S.B. 1987b. A hierarchical framework for manufacturing systems scheduling: A two machine example.Proc. 26th Conf. on Decision and Control, (Dec.): Los Angeles.Google Scholar
  12. Gershwin, S.B. 1989. Hierarchical flow control: A framework for scheduling and planning discrete events in manufacturing systems.Proc. IEEE 77: 195–209.Google Scholar
  13. Gershwin, S.B., Akella, R. and Choong, Y.F. 1985. Short-term production scheduling of an automated manufacturing facility.IBM J. Res. Dev. 29: 392–400.Google Scholar
  14. Goyal, S.K. 1984. Determination of economic production quantities for a two-product single machine system.Int. J. Production Res. 22: 121–126.Google Scholar
  15. Haurie, A. and Van Delft, Ch. 1989. Turnpike properties for a class of piecewise deterministic systems arising in manufacturing flow control.Proc. 3rd ORSA/TIMS Special Interest Conf. on FMS (Aug.): 333–338, Cambridge, MA. K.E. Steck and R. Suri (eds.), Elsevier, Amsterdam.Google Scholar
  16. Jones, P.C. and Inman, R.R. 1989. When is the economic lot scheduling problem easy?IIE Trans. 21: 11–20.Google Scholar
  17. Kimemia, J.G. and Gershwin, S.B. 1983. An algorithm for the computer control of production in flexible manufactring systems.IIE Trans. 15: 353–362.Google Scholar
  18. Kumar, P.R. and Seidman, T.I. 1990. Dynamic instabilities and stabilization methods in distributed real-time scheduling of manufacturing systems.IEEE Trans. on Automatic Control 35: 289–298.Google Scholar
  19. Lou, S., Sethi, S. and Sorger, G. 1989.Stability of real-time lot scheduling policies for an unreliable machine. preprint, Faculty of Management, University of Toronto, June.Google Scholar
  20. Malhame, R. and Boukas, E. 1989. Transient and steady-states of the statistical flow balance equations in manufacturing systems.Proc. 3rd ORSA/TIMS Special Interest Conf. on FMS (Aug.): 339–345, Cambridge, MA. K.E. Stecke and R. Suri (eds.), Elsevier, Amsterdam.Google Scholar
  21. Olsder, G.J. and Suri, R. 1980. Time-optimal control of parts routing in a manufacturing system with failureprone machines.Proceedings of the 19th IEEE Conf. on Decision and Control (Dec.).Google Scholar
  22. Perkins, J. and Kumar, P.R. 1989. Stable, distributed, real-time scheduling of flexible manufacturing/assembly/disassembly systems.IEEE Trans. Automatic Control 34: 139–148.Google Scholar
  23. Rishel, R. 1975. Dynamic programming and minimum principle for systems with jump Markov disturbances.SIAM J. Control 13: 338–371.Google Scholar
  24. Sharifnia, A. 1988. Optimal production control of a manufacturing system with machine failures.IEEE Trans. Automatic Control 33: 620–625.Google Scholar

Copyright information

© Kluwer Academic Publishers 1991

Authors and Affiliations

  • Ali Sharifnia
    • 1
  • Michael Caramanis
    • 1
  • Stanley B. Gershwin
    • 2
  1. 1.Department of Manufacturing EngineeringBoston UniversityBoston
  2. 2.Department of Mechanical EngineeringMassachusetts Insitutue of TechnologyCambridge

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