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A methodology to customize pull control systems

Author

Listed:
  • E G A Gaury

    (Tilburg University
    Equipe de Recherche en Systèmes de Production de l'Institut Français de Mécanique Avancée, Aubière)

  • J P C Kleijnen

    (Tilburg University)

  • H Pierreval

    (Equipe de Recherche en Systèmes de Production de l'Institut Français de Mécanique Avancée, Aubière)

Abstract

The objective of this paper is to develop a methodology for customizing pull control systems, replacing traditional control systems such as Kanban, Conwip, and Base Stock. The basic principle is to start with a pull control system that connects each stage of a given production line with each preceding stage; next, the optimization of the corresponding simulation model shows which of these potential control loops are actually implemented. The result of this methodology may be one of the traditional systems, but it may also be one of the following three new types: (1) the total line may be decomposed into several segments, each with its own classic control system, (2) the total line or its segments may combine different traditional systems, or (3) the line may be controlled through a new type of control system. Indeed, these three systems are found in a simulation experiment with a set of twelve production lines. These twelve lines are selected through a statistical design with ten factors that characterize production lines.

Suggested Citation

  • E G A Gaury & J P C Kleijnen & H Pierreval, 2001. "A methodology to customize pull control systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(7), pages 789-799, July.
    • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:7:d:10.1057_palgrave.jors.2601153
    DOI: 10.1057/palgrave.jors.2601153
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    Citations

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    Cited by:

    1. Thürer, Matthias & Stevenson, Mark & Protzman, Charles W., 2015. "COBACABANA (Control of Balance by Card Based Navigation): An alternative to kanban in the pure flow shop?," International Journal of Production Economics, Elsevier, vol. 166(C), pages 143-151.
    2. Onyeocha, Chukwunonyelum Emmanuel & Wang, Jiayi & Khoury, Joseph & Geraghty, John, 2015. "A comparison of HK-CONWIP and BK-CONWIP control strategies in a multi-product manufacturing system," Operations Research Perspectives, Elsevier, vol. 2(C), pages 137-149.
    3. Geraghty, John & Heavey, Cathal, 2004. "A comparison of Hybrid Push/Pull and CONWIP/Pull production inventory control policies," International Journal of Production Economics, Elsevier, vol. 91(1), pages 75-90, September.
    4. Yang, Taho & Fu, Hsin-Pin & Yang, Kuang-Yi, 2007. "An evolutionary-simulation approach for the optimization of multi-constant work-in-process strategy--A case study," International Journal of Production Economics, Elsevier, vol. 107(1), pages 104-114, May.
    5. Lavoie, P. & Gharbi, A. & Kenné, J.-P., 2010. "A comparative study of pull control mechanisms for unreliable homogenous transfer lines," International Journal of Production Economics, Elsevier, vol. 124(1), pages 241-251, March.
    6. Lage Junior, Muris & Godinho Filho, Moacir, 2010. "Variations of the kanban system: Literature review and classification," International Journal of Production Economics, Elsevier, vol. 125(1), pages 13-21, May.
    7. M I Reis dos Santos & P M Reis dos Santos, 2011. "Construction and validation of distribution-based regression simulation metamodels," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1376-1384, July.

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