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Kanban Controlled Pull Systems: An Analytic Approach

Author

Listed:
  • Jean-Luc Deleersnyder

    (McKinsey and Company, Brussels, Belgium)

  • Thom J. Hodgson

    (Department of Industrial Engineering, North Carolina State University, Raleigh, North Carolina 27695-7906)

  • Henri Muller-Malek

    (Department of Industrial Management, Vlerick School of Management, Rijksuniversiteit B-9710 Gent, Belgium)

  • Peter J. O'Grady

    (Department of Industrial Engineering, North Carolina State University, Raleigh, North Carolina 27695-7906)

Abstract

Three problem areas exist in designing and implementing a kanban controlled JIT system: the identification of flow lines problem, the flow line loading problem and the operational control problem. This paper addresses the operational control problem. A general N-stage serial production system is modeled as a discrete time Markov process. Capacity constraints, stochastic machine reliability and demand variability are included. The model is illustrated by a 3-stage system, describing the effects of the number of kanbans, the machine reliability, the demand variability and safety stock requirements on the performance of a kanban controlled pull system.

Suggested Citation

  • Jean-Luc Deleersnyder & Thom J. Hodgson & Henri Muller-Malek & Peter J. O'Grady, 1989. "Kanban Controlled Pull Systems: An Analytic Approach," Management Science, INFORMS, vol. 35(9), pages 1079-1091, September.
    • Handle: RePEc:inm:ormnsc:v:35:y:1989:i:9:p:1079-1091
    DOI: 10.1287/mnsc.35.9.1079
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    Citations

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    Cited by:

    1. Kim, Ilhyung & Tang, Christopher S., 1997. "Lead time and response time in a pull production control system," European Journal of Operational Research, Elsevier, vol. 101(3), pages 474-485, September.
    2. Chen-Yang Cheng & Shu-Fen Li & Chia-Leng Lee & Ranon Jientrakul & Chumpol Yuangyai, 2022. "A Comparative Study of Unbalanced Production Lines Using Simulation Modeling: A Case Study for Solar Silicon Manufacturing," Sustainability, MDPI, vol. 14(2), pages 1-15, January.
    3. Zhao Xiaobo & Qiguo Gong & Kenichi Nakashima, 2001. "Analysis of a production system in a general configuration," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(2), pages 128-143, March.
    4. Ou, Jihong & Jiang, Jiong, 1997. "Yield comparison of push and pull control methods on production systems with unreliable machines," International Journal of Production Economics, Elsevier, vol. 50(1), pages 1-12, May.
    5. John Miltenburg, 1993. "On the equivalence of jit and mrp as technologies for reducing wastes in manufacturing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(7), pages 905-924, December.
    6. Venky Nagar & Madhav V. Rajan & Richard Saouma, 2009. "The Incentive Value of Inventory and Cross‐training in Modern Manufacturing," Journal of Accounting Research, Wiley Blackwell, vol. 47(4), pages 991-1025, September.
    7. Huang, Min & Wang, Dingwei & Ip, W. H., 1998. "Simulation study of CONWIP for a cold rolling plant," International Journal of Production Economics, Elsevier, vol. 54(3), pages 257-266, May.
    8. Subba Rao, S. & Gunasekaran, A. & Goyal, S. K. & Martikainen, T., 1998. "Waiting line model applications in manufacturing," International Journal of Production Economics, Elsevier, vol. 54(1), pages 1-28, January.
    9. Askin, Ronald G. & Krishnan, Shravan, 2009. "Defining inventory control points in multiproduct stochastic pull systems," International Journal of Production Economics, Elsevier, vol. 120(2), pages 418-429, August.
    10. Iwase, Masaharu & Ohno, Katsuhisa, 2011. "The performance evaluation of a multi-stage JIT production system with stochastic demand and production capacities," European Journal of Operational Research, Elsevier, vol. 214(2), pages 216-222, October.
    11. Kojima, Mitsutoshi & Nakashima, Kenichi & Ohno, Katsuhisa, 2008. "Performance evaluation of SCM in JIT environment," International Journal of Production Economics, Elsevier, vol. 115(2), pages 439-443, October.
    12. Mascolo, Maria Di, 1996. "Analysis of a synchronization station for the performance evaluation of a kanban system with a general arrival process of demands," European Journal of Operational Research, Elsevier, vol. 89(1), pages 147-163, February.
    13. Wilhelm, W. E. & Som, Pradip, 1998. "Analysis of a single-stage, single-product, stochastic, MRP-controlled assembly system," European Journal of Operational Research, Elsevier, vol. 108(1), pages 74-93, July.
    14. Andijani, A. A., 1998. "A multi-criterion approach for Kanban allocations," Omega, Elsevier, vol. 26(4), pages 483-493, August.
    15. Yucesan, Enver & de Groote, Xavier, 2000. "Lead times, order release mechanisms, and customer service," European Journal of Operational Research, Elsevier, vol. 120(1), pages 118-130, January.
    16. Alfieri, Arianna & Matta, Andrea, 2012. "Mathematical programming formulations for approximate simulation of multistage production systems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 773-783.
    17. Ahmadi, Reza H. & Matsuo, Hirofumi, 2000. "A mini-line approach for pull production," European Journal of Operational Research, Elsevier, vol. 125(2), pages 340-358, September.
    18. Hirakawa, Yasuhiro, 1996. "Performance of a multistage hybrid push/pull production control system," International Journal of Production Economics, Elsevier, vol. 44(1-2), pages 129-135, June.
    19. Houmin Yan & Xun Yu Zhou & G. Yin, 1999. "Approximating an Optimal Production Policy in a Continuous Flow Line: Recurrence and Asymptotic Properties," Operations Research, INFORMS, vol. 47(4), pages 535-549, August.

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