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Performance evaluation of SCM in JIT environment

Author

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  • Kojima, Mitsutoshi
  • Nakashima, Kenichi
  • Ohno, Katsuhisa

Abstract

Under stochastic demand and deterministic processing times, we discussed a single-stage JIT production system with the production-ordering and supplier kanbans and derived a probability generating function (p.g.f.) of the stationary distributions of the backlogged demand. In this paper, we extend the system to supply chain management (SCM) in JIT environment with two kinds of kanbans under stochastic demand, deterministic processing times and withdrawals with lead time. These conditions are more realistic than the previous papers. We develop an algorithm for the exact performance evaluation of the SCM such as the stationary distributions of the inventory level, production quantities and total backlogged demand in each stage, using discrete-time Markov process. Optimal numbers of two kinds of kanbans in the system are determined by minimizing a general total cost function. Numerical examples are given to show the efficiency of the proposed approach.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:115:y:2008:i:2:p:439-443
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    References listed on IDEAS

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    1. 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.
    2. Debasis Mitra & Isi Mitrani, 1990. "Analysis of a Kanban Discipline for Cell Coordination in Production Lines. I," Management Science, INFORMS, vol. 36(12), pages 1548-1566, December.
    3. Sridhar R. Tayur, 1993. "Structural Properties and a Heuristic for Kanban-Controlled Serial Lines," Management Science, INFORMS, vol. 39(11), pages 1347-1368, November.
    4. Debasis Mitra & Isi Mitrani, 1991. "Analysis of a Kanban Discipline for Cell Coordination in Production Lines, II: Stochastic Demands," Operations Research, INFORMS, vol. 39(5), pages 807-823, October.
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    Cited by:

    1. Andreas C. Nearchou, 2018. "Multicriteria scheduling optimization using an elitist multiobjective population heuristic: the h-NSDE algorithm," Journal of Heuristics, Springer, vol. 24(6), pages 817-851, December.
    2. Om Prakash Mishra & Vikas Kumar & Dixit Garg, 2018. "Performance evaluation of JIT enabled SCM using ANP method," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(2), pages 547-558, April.
    3. Lo, Chris K.Y. & Yeung, Andy C.L. & Cheng, T.C.E., 2009. "ISO 9000 and supply chain efficiency: Empirical evidence on inventory and account receivable days," International Journal of Production Economics, Elsevier, vol. 118(2), pages 367-374, April.
    4. Garcia, Fernanda A. & Marchetta, Martin G. & Camargo, Mauricio & Morel, Laure & Forradellas, Raymundo Q., 2012. "A framework for measuring logistics performance in the wine industry," International Journal of Production Economics, Elsevier, vol. 135(1), pages 284-298.
    5. Walker, Nathan L. & Styles, David & Coughlan, Paul & Williams, A. Prysor, 2022. "Cross-sector sustainability benchmarking of major utilities in the United Kingdom," Utilities Policy, Elsevier, vol. 78(C).

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