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Information to share in supply chains dedicated to the mass production of customized products for decentralized management

Listed author(s):
  • Carole Camisullis

    (IRG - Institut de Recherche en Gestion - UPEM - Université Paris-Est Marne-la-Vallée - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12)

  • Vincent Giard

    ()

    (CRG - Centre de recherche en gestion - Polytechnique - X - CNRS - Centre National de la Recherche Scientifique, LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique)

  • Gisele Mendy-Bilek

    ()

    (IAE, Université de Pau et des Pays de l'Adour - IAE, Université de Pau et des Pays de l'Adour)

Registered author(s):

    In an upstream supply chain dedicated to the mass production of customized products, decentralized management can be an efficient and effective method in a steady state in which stochastic characteristics of customers' demands remain stable. However, this is possible only if all echelons that precede the final assembly line use periodic replenishment policies that restrain the stockout risk to a low predetermined probability. The safety stocks' levels are more difficult to define for alternative or optional parts, as well as the components they use, whose demands are weighted sums of random variables, affected by several random factors and organizational constraints. The factors and constraints to consider are not the same for supplied and produced components. The random demand of a component depends on the demand of alternative or optional parts mounted in the final product, through a double transformation involving the bill of materials explosion, which is at the origin of the weighted sum of random variables, and time lags. In the steady state, the knowledge of the probability distribution of that random variable allows for the determination of safety stocks that decouple the management of upstream supply chains. Progressive changes in the steady state require periodic and progressive adaptations of the safety stocks that do not directly depend on the final demand knowledge.

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    Paper provided by HAL in its series Working Papers with number hal-00876865.

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    Date of creation: 31 Jan 2011
    Handle: RePEc:hal:wpaper:hal-00876865
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00876865
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    1. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    2. Ryu, Seung-Jin & Tsukishima, Takahiro & Onari, Hisashi, 2009. "A study on evaluation of demand information-sharing methods in supply chain," International Journal of Production Economics, Elsevier, vol. 120(1), pages 162-175, July.
    3. repec:dau:papers:123456789/487 is not listed on IDEAS
    4. Ouyang, Yanfeng & Li, Xiaopeng, 2010. "The bullwhip effect in supply chain networks," European Journal of Operational Research, Elsevier, vol. 201(3), pages 799-810, March.
    5. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    6. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    7. Olhager, Jan & Ostlund, Bjorn, 1990. "An integrated push-pull manufacturing strategy," European Journal of Operational Research, Elsevier, vol. 45(2-3), pages 135-142, April.
    8. Gunasekaran, Angappa & Ngai, Eric W.T., 2009. "Modeling and analysis of build-to-order supply chains," European Journal of Operational Research, Elsevier, vol. 195(2), pages 319-334, June.
    9. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    10. Springer, Mark & Kim, Ilhyung, 2010. "Managing the order pipeline to reduce supply chain volatility," European Journal of Operational Research, Elsevier, vol. 203(2), pages 380-392, June.
    11. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
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