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Optimal Leadtimes Planning in a Serial Production System

Author

Listed:
  • Linguo Gong

    (Department of Quantitative Business Analysis, Louisiana State University, Baton Rouge, Louisiana 70803)

  • Ton de Kok

    (Department of Mathematics and Computing Science, University of Technology, Eindhoven, Netherlands)

  • Jie Ding

    (Department of Management Sciences, Rider University, Lawrenceville, New Jersey 08648)

Abstract

Consider an N stage serial production line where the processing times of orders may be random. Since the carrying costs increase from stage to stage, the standard production procedure, that is, to determine a total leadtime for the entire order by taking an appropriate percentile of the distribution of total processing time and then release the order immediately from stage to stage during the process, may not be optimal since it ignores inventory carrying costs. This article studies a per stage planned leadtime dispatching policy for such systems. The order will not be released immediately to the next workstation prior to a predetermined delivery time, or planned leadtime. The vector of planned leadtimes at workstations is to be determined by trading off expected holding costs at all stages and expected penalty costs for exceeding the total planned leadtime. We show that the optimal vector of planned leadtimes may be obtained efficiently by solving an equivalent serial inventory model of the type considered in Clark and Scarf (1960).

Suggested Citation

  • Linguo Gong & Ton de Kok & Jie Ding, 1994. "Optimal Leadtimes Planning in a Serial Production System," Management Science, INFORMS, vol. 40(5), pages 629-632, May.
    • Handle: RePEc:inm:ormnsc:v:40:y:1994:i:5:p:629-632
    DOI: 10.1287/mnsc.40.5.629
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    Citations

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    Cited by:

    1. Hum, Sin-Hoon & Parlar, Mahmut & Zhou, Yun, 2018. "Measurement and optimization of responsiveness in supply chain networks with queueing structures," European Journal of Operational Research, Elsevier, vol. 264(1), pages 106-118.
    2. Altendorfer, Klaus & Minner, Stefan, 2011. "Simultaneous optimization of capacity and planned lead time in a two-stage production system with different customer due dates," European Journal of Operational Research, Elsevier, vol. 213(1), pages 134-146, August.
    3. Song, Dong-Ping, 2006. "Raw material release time control for complex make-to-order products with stochastic processing times," International Journal of Production Economics, Elsevier, vol. 103(1), pages 371-385, September.
    4. Hadjinicola, George C. & Soteriou, Andreas C., 2003. "Reducing the cost of defects in multistage production systems: A budget allocation perspective," European Journal of Operational Research, Elsevier, vol. 145(3), pages 621-634, March.
    5. van Ooijen, H. P. G. & Bertrand, J. W. M., 2001. "Economic due-date setting in job-shops based on routing and workload dependent flow time distribution functions," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 261-268, December.
    6. Inderfurth, K. & de Kok, A. G. & Flapper, S. D. P., 2001. "Product recovery in stochastic remanufacturing systems with multiple reuse options," European Journal of Operational Research, Elsevier, vol. 133(1), pages 130-152, August.
    7. Zümbül Atan & Ton de Kok & Nico P. Dellaert & Richard van Boxel & Fred Janssen, 2016. "Setting Planned Leadtimes in Customer-Order-Driven Assembly Systems," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 122-140, February.
    8. Rong Yuan & Stephen C. Graves, 2016. "Setting optimal production lot sizes and planned lead times in a job shop," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 6105-6120, October.
    9. Diks, E. B. & de Kok, A. G., 1998. "Optimal control of a divergent multi-echelon inventory system," European Journal of Operational Research, Elsevier, vol. 111(1), pages 75-97, November.

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