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A Study of Production Smoothing in a Job Shop Environment

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Author Info

  • Allan B. Cruickshanks

    (Rolm Corp., Austin, Texas)

  • Robert D. Drescher

    (Rolm Corp., Austin, Texas)

  • Stephen C. Graves

    (Massachusetts Institute of Technology)

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    Abstract

    We consider the problem of smoothing production in a job shop in which all production is to customer order and the demand process is a stationary stochastic process. We present an approach to production smoothing based on the concept of a planning window. A planning window is the difference between the promised delivery time and the planned production time for a product. It represents the degree of flexibility available for planning the production of committed orders. We characterize the production smoothing benefits for a range of planning windows by means of an approximate analytic model and a simulation study. These analyses show that substantial smoothing benefits result from small changes in the length of the planning window. We discuss the implementation of the production smoothing approach and illustrate this implementation with an industrial case study that was the motivation for this work.

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    File URL: http://dx.doi.org/10.1287/mnsc.30.3.368
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 30 (1984)
    Issue (Month): 3 (March)
    Pages: 368-380

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    Handle: RePEc:inm:ormnsc:v:30:y:1984:i:3:p:368-380

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    Related research

    Keywords: production/scheduling: job shop; stochastic; production smoothing;

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    Cited by:
    1. Graves, Stephen C., 1984. "Operational analysis of a job shop," Working papers 1552-84., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Graves, Stephen C., 1985. "Determining the spares and staffing level for a repair depot," Working papers 1699-85., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. Graves, Stephen C. & Meal, Harlan C. & Dasu, Sririam. & Qui, Yuping., 1985. "Two-stage production planning in a dynamic environment," Working papers 1698-85., Massachusetts Institute of Technology (MIT), Sloan School of Management.

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