IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v41y1995i4p620-636.html
   My bibliography  Save this article

Optimal Operating Policy for a Bottleneck with Random Rework

Author

Listed:
  • Kut C. So

    (Graduate School of Management, University of California, Irvine, California 92717)

  • Christopher S. Tang

    (Anderson Graduate School of Management, University of California, Los Angeles, California 90024)

Abstract

This paper presents a model of a bottleneck facility that performs two distinct types of operations: "regular" and "rework." Each job is subjected to a test after completing the regular operation at the bottleneck. If the job passes the test, then it continues its process downstream. Otherwise, the job will cycle back to the bottleneck stage for rework operation. Upon the completion of a batch of regular jobs, the decision maker observes the amount of rework and decides on whether to switch over to process the reworks or continue to process another batch of regular jobs. It is assumed that both switch-over time and cost are incurred when the facility switches from performing one type of operation to a different type. The goal of the analysis is to characterize the optimal operating policy for the bottleneck so that the average operating cost is minimized. In order to characterize the optimal operating policy, we first formulate the problem as a semi-Markov decision process. Then we show that there exists an optimal "threshold" operating policy that can be described as follows: upon completion of a batch of regular jobs, switch over to process the reworks only if the number of reworks exceeds a critical value. In addition, we develop a simple procedure to compute the critical value that specifies the optimal threshold policy. Moreover, we evaluate the impact of batch sizes, yield, and switch-over time on the optimal threshold policy.

Suggested Citation

  • Kut C. So & Christopher S. Tang, 1995. "Optimal Operating Policy for a Bottleneck with Random Rework," Management Science, INFORMS, vol. 41(4), pages 620-636, April.
    • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:4:p:620-636
    DOI: 10.1287/mnsc.41.4.620
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.41.4.620
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.41.4.620?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sarker, Bhaba R. & Jamal, A.M.M. & Mondal, Sanjay, 2008. "Optimal batch sizing in a multi-stage production system with rework consideration," European Journal of Operational Research, Elsevier, vol. 184(3), pages 915-929, February.
    2. S. Priyan & R. Uthayakumar, 2017. "Setup cost reduction EMQ inventory system with probabilistic defective and rework in multiple shipments management," 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. 8(2), pages 223-241, June.
    3. Flapper, Simme Douwe P. & Teunter, Ruud H., 2004. "Logistic planning of rework with deteriorating work-in-process," International Journal of Production Economics, Elsevier, vol. 88(1), pages 51-59, March.
    4. G C Hadjinicola, 2010. "Manufacturing costs in serial production systems with rework," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 342-351, February.
    5. Sonntag, Danja & Kiesmüller, Gudrun P., 2018. "Disposal versus rework – Inventory control in a production system with random yield," European Journal of Operational Research, Elsevier, vol. 267(1), pages 138-149.
    6. Chiu, Yuan-Shyi Peter & Chiu, Victoria & Lin, Hong-Dar & Chang, Huei-Hsin, 2019. "Meeting multiproduct demand with a hybrid inventory replenishment system featuring quality reassurance," Operations Research Perspectives, Elsevier, vol. 6(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:41:y:1995:i:4:p:620-636. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.