IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v36y1990i12p1532-1547.html
   My bibliography  Save this article

Adjusting Replenishment Orders to Reflect Learning in a Material Requirements Planning Environment

Author

Listed:
  • Larry R. Dolinsky

    (Operations Management Department, Bentley College, Waltham, Massachusetts 02154-4705)

  • Thomas E. Vollmann

    (School of Management, Boston University, Boston, Massachusetts 02215)

  • Michael J. Maggard

    (College of Business Administration, Northeastern University, Boston, Massachusetts 02254)

Abstract

Some manufacturing firms, particularly in the high-technology sector, have production processes which are characterized by very low initial yields followed by steady "experience" based yield improvement. Material Requirements Planning literature reveals that MRP implementations are seldom adjusted in any systematic way to account for such yield improvement. A single product, single stage MRP model is developed which incorporates learning curve behavior into conventional MRP logic. A series of experiments systematically examine the impact on mean inventory level of various combinations of environmental conditions and managerial policies. The research demonstrates that substantial reductions in mean inventory levels can be realized in low yield environments if learning is properly included in the order release logic. This finding proves to be robust with respect to modest errors in the estimation of learning rate.

Suggested Citation

  • Larry R. Dolinsky & Thomas E. Vollmann & Michael J. Maggard, 1990. "Adjusting Replenishment Orders to Reflect Learning in a Material Requirements Planning Environment," Management Science, INFORMS, vol. 36(12), pages 1532-1547, December.
  • Handle: RePEc:inm:ormnsc:v:36:y:1990:i:12:p:1532-1547
    DOI: 10.1287/mnsc.36.12.1532
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.36.12.1532
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.36.12.1532?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. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2008. "Learning curves for imperfect production processes with reworks and process restoration interruptions," European Journal of Operational Research, Elsevier, vol. 189(1), pages 93-104, August.
    2. Jaber, M.Y. & Goyal, S.K. & Imran, M., 2008. "Economic production quantity model for items with imperfect quality subject to learning effects," International Journal of Production Economics, Elsevier, vol. 115(1), pages 143-150, September.
    3. Jaber, Mohamad Y. & Khan, Mehmood, 2010. "Managing yield by lot splitting in a serial production line with learning, rework and scrap," International Journal of Production Economics, Elsevier, vol. 124(1), pages 32-39, March.
    4. Linda Argote & Sunkee Lee & Jisoo Park, 2021. "Organizational Learning Processes and Outcomes: Major Findings and Future Research Directions," Management Science, INFORMS, vol. 67(9), pages 5399-5429, September.

    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:36:y:1990:i:12:p:1532-1547. 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.