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An economic order quantity model for an imperfect production process with entropy cost

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  • Jaber, M.Y.
  • Bonney, M.
  • Moualek, I.
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    Abstract

    Among the assumptions of the classical economic order quantity (EOQ) model is that all units that are purchased (or produced) are of perfect quality. However, this is frequently unrealistic since production processes deteriorate resulting in the production of defective products requiring rework. Some recent studies suggest that production systems performance might be improved by applying the first and second laws of thermodynamics to reduce system entropy (or disorder). This paper applies the concept of entropy cost to extend the classical EOQ model under the assumptions of perfect and imperfect quality. Mathematical models are developed and numerical examples illustrating the solution procedure are provided. Accounting for entropy cost suggests that order quantities should be larger than the figures derived from the classical EOQ model.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 118 (2009)
    Issue (Month): 1 (March)
    Pages: 26-33

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    Handle: RePEc:eee:proeco:v:118:y:2009:i:1:p:26-33

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    Web page: http://www.elsevier.com/locate/ijpe

    Related research

    Keywords: Lot sizing Defects Rework Entropy cost;

    References

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    1. Jaber, Mohamad Y. & Rosen, Marc A., 2008. "The economic order quantity repair and waste disposal model with entropy cost," European Journal of Operational Research, Elsevier, vol. 188(1), pages 109-120, July.
    2. Chyr, Fuchiao & Lin, Tsong Ming & Ho, Chin-Fu, 1990. "Comparison between just-in-time and EOQ system," Engineering Costs and Production Economics, Elsevier, vol. 18(3), pages 233-240, January.
    3. Geren, Necdet & Redford, Alan, 1999. "Cost and performance analysis of a robotic rework cell," International Journal of Production Economics, Elsevier, vol. 58(2), pages 159-172, January.
    4. Chand, Suresh, 1989. "Lot sizes and setup frequency with learning in setups and process quality," European Journal of Operational Research, Elsevier, vol. 42(2), pages 190-202, September.
    5. Agnihothri, Saligrama R. & Kenett, Ron S., 1995. "The impact of defects on a process with rework," European Journal of Operational Research, Elsevier, vol. 80(2), pages 308-327, January.
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    Cited by:
    1. Björk, Kaj-Mikael, 2012. "A multi-item fuzzy economic production quantity problem with a finite production rate," International Journal of Production Economics, Elsevier, vol. 135(2), pages 702-707.
    2. Yoo, Seung Ho & Kim, DaeSoo & Park, Myung-Sub, 2009. "Economic production quantity model with imperfect-quality items, two-way imperfect inspection and sales return," International Journal of Production Economics, Elsevier, vol. 121(1), pages 255-265, September.
    3. Erjavec, J. & Gradisar, M. & Trkman, P., 2012. "Assessment of stock size to minimize cutting stock production costs," International Journal of Production Economics, Elsevier, vol. 135(1), pages 170-176.
    4. Nadeau, Marie-Claude & Kar, Ashish & Roth, Richard & Kirchain, Randolph, 2010. "A dynamic process-based cost modeling approach to understand learning effects in manufacturing," International Journal of Production Economics, Elsevier, vol. 128(1), pages 223-234, November.

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