IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-33012-4_16.html
   My bibliography  Save this book chapter

An Optimal Product Mix Decision Model Considering Unit-Batch-Product Level Cost for Steel Plant

In: Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012)

Author

Listed:
  • Hu-sheng Lu

    (Inner Mongolia University of Science and Technology)

  • Guo-qiang Lv

    (Inner Mongolia University of Science and Technology)

Abstract

In recent years, the iron and steel industry’s operation condition has been continuously worsening, profitability reducing, thus the product mix decision (PMD) for the iron and steel enterprises became research focus to reduce manufacturing costs and maximize profits. Taking into account unit-level, batch-level and product-level cost, an integrated model conducting product mix decision for steelmaking, continuous casting and hot rolling (SM-CC-HR) process was proposed in this paper. A numerical example was presented to illustrate data input, solution method and result analysis. By comparing the model with two traditional ones, it was showed that the model attained higher profit and smoother implementation, because it traced the cost appropriately and effectively reduced the volume of left slabs in manufacturing processes and that of left steel products after order-delivery.

Suggested Citation

  • Hu-sheng Lu & Guo-qiang Lv, 2013. "An Optimal Product Mix Decision Model Considering Unit-Batch-Product Level Cost for Steel Plant," Springer Books, in: Runliang Dou (ed.), Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012), edition 127, chapter 0, pages 147-157, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-33012-4_16
    DOI: 10.1007/978-3-642-33012-4_16
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:sprchp:978-3-642-33012-4_16. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.