IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v53y2015i2p435-450.html
   My bibliography  Save this article

An Environmental Hedging Point Policy to control production rate and emissions in unreliable manufacturing systems

Author

Listed:
  • A. Ben-Salem
  • A. Gharbi
  • A. Hajji

Abstract

This paper proposes a new Hedging Point Policy (HPP) which integrates environmental concerns into the optimal control of unreliable manufacturing systems. The considered system is composed of a production facility subjects to random failures and producing a product family intended for a given market with stable demand. The manufacturing facility’s operations cause harmful emissions to the environment, and may incur sanctions in the form of an environmental tax imposed by the relevant authorities. Given the significant compromise that must take place between inventory, backlog and taxes costs, the main objective of this paper is to propose a feedback adaptive control policy which provides a better control of the production rate and the emissions generated. Under the HPP category, a new structure called the Environmental Hedging Point Policy (EHPP) is proposed. To illustrate the effectiveness of the proposal, an experimental approach based on simulation modelling, variance analysis and response surface methodology (RSM) is applied. The results show a significant gain in terms of incurred costs compared to those incurred when the system is governed by a classical HPP. An improved version of EHPP is also proposed for systems with high emission rates. Several sensitivity analyses are conducted to illustrate the robustness and effectiveness of the proposed policies.

Suggested Citation

  • A. Ben-Salem & A. Gharbi & A. Hajji, 2015. "An Environmental Hedging Point Policy to control production rate and emissions in unreliable manufacturing systems," International Journal of Production Research, Taylor & Francis Journals, vol. 53(2), pages 435-450, January.
  • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:2:p:435-450
    DOI: 10.1080/00207543.2014.946161
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2014.946161
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2014.946161?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Behnamfar, Reza & Sajadi, Seyed Mojtaba & Tootoonchy, Mahshid, 2022. "Developing environmental hedging point policy with variable demand: A machine learning approach," International Journal of Production Economics, Elsevier, vol. 254(C).
    2. Xu, Bin & Lin, Boqiang, 2015. "Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach," Energy, Elsevier, vol. 83(C), pages 486-495.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:53:y:2015:i:2:p:435-450. 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 Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.