IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v56y2018i3p1249-1268.html
   My bibliography  Save this article

Optimal job assignment considering operators’ walking costs and ergonomic aspects

Author

Listed:
  • Elisa Gebennini
  • Luca Zeppetella
  • Andrea Grassi
  • Bianca Rimini

Abstract

The paper deals with the problem of assigning jobs to operators in contexts where the operators are not fixed on a single position, but rotate, by travelling on foot, between different stations. The objective is to jointly consider the need for minimising the operators’ walking costs, expressed as both unproductive times and physiological costs, and the ergonomic risk of the scheduled jobs and their combinations. A new optimisation-based methodology is presented by developing a systematic procedure for input data analysis and an original mixed-integer linear programming model which minimises the cost of walking (or the total metabolic cost) by considering workplace safety and physiological needs. Finally, the proposed optimisation approach has been applied to a case study from the plastic industry. The obtained results allow to draw some interesting conclusions about the impact of ergonomic aspects on the optimal assignment of jobs to operators. Moreover, the importance of reducing unproductive times (i.e. walking times) and, if possible, improving the design of manual tasks (e.g. lifting operations) is highlighted by showing that even small ergonomic investments may lead to significant cost savings.

Suggested Citation

  • Elisa Gebennini & Luca Zeppetella & Andrea Grassi & Bianca Rimini, 2018. "Optimal job assignment considering operators’ walking costs and ergonomic aspects," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1249-1268, February.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1249-1268
    DOI: 10.1080/00207543.2017.1414327
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2017.1414327
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2017.1414327?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. Hashemi-Petroodi, S. Ehsan & Thevenin, Simon & Kovalev, Sergey & Dolgui, Alexandre, 2022. "Model-dependent task assignment in multi-manned mixed-model assembly lines with walking workers," Omega, Elsevier, vol. 113(C).

    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:56:y:2018:i:3:p:1249-1268. 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.