IDEAS home Printed from https://ideas.repec.org/a/ids/ijpmbe/v2y2008i3p234-248.html
   My bibliography  Save this article

A proposal: evaluation of OEE and impact of six big losses on equipment earning capacity

Author

Listed:
  • Anil S. Badiger
  • R. Gandhinathan

Abstract

In the recent past maintenance strategy has gained heightened importance in organisations and requires the manufacturing and maintenance managers to develop and follow well devised production and maintenance plans. Remarkable improvement has taken place in the maintenance management of physical assets and productive systems, to reduce wastage of energy and resources. Overall Equipment Effectiveness (OEE) methodology is a proven approach to increase overall performance of equipment. In the present paper, a method is proposed to evaluate OEE by including a factor known as usability, in the OEE calculation method. Further, an approach is developed to evaluate the earning capacity of addressing the six big losses, with incremental improvement in OEE, as an extension to the maturity of OEE.

Suggested Citation

  • Anil S. Badiger & R. Gandhinathan, 2008. "A proposal: evaluation of OEE and impact of six big losses on equipment earning capacity," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 2(3), pages 234-248.
    • Handle: RePEc:ids:ijpmbe:v:2:y:2008:i:3:p:234-248
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=17962
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Kanwal Zehra & Nayyar Hussain Mirjat & Shakeel Ahmed Shakih & Khanji Harijan & Laveet Kumar & Mamdouh El Haj Assad, 2024. "Optimizing Auto Manufacturing: A Holistic Approach Integrating Overall Equipment Effectiveness for Enhanced Efficiency and Sustainability," Sustainability, MDPI, vol. 16(7), pages 1-32, April.
    2. Muhammad Babar Ramzan & Hafsa Jamshaid & Ismial Usman & Rajesh Mishra, 2022. "Development and Evaluation of Overall Equipment Effectiveness of Knitting Machines Using Statistical Tools," SAGE Open, , vol. 12(2), pages 21582440221, April.
    3. Jorge Luis García Alcaraz & Adrián Salvador Morales García & José Roberto Díaz Reza & Julio Blanco Fernández & Emilio Jiménez Macías & Rita Puig i Vidal, 2022. "Machinery Lean Manufacturing Tools for Improved Sustainability: The Mexican Maquiladora Industry Experience," Mathematics, MDPI, vol. 10(9), pages 1-18, April.

    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:ids:ijpmbe:v:2:y:2008:i:3:p:234-248. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=95 .

    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.