IDEAS home Printed from https://ideas.repec.org/a/spr/fuzodm/v24y2025i2d10.1007_s10700-025-09445-1.html
   My bibliography  Save this article

Computing weighted overall equipment effectiveness based on a fuzzy approach: a comparative study with an application

Author

Listed:
  • Adil Baykasoğlu

    (Dokuz Eylül University)

  • Elif Yoruk

    (Dokuz Eylül University)

Abstract

This paper introduces a new method for calculating weighted Overall Equipment Effectiveness (OEE) by using fuzzy logic. Traditional crisp methods for computing weighted OEE have limitations due to the multiplicative nature of the OEE equation, leading to questionable outcomes. OEE is computed as the product of three key factors -Availability, Performance and Quality- that means that even a small reduction in any one factor results in a disproportionately lower OEE value. This multiplicative structure also makes it difficult to incorporate weighting mechanisms fairly. Previous literature has explored fuzzy logic-based approaches, particularly fuzzy rule-based methods, which do not necessitate the multiplication of OEE variables (Availability, Performance, and Quality). These fuzzy logic approaches can also handle system uncertainties and yield satisfactory results. However, there is currently no study in the literature for calculating weighted OEE by utilizing fuzzy rule-based techniques. The current paper outlines an approach to address this issue, accompanied by a case study conducted in an actual manufacturing company. Additionally, alternative weighted OEE computation methods are also evaluated for demonstrating suitability of the proposed approach.

Suggested Citation

  • Adil Baykasoğlu & Elif Yoruk, 2025. "Computing weighted overall equipment effectiveness based on a fuzzy approach: a comparative study with an application," Fuzzy Optimization and Decision Making, Springer, vol. 24(2), pages 251-269, June.
  • Handle: RePEc:spr:fuzodm:v:24:y:2025:i:2:d:10.1007_s10700-025-09445-1
    DOI: 10.1007/s10700-025-09445-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10700-025-09445-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10700-025-09445-1?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.

    References listed on IDEAS

    as
    1. Marcello Braglia & Roberto Gabbrielli & Leonardo Marrazzini, 2019. "Overall Task Effectiveness: a new Lean performance indicator in engineer-to-order environment," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 68(2), pages 407-422, January.
    2. Pardeep Gupta & Sachit Vardhan, 2016. "Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: a case study," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 2976-2988, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Santosh B. Rane & Sandesh Wavhal & Prathamesh R. Potdar, 2023. "Integration of Lean Six Sigma with Internet of Things (IoT) for productivity improvement: a case study of contactor manufacturing industry," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1990-2018, October.
    2. Hung, Yick-Hin & Li, Leon Y.O. & Cheng, T.C.E., 2022. "Uncovering hidden capacity in overall equipment effectiveness management," International Journal of Production Economics, Elsevier, vol. 248(C).
    3. Alberuni Aziz & Subrata Talapatra & H. M. Belal, 2024. "Improving Equipment Effectiveness through Visual Stream Mapping: Some Exploratory Research Findings in the Ready-Made Garment (RMG) Sector," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(2), pages 303-324, June.
    4. Cannas, Violetta Giada & Gosling, Jonathan, 2021. "A decade of engineering-to-order (2010–2020): Progress and emerging themes," International Journal of Production Economics, Elsevier, vol. 241(C).

    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:fuzodm:v:24:y:2025:i:2:d:10.1007_s10700-025-09445-1. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.