IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v49y2018i2p392-406.html
   My bibliography  Save this article

The (α, β)-cut control charts for process average based on the generalised intuitionistic fuzzy number

Author

Listed:
  • Ali Shabani
  • Saralees Nadarajah
  • Mojtaba Alizadeh

Abstract

Intuitionistic fuzzy set is very useful in providing a flexible model to elaborate uncertainty and vagueness involved in decision-making. In this paper, we introduce the generalised trapezoidal intuitionistic fuzzy number (denoted by GtrIFNB) and then construct the (α, β)-cut X‾˜-R˜$\widetilde{\overline{X}} - \widetilde{R}$ and X‾˜-S˜$\widetilde{\overline{X}} - \widetilde{S}$ control charts for GTrIFNB. We also present fuzzy decisions for in-control and out-of-control of the process, in which membership and non-membership degrees of in-control and out-of-control states of the process mean are computed. We also compare X‾$\overline{X}$ control charts with the constructed control chart by bootstrapping for generalised intuitionistic fuzzy numbers. Finally, a real data application and a numerical example are given, showing flexibility and potentiality of the proposed method.

Suggested Citation

  • Ali Shabani & Saralees Nadarajah & Mojtaba Alizadeh, 2018. "The (α, β)-cut control charts for process average based on the generalised intuitionistic fuzzy number," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(2), pages 392-406, January.
  • Handle: RePEc:taf:tsysxx:v:49:y:2018:i:2:p:392-406
    DOI: 10.1080/00207721.2017.1406550
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2017.1406550
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2017.1406550?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. Iván E. Villalón-Turrubiates & Rogelio López-Herrera & Jorge L. García-Alcaraz & José R. Díaz-Reza & Arturo Soto-Cabral & Iván González-Lazalde & Gerardo Grijalva-Avila & José L. Rodríguez-Álvarez, 2022. "A Non-Invasive Method to Evaluate Fuzzy Process Capability Indices via Coupled Applications of Artificial Neural Networks and the Placket–Burman DOE," Mathematics, MDPI, vol. 10(16), pages 1-27, August.

    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:tsysxx:v:49:y:2018:i:2:p:392-406. 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/TSYS20 .

    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.