IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v56y2018i6p2370-2387.html
   My bibliography  Save this article

Systematic continuous improvement model for variation management of key characteristics running with low capability

Author

Listed:
  • Gabriela Estrada
  • Dan L. Shunk
  • Feng Ju

Abstract

A systematic continuous improvement model (SCIM) is described in this paper. This model responds to improvements opportunities that were identified in the literature and aerospace companies to aim in variation management of KCs and for developing solutions to improve issues in KCs. This approach helps to identify and improve key characteristics (KCs) in products that most influence in rework and scrap costs, especially in material removal processes. SCIM complies with two purposes; a mathematical method to calculate the rework cost for KCs as a variable in function of expected amount of material to be removed. This cost plus scrap cost is used to prioritise KCs running with low capability; this prioritisation is performed by predicting rework and scrap costs based on historical data of manufacturing processes performance, costs associated to rework and scrap parts out of specification and forecast for product demand. Once critical KCs are identified, the second purpose of this model helps engineers to develop solutions to eliminate what is causing KCs running with low capability; this is possible using knowledge management methodologies to capture, structure and storage solutions developed, in order to reuse them in future similar issues. A case study is presented in this paper to apply this model.

Suggested Citation

  • Gabriela Estrada & Dan L. Shunk & Feng Ju, 2018. "Systematic continuous improvement model for variation management of key characteristics running with low capability," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2370-2387, March.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2370-2387
    DOI: 10.1080/00207543.2017.1369599
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2017.1369599
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2017.1369599?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. Mobin, Mohammadsadegh & Li, Zhaojun & Cheraghi, S. Hossein & Wu, Gongyu, 2019. "An approach for design Verification and Validation planning and optimization for new product reliability improvement," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    2. Gongyu Wu & Zhaojun (Steven) Li & Pan Liu, 2022. "Risk-informed reliability improvement optimization for verification and validation planning based on set covering modeling," Journal of Risk and Reliability, , vol. 236(2), pages 357-370, April.

    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:6:p:2370-2387. 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.