IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v236y2022i5p710-726.html
   My bibliography  Save this article

Root cause identification approach using decomposition of QFD and extended RPN for product manufacturing reliability degradation

Author

Listed:
  • Anqi Zhang
  • Yihai He
  • Chengcheng Wang
  • Jishan Zhang
  • Zixuan Zhang

Abstract

Reliability is reflected in product during manufacturing. However, due to uncontrollable factors during production, product reliability may degrade substantially after manufacturing. Thus, root cause analysis is important in identifying vulnerable parameters to prevent the product reliability degradation in manufacturing. Therefore, a novel root cause identification approach based on quality function deployment (QFD) and extended risk priority number (RPN) is proposed to prevent the degradation of product manufacturing reliability. First, the connotation of product manufacturing reliability and its degradation mechanism are expounded. Second, the associated tree of the root cause of product manufacturing reliability degradation is established using the waterfall decomposition of QFD. Third, the classic RPN is extended to focus on importance to reliability characteristics, probability, and un-detectability. Furthermore, fuzzy linguistic is adopted and the integrated RPN is calculated to determine the risk of root causes. Therefore, a risk-oriented root cause identification technique of product manufacturing reliability degradation is proposed using RPN. Finally, a root cause identification of an engine component is presented to verify the effectiveness of this method. Results show that the proposed approach can identify the root cause objectively and provide reference for reliability control during production.

Suggested Citation

  • Anqi Zhang & Yihai He & Chengcheng Wang & Jishan Zhang & Zixuan Zhang, 2022. "Root cause identification approach using decomposition of QFD and extended RPN for product manufacturing reliability degradation," Journal of Risk and Reliability, , vol. 236(5), pages 710-726, October.
  • Handle: RePEc:sae:risrel:v:236:y:2022:i:5:p:710-726
    DOI: 10.1177/1748006X211043656
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X211043656
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X211043656?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
    ---><---

    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:sae:risrel:v:236:y:2022:i:5:p:710-726. 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: SAGE Publications (email available below). General contact details of provider: .

    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.