IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v91y1999i0p137-16110.1023-a1018989404805.html
   My bibliography  Save this article

Optimal Stress Screening strategies formulti‐component systems sold under warranty:The case of phase‐type lifetimes

Author

Listed:
  • E.A. Pohl
  • D.L. Dietrich

Abstract

Environmental Stress Screening (ESS) is employed to reduce, if not eliminate, the occurrenceof early field failures. This paper examines the necessary trade‐offs between thereduction in warranty costs and the increase in manufacturing costs associated with optimalstress screening strategies. A multi‐level ESS model is presented for a multi‐componentelectronic system. Screening can be performed at component, unit, and system levels. Componentsand connections are assumed to come from good and substandard populations andtheir time‐to‐failure distributions are modeled by mixed distributions. The majority of ESSmodels found in the literature assume that the time‐to‐failure distributions are exponential.The exponential distribution is used primarily to take advantage of its mathematical tractability.This paper generalizes previous work by modeling component and connection lifetimes withphase-type distributions. Phase‐type distributions offer the advantage of mathematical tractabilityas well as versatility in the family of distributions they can represent. To date thereis no significant research into the impact that the selection of a lifetime distributions formodeling the failure process has on ESS decisions. In this paper, we evaluate screeningstrategies for several lifetime distributions. Numerical examples are provided to illustratethe effect of various model parameters on the optimal stress screening strategy. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • E.A. Pohl & D.L. Dietrich, 1999. "Optimal Stress Screening strategies formulti‐component systems sold under warranty:The case of phase‐type lifetimes," Annals of Operations Research, Springer, vol. 91(0), pages 137-161, January.
  • Handle: RePEc:spr:annopr:v:91:y:1999:i:0:p:137-161:10.1023/a:1018989404805
    DOI: 10.1023/A:1018989404805
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018989404805
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1018989404805?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. Zhi-Sheng Ye & Loon-Ching Tang & Min Xie, 2014. "Bi-objective burn-in modeling and optimization," Annals of Operations Research, Springer, vol. 212(1), pages 201-214, January.

    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:spr:annopr:v:91:y:1999:i:0:p:137-161:10.1023/a:1018989404805. 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: 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.