IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-1-84800-011-7_7.html
   My bibliography  Save this book chapter

Reliability Prediction and Accelerated Testing

In: Complex System Maintenance Handbook

Author

Listed:
  • E. A. Elsayed

    (Rutgers University)

Abstract

Reliability is one of the key quality characteristics of components, products and systems. It cannot be directly measured and assessed like other quality characteristics but can only be predicted for given times and conditions. Its value depends on the use conditions of the product as well as the time at which it is to be predicted. Reliability prediction has a major impact on critical decisions such as the optimum release time of the product, the type and length of warranty policy and associated duration and cost, and the determination of the optimum maintenance and replacement schedules. Therefore, it is important to provide accurate reliability predictions over time in order to determine accurately the repair, inspection and replacements strategies of products and systems.

Suggested Citation

  • E. A. Elsayed, 2008. "Reliability Prediction and Accelerated Testing," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 7, pages 155-178, Springer.
  • Handle: RePEc:spr:ssrchp:978-1-84800-011-7_7
    DOI: 10.1007/978-1-84800-011-7_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Edyta Brzychczy & Paulina Gackowiec & Mirko Liebetrau, 2020. "Data Analytic Approaches for Mining Process Improvement—Machinery Utilization Use Case," Resources, MDPI, vol. 9(2), pages 1-17, February.

    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:ssrchp:978-1-84800-011-7_7. 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.