IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-0-85729-118-9_2.html
   My bibliography  Save this book chapter

Models for Perfect Repair

In: Applied Nonparametric Statistics in Reliability

Author

Listed:
  • M. Luz Gámiz

    (Universidad Granada)

  • K. B. Kulasekera

    (Clemson University)

  • Nikolaos Limnios

    (Université de Technologie de Compiègne)

  • Bo Henry Lindqvist

    (Norwegian University of Science and Technology)

Abstract

In this chapter, we begin with the study of repairable systems. Specifically, we study probabilistic models for systems which after failure are replaced by a new one exactly. We say then that the system operating state is restored to “as good as new” conditions after failure. In the first approach to this kind of systems, we assume that the system is repaired (replaced) and put into new operation immediately after the failure. The sample information that we analyze consist of a sequence of random variables independent and identically distributed, which represent the time between two consecutive failures. The model that we consider in this situation is a Renewal Process, and the main purpose is to present and compare several ways of nonparametrically estimate the renewal function, that is, the expected number of failures occurring in the system up to a given time t. When the repair times are of interest, the data collected consist of a sequence of alternating up and down periods. The modeling tool indicated in this case is the Alternating Renewal Process, and we will concentrate on estimating the availability function (the probability that the system is functioning at a given time) using nonparametric techniques.

Suggested Citation

  • M. Luz Gámiz & K. B. Kulasekera & Nikolaos Limnios & Bo Henry Lindqvist, 2011. "Models for Perfect Repair," Springer Series in Reliability Engineering, in: Applied Nonparametric Statistics in Reliability, chapter 0, pages 33-64, Springer.
    • Handle: RePEc:spr:ssrchp:978-0-85729-118-9_2
    DOI: 10.1007/978-0-85729-118-9_2
    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.

    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:978-0-85729-118-9_2. 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.