IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v33y2017i5p494-506.html
   My bibliography  Save this article

Computing optimum design parameters of a progressive type I interval censored life test from a cost model

Author

Listed:
  • Sonal Budhiraja
  • Biswabrata Pradhan

Abstract

This work considers optimum design of a life testing experiment with progressive type I interval censoring. A cost minimization‐based optimality criterion is proposed. The proposed cost function incorporates the cost of conducting the experiment, opportunity cost, and post‐sale cost. It is shown that the proposed cost function is scale invariant for any lifetime distribution whose support does not depend on the parameters of the distribution. Weibull distribution is considered for illustration. Optimum solution is obtained by a suitable numerical method. A sensitivity analysis is undertaken to study the effect of small perturbations in lifetime model parameter values or cost coefficients. Copyright © 2017 John Wiley & Sons, Ltd.

Suggested Citation

  • Sonal Budhiraja & Biswabrata Pradhan, 2017. "Computing optimum design parameters of a progressive type I interval censored life test from a cost model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(5), pages 494-506, September.
    • Handle: RePEc:wly:apsmbi:v:33:y:2017:i:5:p:494-506
    DOI: 10.1002/asmb.2251
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.2251
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.2251?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
    ---><---

    Citations

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


    Cited by:

    1. Shuvashree Mondal & Ritwik Bhattacharya & Biswabrata Pradhan & Debasis Kundu, 2020. "Bayesian optimal life‐testing plan under the balanced two sample type‐II progressive censoring scheme," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(4), pages 628-640, July.

    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:wly:apsmbi:v:33:y:2017:i:5:p:494-506. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.