IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-319-63423-4_5.html
   My bibliography  Save this book chapter

Optimizing Availability and Performance of a Two-Unit Redundant Multi-state Deteriorating System

In: Recent Advances in Multi-state Systems Reliability

Author

Listed:
  • Sonia Malefaki

    (University of Patras)

  • Vasilis P. Koutras

    (University of the Aegean)

  • Agapios N. Platis

    (University of the Aegean)

Abstract

The most of the contemporary large scale technological systems are functioning under multiple stages of degradation, from their perfect state to their total failure. The study of the performance and the availability of multi-stage systems is of great importance since their deterioration and/or failure may lead to important losses. Under a proper inspection and maintenance policy, it is feasible the operation of the system to be improved significantly. Our main goal is to model multi-state systems with redundancy and to identify the optimal maintenance policies. The system is inspected periodically. Depending on the condition of the system, either no action takes place or maintenance is carried out, either minimal or major. The proposed model takes also into account the scenario of imperfect and failed maintenance. The asymptotic behaviour of the system is studied and optimization problems for the asymptotic availability, the downtime cost and the expected cost due to maintenance and unavailability, with respect to inspection intervals, are formulated and solved.

Suggested Citation

  • Sonia Malefaki & Vasilis P. Koutras & Agapios N. Platis, 2018. "Optimizing Availability and Performance of a Two-Unit Redundant Multi-state Deteriorating System," Springer Series in Reliability Engineering, in: Anatoly Lisnianski & Ilia Frenkel & Alex Karagrigoriou (ed.), Recent Advances in Multi-state Systems Reliability, pages 71-105, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-319-63423-4_5
    DOI: 10.1007/978-3-319-63423-4_5
    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. Fanping Wei & Jingjing Wang & Xiaobing Ma & Li Yang & Qingan Qiu, 2023. "An Optimal Opportunistic Maintenance Planning Integrating Discrete- and Continuous-State Information," Mathematics, MDPI, vol. 11(15), pages 1-19, July.

    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:978-3-319-63423-4_5. 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.