• DocumentCode
    127037
  • Title

    Optimal inspection model for a load-sharing redundant system

  • Author

    Taghipour, S.

  • Author_Institution
    Dept. of Mech. & Ind. Eng., Ryerson Univ., Toronto, ON, Canada
  • fYear
    2014
  • fDate
    27-30 Jan. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper we consider a k-out-of-n load sharing system, in which the failure of a component increases the hazard rates of the surviving components. The components failures follow a power law intensity function. The system is periodically inspected to detect failed components if the number of failures is less than n-k+1. However, the system fails when the number of failures equals to n-k+1, which is when all components are opportunistically inspected and repaired if they are in a failed state. Two models of load-sharing are considered: a tampered failure rate model, in which only the scale parameter of the power law is affected due to a change in load, and the cumulative exposure (CE) model, in which both the scale parameter and the ages of the surviving components are affected. We propose a model to find the optimal inspection interval for such systems, and describe the application of the model in several case studies. The results reveal that a system with the CE model requires to be inspected more frequently to avoid a high penalty incurred due to system failure. Moreover, shorter inspection interval is also required for a system with higher load intensity.
  • Keywords
    redundancy; CE model; cumulative exposure model; k-out-of-n load sharing system; load-sharing redundant system; optimal inspection model; power law intensity function; system failure; tampered failure rate model; Equations; Hazards; Inspection; Load modeling; Maintenance engineering; Mathematical model; Reliability; Inspection optimization; cumulative exposure; k-out-of-n; load-sharing; tampered failure rate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium (RAMS), 2014 Annual
  • Conference_Location
    Colorado Springs, CO
  • Print_ISBN
    978-1-4799-2847-7
  • Type

    conf

  • DOI
    10.1109/RAMS.2014.6798466
  • Filename
    6798466