• DocumentCode
    1495120
  • Title

    Some statistical characteristics of a repairable, standby, human and machine system

  • Author

    Sridharan, Varadachari ; Mohanavadivu, Periasamy

  • Author_Institution
    Anna Univ., Chennai, India
  • Volume
    47
  • Issue
    4
  • fYear
    1998
  • fDate
    12/1/1998 12:00:00 AM
  • Firstpage
    431
  • Lastpage
    435
  • Abstract
    This paper presents a model for a two-unit s-identical system with one operating-unit (OU) online and the other, warm standby-unit (SU) human machine system. The failure rates for both the OU and SU (common-cause, human error and hardware failures) are constant, whereas the repair times are arbitrarily distributed for a failed system. Linear ordinary differential equations are used to obtain a general expression for system steady-state availability for failed system by taking the repair time distributions as Gamma. Generalized expressions for system reliability, and time-dependent availability are presented. Graphs demonstrate the impact of human error on system steady-state availability for various distributions, and some physical meaning is given. As time increases, the time-dependent availability decreases for exponential repair time distribution for different values of initial human error rate
  • Keywords
    failure analysis; gamma distribution; human factors; maintenance engineering; reliability theory; statistical analysis; exponential repair time distribution; failure rates; gamma distributions; human error; human error rate; human machine system; linear ordinary differential equations; operating-unit; reliability; repair times; standby-unit; statistical characteristics; steady-state availability; time-dependent availability; two-unit s-identical system; Availability; Differential equations; Error analysis; Genetic expression; Hardware; Humans; Man machine systems; Reactive power; Reliability; Steady-state;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/24.756086
  • Filename
    756086