• DocumentCode
    778942
  • Title

    A discretizing approach for stress/strength analysis

  • Author

    English, John R. ; Sargent, Tom ; Landers, Thomas L.

  • Author_Institution
    Dept. of Ind. Eng., Arkansas Univ., Fayetteville, AR, USA
  • Volume
    45
  • Issue
    1
  • fYear
    1996
  • fDate
    3/1/1996 12:00:00 AM
  • Firstpage
    84
  • Lastpage
    89
  • Abstract
    This paper implements and evaluates a discretizing approach for estimating the reliability of systems for which complex functions define strength or stress and where the derivation of reliability exceed analytic techniques. The discretizing approach predicts system reliability with reasonably high accuracy. Specifically, there is little difference in the accuracy of predictions for three engineering problems when compared to simulation results. The reliability predictions are near the 95% confidence intervals of the simulation results and are best in the high reliability and low reliability regions. The small errors observed are attributed to the estimation errors of the discretizing approach. The mid-range reliability values (e.g. 50% reliability) are not generally of interest in engineering applications, and even for these value, the errors are small. There is little improvement in increasing the number of points in the pmf from 3 to 6. Due to this small difference, 3 discretizing points are recommended for reliability predictions when computational ease is of concern and limited to 4 points when more accurate reliability predictions are required. This paper models three systems and evaluates the robustness (departures from assumed distributions) of the discretizing approach. The discretizing approach is not too sensitive to departures from the assumed distribution of the underlying random variables regions are accurately estimated
  • Keywords
    mechanical strength; random processes; reliability theory; stress analysis; Gaussian case; confidence intervals; discretizing approach; high reliability; low reliability; near Gaussian case; reliability estimation; robustness evaluation; stress/strength analysis; system reliability prediction; underlying random variables regions; Engine cylinders; Interference; Marine vehicles; Reliability engineering; Reliability theory; State estimation; Statistical distributions; Stress; System testing; Torque;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/24.488921
  • Filename
    488921