• DocumentCode
    1315383
  • Title

    Estimation of Weibull Parameters With Competing-Mode Censoring

  • Author

    McCool, John I.

  • Author_Institution
    SKF Industries, Inc.//Technology Center//1100 First Avenue//King of Prussia//Pennsylvania 19406 USA
  • Issue
    1
  • fYear
    1976
  • fDate
    4/1/1976 12:00:00 AM
  • Firstpage
    25
  • Lastpage
    31
  • Abstract
    Existing results are reviewed for the maximum likelihood (ML) estimation of the parameters of a 2-parameter Weibull life distribution for the case where the data are censored by failures due to an arbitrary number of independent 2-parameter Weibull failure modes. For the case where all distributions have a common but unknown shape parameter the joint ML estimators are derived for i) a general percentile of the j-th distribution, ii) the common shape parameter, and iii) the proportion of failures due to failure mode j. Exact interval estimates of the common shape parameter are constructable in terms of the ML estimates obtained by using i) the data without regard to failure mode, and ii) existing tables of the percentage points of a certain pivotal function. Exact interval estimates for a general percentile of failure-mode-j distribution are calculable when the failure proportion due to failure-mode-j is known; otherwise a joint s-confidence region for the percentile and failure proportion is calculable. It is shown that sudden death endurance test results can be analyzed as a special case of competing-mode censoring. Tabular values for the construction of interval estimates for the 10-th percentile of the failure-mode-j distribution are given for 17 combinations of sample size (from 5 to 30) and number of failures.
  • Keywords
    Accidents; Diseases; Failure analysis; Humans; Life estimation; Life testing; Maximum likelihood estimation; Parameter estimation; Probability; Shape; Competing risks; Confidence interval; Failure mode; Weibull distribution;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/TR.1976.5214946
  • Filename
    5214946