Abstract
The statistical aspects of proof-testing as they relate to the Weibull cumulative distribution function (cdf) are described. Properties of the truncated Weibull cdf which arise from proof testing are presented. The need for accurate parameter estimation techniques is discussed, and the maximum likelihood (ML) method is developed for this application. Two examples are given which demonstrate the applicability and usefulness of the truncated Weibull cdf. One example, developed from proof-testing single filaments, illustrates the results for ungrouped data. The other, taken from an application of optical image analysis of creep cavities in stain less steel, is an example of the analysis for grouped data.
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