A bootstrap control chart for Birnbaum-Saunders percentiles

Abstract

The problem of detecting a shift in the percentile of a Birnbaum-Saunders population in a process monitoring situation is considered. For example, such problems may arise when the quality characteristic of interest is tensile strength or breaking stress. The parametric bootstrap method is used to develop a quality control chart for monitoring percentiles when process measurements have a Birnbaum-Saunders distribution. Through extensive Monte Carlo simulations, we investigate the behavior and performance of the proposed bootstrap percentile charts. Average run lengths of the proposed percentile chart are also investigated. Illustrative examples with the data concerning the tensile strength of the aluminum sheeting are presented. Copyright © 2008 John Wiley & Sons, Ltd.