Name
Abstract | ||
|---|---|---|
In this article, we propose control charts for the quantiles of the Weibull distribution, for type II censored data, based on the distribution of a pivotal quantity conditioned on ancillary statistics. These control charts must be considered as alternatives to bootstrap type control charts. We derive an analytical form of the conditional distribution function of the monitored statistic and we use this function to propose ARL-unbiased control limits. We further demonstrate that the proposed conditional chart have a general analytical form for the ARL that can be evaluated numerically without use of simulations and we also show that these charts perform at least as well as the bootstrap type ones. We finally apply the conditional charts to a dataset on the strength of carbon fibers to detect shifts in a specifiedWeibull quantile. Copyright (c) 2014 JohnWiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1002/qre.1698 | QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL |
Keywords | Field | DocType |
average run length,conditional charts,statistical process control,unbiased control charts,Weibull quantiles | Econometrics,Control limits,Pivotal quantity,Posterior probability,Control chart,Quantile,Statistical process control,Prior probability,Statistics,Censoring (statistics),Mathematics | Journal |
Volume | Issue | ISSN |
31 | 8 | 0748-8017 |
Citations | PageRank | References |
7 | 0.62 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Firoozeh Haghighi | 1 | 16 | 2.54 |
| Francis Pascual | 2 | 97 | 14.35 |
| Philippe Castagliola | 3 | 529 | 61.65 |