Quality and Reliability Engineering International
| Autor: | Rob Goedhart, William H. Woodall, Ronald J. M. M. Does |
|---|---|
| Přispěvatelé: | Faculteit Economie en Bedrijfskunde, Operations Management (ABS, FEB), Statistics |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
exponentially weighted moving average
0211 other engineering and technologies CUSUM 02 engineering and technology Management Science and Operations Research 01 natural sciences CUSUM control chart 010104 statistics & probability Phase I Statistics Control chart cumulative sum EWMA control chart nonparametric EWMA chart 0101 mathematics Safety Risk Reliability and Quality Mathematics Parametric statistics 021103 operations research Estimation theory Nonparametric statistics Phase II Shewhart control chart Control limits Parametric model parameter estimation |
| Zdroj: | Quality and Reliability Engineering International, 36(8), 2610-2620. John Wiley and Sons Ltd |
| ISSN: | 0748-8017 |
| DOI: | 10.1002/qre.2658 |
| Popis: | When designing control charts the in-control parameters are unknown, so the control limits have to be estimated using a Phase I reference sample. To evaluate the in-control performance of control charts in the monitoring phase (Phase II), two performance indicators are most commonly used: the average run length (ARL) or the false alarm rate (FAR). However, these quantities will vary across practitioners due to the use of different reference samples in Phase I. This variation is small only for very large amounts of Phase I data, even when the actual distribution of the data is known. In practice, we do not know the distribution of the data, and it has to be estimated, along with its parameters. This means that we have to deal with model error when parametric models are used and stochastic error because we have to estimate the parameters. With these issues in mind, choices have to be made in order to control the performance of control charts. In this paper, we discuss some results with respect to the in-control guaranteed conditional performance of control charts with estimated parameters for parametric and nonparametric methods. We focus on Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) control charts for monitoring the mean when parameters are estimated. |
| Databáze: | OpenAIRE |
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