| Autor: |
Le Goh Kai, Teoh Wei Lin, Chong Zhi Lin, Ong Kai Lin, El-Ghandour Laila |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
ITM Web of Conferences, Vol 67, p 01002 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2271-2097 |
| DOI: |
10.1051/itmconf/20246701002 |
| Popis: |
The run sum (RS) X̄ chart is known as a simple and powerful tool for monitoring the mean of a process. Most developments of the RS X̄ chart assume that the underlying process comes from a normal distribution. However, in practice, many processes tend to follow a non-normal distribution. These non-normal processes affect the performances of control charts under the design of normal distribution. In this paper, we present a detailed analysis on the performances of the RS X̄ chart when the underlying data come from a gamma distribution. By using Monte Carlo simulation approach, the run-length properties, namely the average run length and the standard deviation of the run length will be computed. Particularly, the 4 and 7 regions RS X̄ charts under both distributions are considered. When the charts’ parameters specifically designed for the normal distribution are used to monitor the data from a gamma distribution, simulated results show that RS X̄ charts’ performances are significantly deteriorated. The RS X̄ chart has higher false alarm rates when the underlying distribution is gamma. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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