Please use this identifier to cite or link to this item:
- Monitoring process mean and variability with one non-central chi-square chart
- Univ New Brunswick
- Universidade Estadual Paulista (UNESP)
- Traditionally, an (X) over bar -chart is used to control the process mean and an R-chart to control the process variance. However, these charts are not sensitive to small changes in process parameters. A good alternative to these charts is the exponentially weighted moving average (EWMA) control chart for controlling the process mean and variability, which is very effective in detecting small process disturbances. In this paper, we propose a single chart that is based on the non-central chi-square statistic, which is more effective than the joint (X) over bar and R charts in detecting assignable cause(s) that change the process mean and/or increase variability. It is also shown that the EWMA control chart based on a non-central chi-square statistic is more effective in detecting both increases and decreases in mean and/or variability.
- Journal of Applied Statistics. Basingstoke: Carfax Publishing, v. 31, n. 10, p. 1171-1183, 2004.
- Carfax Publishing
- monitoring process mean and variance
- (X)over-bar chart
- EWMA chart
- non-central chi-square chart
- Acesso restrito
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.