Artigo
Monitoring process mean and variability with one non-central chi-square chart
Fecha
2004-12-01Registro en:
Journal of Applied Statistics. Basingstoke: Carfax Publishing, v. 31, n. 10, p. 1171-1183, 2004.
0266-4763
10.1080/0266476042000285503
WOS:000225394000003
Autor
Univ New Brunswick
Universidade Estadual Paulista (Unesp)
Resumen
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.