Control chart for monitoring the coefficient of variation with an exponentially weighted moving average procedure
被引:27
|
作者:
Zhang, Jiujun
论文数: 0引用数: 0
h-index: 0
机构:
Liaoning Univ, Dept Math, Shenyang 110036, Peoples R China
Nankai Univ, Inst Stat, Tianjin 300071, Peoples R China
Nankai Univ, LPMC, Tianjin 300071, Peoples R ChinaLiaoning Univ, Dept Math, Shenyang 110036, Peoples R China
Zhang, Jiujun
[1
,2
,3
]
Li, Zhonghua
论文数: 0引用数: 0
h-index: 0
机构:
Nankai Univ, Inst Stat, Tianjin 300071, Peoples R China
Nankai Univ, LPMC, Tianjin 300071, Peoples R ChinaLiaoning Univ, Dept Math, Shenyang 110036, Peoples R China
Li, Zhonghua
[2
,3
]
Wang, Zhaojun
论文数: 0引用数: 0
h-index: 0
机构:
Nankai Univ, Inst Stat, Tianjin 300071, Peoples R China
Nankai Univ, LPMC, Tianjin 300071, Peoples R ChinaLiaoning Univ, Dept Math, Shenyang 110036, Peoples R China
Wang, Zhaojun
[2
,3
]
机构:
[1] Liaoning Univ, Dept Math, Shenyang 110036, Peoples R China
[2] Nankai Univ, Inst Stat, Tianjin 300071, Peoples R China
[3] Nankai Univ, LPMC, Tianjin 300071, Peoples R China
control charts;
coefficient of variation;
exponentially weighted moving average;
reflecting boundary;
statistical process control;
MULTIVARIATE COEFFICIENT;
UNIVARIATE PROCESSES;
CONTROL SCHEMES;
VARIANCE;
RUNS;
VARIABILITY;
STRENGTH;
VECTOR;
RULES;
CUSUM;
D O I:
10.1002/qre.2247
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
The coefficient of variation (CV) of a population is defined as the ratio of the population standard deviation to the population mean, which can be regarded as a measure of stability or uncertainty and can also indicate the relative dispersion of data to the population mean. This paper proposes a new exponentially weighted moving average chart for monitoring CV, which is constructed by truncating those negative normalized observations to 0 in the traditional exponentially weighted moving average CV statistics. The implementation and optimization procedures of the proposed chart are presented. The new chart is compared with some existing CV charts by means of average run length, and the comparison results show that the new chart outperforms other charts in most cases. Two examples illustrate the use of this chart on real data gathered from a metal sintering process and from a die casting hot chamber process.