A Cramer-von Mises test-based distribution-free control chart for joint monitoring of location and scale

被引:36
|
作者
Zhang, Jiujun [1 ]
Li, Erjie [1 ]
Li, Zhonghua [2 ,3 ]
机构
[1] Liaoning Univ, Dept Math, Shenyang 110036, Liaoning, Peoples R China
[2] Nankai Univ, Inst Stat, Tianjin 300071, Peoples R China
[3] Nankai Univ, LPMC, Tianjin 300071, Peoples R China
基金
中国国家自然科学基金;
关键词
Exponentially weighted moving average; Empirical cumulative distribution function; Cramer-von Mises test; Nonparametric; Statistical process control; CUSUM CONTROL CHARTS; NONPARAMETRIC CONTROL CHARTS; STATISTICAL PROCESS-CONTROL; EWMA CONTROL CHARTS; PHASE-II; UNIVARIATE PROCESSES; UNKNOWN LOCATION; OPTIMAL-DESIGN; RUN-LENGTH; PARAMETERS;
D O I
10.1016/j.cie.2017.06.027
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper proposes a new distribution-free control chart by integrating the powerful nonparametric two-sample Cramer-von Mises test and the exponentially weighted moving average control scheme to on-line monitoring. The proposed control chart can be used to monitor the location and the scale parameters of a univariate continuous distribution, simultaneously. The control limits based on Monte-Carlo simulation are provided in a table. The sensitivity analysis of effect of the number of reference samples on the control chart is studied in detail. Comparison results based on Monte-Carlo simulation show that the proposed chart is quite robust to non-normally distributed data, and moreover, it shows satisfactory performance in detecting various process shifts in terms of the average run length and standard deviation of run length. The application of our proposed chart is illustrated by a real data example for automobile engine piston rings. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:484 / 497
页数:14
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