OWave control chart for monitoring the process mean

被引：3
|
作者：
Cohen, Achraf [1 ]
Tiplica, Teodor [1 ]
Kobi, Abdessamad [1 ]
机构：
[1] LUNAM, ISTIA Engn Sch, LARIS Syst Engn Res Lab, 62 Ave Notre Dame Lac, F-49000 Angers, France
来源：
CONTROL ENGINEERING PRACTICE | 2016年 / 54卷
关键词：
Statistical process control; Fault detection; Multi-scale analysis; Wavelets; Mean shifts; Probability distribution; PRINCIPAL-COMPONENT ANALYSIS; VARIABLE SAMPLING INTERVALS; STATISTICAL PROCESS-CONTROL; FAULT-DETECTION; WAVELETS; TRANSFORM; DIAGNOSIS; DESIGN; SIZES;
D O I：
10.1016/j.conengprac.2016.06.002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper a control chart for monitoring the process mean, called OWave (Orthogonal Wavelets), is proposed. The statistic that is plotted in the proposed control chart is based on weighted wavelets coefficients, which are provided through the Discrete Wavelets Transform using Daubechies db2 wavelets family. The statistical behavior of the wavelets coefficients when the mean shifts are occurring is presented, and the distribution of wavelets coefficients in the case of normality and independence assumptions is provided. The on-line algorithm of implementing the proposed method is also provided. The detection performance is based on simulation studies, and the comparison result shows that OWave control chart performs slightly better than Fixed Sample Size and Sampling Intervals control charts ((X) over bar, EWMA, CUSUM) in terms of Average Run Length. In addition, illustrative examples of the new control chart are presented, and an application to Tennessee Eastman Process is also proposed. (C) 2016 Elsevier Ltd. All rights reserved.
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页码：223 / 230
页数：8
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