Design of experiments and statistical process control using wavelets analysis

被引:22
|
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 du Lac, F-49000 Angers, France
关键词
Fault detection; Control charts; Design of experiments; Likelihood ratio; Wavelets transformations; Change time; Multiscale SPC; PRINCIPAL-COMPONENT ANALYSIS; FAULT-DETECTION; MULTIRESOLUTION ANALYSIS; ECONOMIC DESIGN; CLASSIFICATION; TRANSFORM; CORROSION;
D O I
10.1016/j.conengprac.2015.07.013
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, three new connections between Wavelets analysis and Statistical Quality Control are proposed. Firstly, we show that the Discrete Wavelet Transform, using Haar wavelet, is equivalent to the Xbar-R control scheme. Results concerning the distribution of wavelets coefficients, using others wavelets families, are presented, and then a new control chart, called DeWave, is proposed, in order to monitor the variability of the process. Secondly, the equivalence between the Likelihood Ratio and the Continuous Wavelet Transform, in terms of estimating the change time, is presented. Finally, we demonstrate that the Discrete Wavelet Transform is an equivalent representation of factorial Design Of Experiments. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:129 / 138
页数:10
相关论文
共 50 条
  • [1] Statistical process control for AR(1) or non-Gaussian processes using wavelets coefficients
    Cohen, A.
    Tiplica, T.
    Kobi, A.
    12TH EUROPEAN WORKSHOP ON ADVANCED CONTROL AND DIAGNOSIS (ACD 2015), 2015, 659
  • [2] Improved statistical process control using wavelets
    Top, S
    Bakshi, BR
    THIRD INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER-AIDED PROCESS OPERATIONS, 1998, 94 (320): : 332 - 337
  • [3] Multivariate statistical process control with dynamic external analysis
    Kano, M
    Maruta, H
    Tanaka, S
    Hasebe, S
    Hashimoto, I
    Ohno, H
    SICE 2002: PROCEEDINGS OF THE 41ST SICE ANNUAL CONFERENCE, VOLS 1-5, 2002, : 3081 - 3086
  • [4] Monitoring biological processes using univariate statistical process control
    Mansouri, Majdi
    Al-Khazraji, Ayman
    Yin Teh, Sin
    Harkat, Mohamed-Faouzi
    Nounou, Hazem
    Nounou, Mohamed
    CANADIAN JOURNAL OF CHEMICAL ENGINEERING, 2019, 97 (04): : 859 - 868
  • [5] On-Line Monitoring of a Continuous Pharmaceutical Process Using Parallel Factor Analysis and Unfolding Multivariate Statistical Process Control Representation
    Kompany-Zareh, M.
    JOURNAL OF THE IRANIAN CHEMICAL SOCIETY, 2011, 8 (01) : 209 - 222
  • [6] Process performance monitoring using multivariate statistical process control
    Martin, EB
    Morris, AJ
    Zhang, J
    IEE PROCEEDINGS-CONTROL THEORY AND APPLICATIONS, 1996, 143 (02): : 132 - 144
  • [7] Wavelets as a tool for systems analysis and control
    Abuhamdia, Tariq
    Taheri, Saied
    JOURNAL OF VIBRATION AND CONTROL, 2017, 23 (09) : 1377 - 1416
  • [8] Design multivariate statistical process control procedure in the case of Ethio cement
    Tegegne, Daniel Ashagrie
    Azene, Daniel Kitaw
    Atanaw, Eshetie Berhan
    INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 2022, 39 (07) : 1617 - 1636
  • [9] A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC)
    Gerard, Karine
    Grandhaye, Jean-Pierre
    Marchesi, Vincent
    Kafrouni, Hanna
    Husson, Francois
    Aletti, Pierre
    MEDICAL PHYSICS, 2009, 36 (04) : 1275 - 1285
  • [10] A new multivariate statistical process monitoring method using principal component analysis
    Kano, M
    Hasebe, S
    Hashimoto, I
    Ohno, H
    COMPUTERS & CHEMICAL ENGINEERING, 2001, 25 (7-8) : 1103 - 1113