Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks</title> <meta name="description" content="Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks"> <meta name="keywords" content="Multivariate quality control, Artificial Intelligence, Neural Networks, Computer Applications"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks"> <meta name="citation_author" content="Francisco Aparisi"> <meta name="citation_author" content="Jos茅 Sanz"> <meta name="citation_publication_date" content="2010/01/26"> <meta name="citation_journal_title" content="International Journal of Computer and Information Engineering"> <meta name="citation_volume" content="4"> <meta name="citation_issue" content="1"> <meta 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href="https://publications.waset.org/search?q=Francisco%20Aparisi">Francisco Aparisi</a>, <a href="https://publications.waset.org/search?q=Jos%C3%A9%20Sanz"> Jos茅 Sanz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages. The main problem is how to interpret the out-ofcontrol signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must be accepted that there is a shift in the vector, but no indication is given about the variables that have produced this shift. The MEWMA quality control chart is a very powerful scheme to detect small shifts in the mean vector. There are no previous specific works about the interpretation of the out-of-control signal of this chart. In this paper neural networks are designed to interpret the out-of-control signal of the MEWMA chart, and the percentage of correct classifications is studied for different cases.</p> <iframe src="https://publications.waset.org/8798.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Multivariate%20quality%20control" title="Multivariate quality control">Multivariate quality control</a>, <a href="https://publications.waset.org/search?q=Artificial%20Intelligence" title=" Artificial Intelligence"> Artificial Intelligence</a>, <a href="https://publications.waset.org/search?q=Neural%20Networks" title=" Neural Networks"> Neural Networks</a>, <a href="https://publications.waset.org/search?q=Computer%20Applications" title=" Computer Applications"> Computer Applications</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1071568" target="_blank">doi.org/10.5281/zenodo.1071568</a> </p> <a href="https://publications.waset.org/8798/interpreting-the-out-of-control-signals-of-multivariate-control-charts-employing-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8798/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8798/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8798/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8798/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8798/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8798/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8798/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8798/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8798/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8798/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8798.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2505</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Lowry, C.A., Woodall, W.H., Champ, C.W., and Rigdon, S.E. A multivariate exponentially weighted moving average control chart. Technometrics, 1992, 34 (1), 46-53. <br>[2] Prabhu, SS. And Runger, GC. Designing a multivariate EWMA control chart. Journal of Quality Technology, 1997, 29:8-15. <br>[3] Roberts, S. W. (1959). Control Chart Test Based on Geometrics Moving Averages. Technometrics, 1959, 1, pp. 239-250. <br>[4] Montgomery, D.C. Introduction to Statistical Quality Control .4rd. John Wiley. New York. 2001 <br>[5] Lowry CA. and, Montgomery, DC. A review of multivariate control charts. IIE Transactions, 1995; 27: 800-810. <br>[6] Blazek, L.W., Novic B .and Scott M.D. Displaying Multivariate Data Using Polyplots. Journal of Quality Technology, 1987, 19(2), 69-74. <br>[7] Subramanyan, N. and Houshmand, A.A. Simultaneous representation of multivariate and corresponding univariate charts using line graph. Quality Engineering, 1995, 4, 681-682. <br>[8] Fuchs, C. and Benjamin, Y. Multivariate profile charts for statistical process control. Technometrics, 1994, 36(2), 182-195. <br>[9] Iglewicz, B. and Hoaglin, D.C. Use of boxplots for process evaluation. Journal of Quality Technology, 1987, 19(4), 180-190. <br>[10] Atienza, O.O., Ching L.T. and Wah, B.A. Simultaneous monitoring of univariante and multivariate SPC information using boxplots. International Journal of Quality Science, 1988, 3(2). <br>[11] Doganaksoy, N., Faltin, F.W. and Tucker, W.T. Identification of-out-of control characteristics in a multivariate manufacturing environment. Communications in Statistics Theory and Methods, 1991, 20, 2775- 2790. <br>[12] Runger, G.C., Alt, F.B., and Montgomery, D.C. Contributors to a multivariate statistical process control chart signal. Communications in Statistics. Theory Methods, 1996, 25, 2203-2213. <br>[13] Mason, R. L., Tracy, N.D. and Young, J.C. Decomposition of T2 multivariate control chart interpretation. Journal of Quality Technology, 1995, 27(2), 99-108. <br>[14] Mason, R.L., Tracy, N.D. and Young, J.C. A practical approach for interpreting multivariate T2 control chart signals. Journal of Quality Technology, 1997, 29(4), 396-406. <br>[15] Aparisi, F., Avenda鈹溾枓o, G. and Sanz, J. Interpreting T2 Control Chart Signals: Effectiveness of MTY decomposition vs. a Neural Network, IIE Transactions, 2006, 38(8), 647-657. </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>

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Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks