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Activity Number:
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102
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Quality and Productivity
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| Abstract - #301935 |
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Title:
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Control Charts with Missing Observations
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Author(s):
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Sara R. Wilson*+ and Marion R. Reynolds, Jr.
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Companies:
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Virginia Polytechnic Institute and State University and Virginia Polytechnic Institute and State University
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Address:
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307 Hunt Club Road #6400 I, Blacksburg, VA, 24060,
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Keywords:
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Statistical process control ; Control charts ; EWMA ; MEWMA ; Average time to signal
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Abstract:
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Traditional control charts for process monitoring are based on taking samples from the process at regular time intervals. However, it is often possible in practice for observations, and even entire samples, to be missing. We investigate different ways to deal with missing observations in Exponentially Weighted Moving Average (EWMA) control charts by considering several approaches for adjusting the weights of the EWMA control statistic. The case in which individual observations are taken at each sampling point, as well as the case in which the sample size is greater than one are considered. Integral equation and Markov chain methods are developed to find and compare the statistical properties of these charts. The multivariate case in which information on some of the variables is missing is also examined using Multivariate EWMA (MEWMA) control charts.
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