Abstract Details
Activity Number:
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247
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Quality and Productivity Section
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Abstract #311639
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Title:
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Robust GLR Charts for Monitoring the Process Mean
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Author(s):
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Shuyu Chu*+ and Yiming Peng and Marion R. Reynolds
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Companies:
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Virginia Tech and Virginia Tech and Virginia Tech
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Keywords:
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generalized likelihood ratio ;
average time to signal ;
robust ;
monitoring ;
statistical process control ;
steady state
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Abstract:
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This paper considers the problem of obtaining robust GLR control charts for detecting changes in the process mean ?. The standard GLR control chart for monitoring ? has been shown to have a very good performance in detecting a wide range of shift sizes. However it is based on the assumption that the process distribution is normal, while the process distribution may not be normal in many real applications. It is shown that using this control chart can lead to very misleading conclusions when the process distribution is not normal. Several robust GLR control charts for ? are investigated, including a GLR chart with a restricted window and two transformed GLR charts. Guidance is given for selecting the design parameters and control limits of these robust GLR charts. The performance of these robust GLR charts is compared with two robust CUSUM charts, a CUSUM chart tuned to detect a relatively small shift size, and a CUSUM sign chart which is a nonparametric control chart based on the sign statistics.
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Authors who are presenting talks have a * after their name.
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