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An Improved R (Range) Control Chart for Monitoring the Process Variance
An R chart is often used to monitor shifts in the process variability. However, the range, $R_i, i = 1, 2, \dots$, statistics from a sampling distribution are highly skewed. Hence, the classical R chart based on the $\pm3\sigma$ control limits will not give an in‐control average run length of approx...
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Published in: | Quality and reliability engineering international 2005-02, Vol.21 (1), p.43-50 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | An R chart is often used to monitor shifts in the process variability. However, the range, $R_i, i = 1, 2, \dots$, statistics from a sampling distribution are highly skewed. Hence, the classical R chart based on the $\pm3\sigma$ control limits will not give an in‐control average run length of approximately 370, or equivalently a type I error, $\alpha = 0.0027$. In this paper, an approach is shown to obtain the control limits of an improved R chart based on a desired type I error from the density function of the Ri statistics. Copyright © 2004 John Wiley & Sons, Ltd. |
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ISSN: | 0748-8017 1099-1638 |
DOI: | 10.1002/qre.606 |