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Nelson rules
Decision rules for interpreting control-chart data
Decision rules for interpreting control-chart data
Nelson rules are a method in process control of determining whether some measured variable is out of control (unpredictable versus consistent). Rules for detecting "out-of-control" or non-random conditions were first postulated by Walter A. Shewhart in the 1920s. The Nelson rules were first published in the October 1984 issue of the Journal of Quality Technology in an article by Lloyd S. Nelson.
The rules are applied to a control chart on which the magnitude of some variable is plotted against time. The rules are based on the mean value and the standard deviation of the samples.
| Rule | Description | Chart Example | Problem Indicated | |||
|---|---|---|---|---|---|---|
The above eight rules apply to a chart of a variable value.
A second chart, the moving range chart, can also be used but only with rules 1, 2, 3 and 4. Such a chart plots a graph of the maximum value - minimum value of N adjacent points against the time sample of the range.
An example moving range: if N = 3 and values are 1, 3, 5, 3, 3, 2, 4, 5 then the sets of adjacent points are (1,3,5) (3,5,3) (5,3,3) (3,3,2) (3,2,4) (2,4,5) resulting in moving range values of (5-1) (5-3) (5-3) (3-2) (4-2) (5-2) = 4, 2, 2, 1, 2, 3.
Applying these rules indicates when a potential "out of control" situation has arisen. However, there will always be some false alerts and the more rules applied the more will occur. For some processes, it may be beneficial to omit one or more rules. Equally there may be some missing alerts where some specific "out of control" situation is not detected. Empirically, the detection accuracy is good.
References
References
- [http://www.itl.nist.gov/div898/handbook/pmc/section3/pmc32.htm Engineering Statistics Handbook 6.3.2], NIST/SEMATECH e-Handbook of Statistical Methods [[National Institute of Standards and Technology]], Dec 2006
- [[Lloyd S. Nelson]], "The Shewhart Control Chart—Tests for Special Causes". Journal of Quality Technology 16, no. 4 (October 1984), 238-239. https://doi.org/10.1080/00224065.1984.11978921
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