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Use variable-width control limits [6] Each observation plots against its own control limits as determined by the sample size-specific values, n i, of A 3, B 3, and B 4: Use control limits based on an average sample size [7] Control limits are fixed at the modal (or most common) sample size-specific value of A 3, B 3, and B 4
As with the ¯ and s and individuals control charts, the ¯ chart is only valid if the within-sample variability is constant. [4] Thus, the R chart is examined before the ¯ chart; if the R chart indicates the sample variability is in statistical control, then the ¯ chart is examined to determine if the sample mean is also in statistical control.
The p-chart only accommodates "pass"/"fail"-type inspection as determined by one or more go-no go gauges or tests, effectively applying the specifications to the data before they are plotted on the chart. Other types of control charts display the magnitude of the quality characteristic under study, making troubleshooting possible directly from ...
Individuals and moving range control chart; Originally proposed by: Walter A. Shewhart: Process observations; Rational subgroup size: n = 1: Measurement type: Average quality characteristic per unit: Quality characteristic type: Variables data: Underlying distribution: none: Performance; Size of shift to detect: ≥ 1.5σ: Process variation ...
In statistical quality control, the np-chart is a type of control chart used to monitor the number of nonconforming units in a sample. It is an adaptation of the p-chart and used in situations where personnel find it easier to interpret process performance in terms of concrete numbers of units rather than the somewhat more abstract proportion. [1]
Data representing each subgroup are taken to be of equal importance if suspected variation among them warrants stratified sampling. If subgroup variances differ significantly and the data needs to be stratified by variance, it is not possible to simultaneously make each subgroup sample size proportional to subgroup size within the total population.
In statistical quality control, an EWMA chart (or exponentially weighted moving average chart) is a type of control chart used to monitor either variables or attributes-type data using the monitored business or industrial process's entire history of output. [1]
The control limits for this chart type are ¯ ¯ where ¯ is the estimate of the long-term process mean established during control-chart setup. The observations u i = x i n i {\displaystyle u_{i}={\frac {x_{i}}{n_{i}}}} are plotted against these control limits, where x i is the number of nonconformities for the ith subgroup and n i is the ...