c-chart

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c-chart
Originally proposed by Walter A. Shewhart
Process observations
Rational subgroup size n > 1
Measurement type Number of nonconformances in a sample
Quality characteristic type Attributes data
Underlying distribution Poisson distribution
Performance
Size of shift to detect ≥ 1.5σ
Process variation chart
Not applicable
Process mean chart
C control chart.svg
Center line \bar c = \frac {\sum_{i=1}^m \sum_{j=1}^n \mbox{no. of defects for } x_{ij}}{m}
Control limits \bar c \pm 3\sqrt{\bar c}
Plotted statistic \bar c_i = \sum_{j=1}^n \mbox{no. of defects for } x_{ij}

In statistical quality control, the c-chart is a type of control chart used to monitor "count"-type data, typically total number of nonconformities per unit.[1] It is also occasionally used to monitor the total number of events occurring in a given unit of time.

The c-chart differs from the p-chart in that it accounts for the possibility of more than one nonconformity per inspection unit, and that (unlike the p-chart and u-chart) it requires a fixed sample size. The p-chart models "pass"/"fail"-type inspection only, while the c-chart (and u-chart) give the ability to distinguish between (for example) 2 items which fail inspection because of one fault each and the same two items failing inspection with 5 faults each; in the former case, the p-chart will show two non-conformant items, while the c-chart will show 10 faults.

Nonconformities may also be tracked by type or location which can prove helpful in tracking down assignable causes.

Examples of processes suitable for monitoring with a c-chart include:

The Poisson distribution is the basis for the chart and requires the following assumptions:[2]

  • The number of opportunities or potential locations for nonconformities is very large
  • The probability of nonconformity at any location is small and constant
  • The inspection procedure is same for each sample and is carried out consistently from sample to sample

The control limits for this chart type are \bar c \pm 3\sqrt{\bar c} where \bar c is the estimate of the long-term process mean established during control-chart setup.

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