A c-chart is a type of control chart used to monitor the total number of nonconformities when measuring subgroups at regular intervals from a process.
Each point on the chart represents the total number of nonconformities in a subgroup.
The center line is the average number of nonconformities. If unspecified, the process average number of nonconformities per unit is the total number of nonconformities divided by the sum of subgroup sizes. Note that the center line varies when the subgroup sizes are unequal.
The control limits are either:
- A multiple (k) of sigma above and below the center line. Default k=3.
- Probability limits, defined as the probability (alpha) of a point exceeding the limits. Default alpha=0.27%.
A Poisson distribution is assumed. That is, the probability of observing a nonconformity in the inspection unit should be small, but a large number of nonconformities should be theoretically possible, and the size of an inspection unit should also be constant over time. When k-sigma limits are used the normal approximation to the Poisson distribution is assumed adequate which usually requires the average number of nonconformities to be at least 5.
A c-chart is useful when the number of units in each subgroup is constant as interpretation is easier than a u-chart. For data with different subgroup sizes, the center line and control limits both vary making interpretation difficult. In this case, you should use a u-chart which has a constant center line but varying control limits.