np-chart
Originally proposed by	Walter A. Shewhart
Process observations
Rational subgroup size	n > 1
Measurement type	Number nonconforming per unit
Quality characteristic type	Attributes data
Underlying distribution	Binomial distribution
Performance
Size of shift to detect	≥ 1.5σ
Process variation chart
Not applicable
Process mean chart
Center line	${\displaystyle n{\bar {p))={\frac {\sum _{i=1}^{m}\sum _{j=1}^{n}{\begin{cases}1&{\mbox{if ))x_{ij}{\mbox{ defective))\\0&{\mbox{otherwise))\end{cases))}{m))}$
Control limits	${\displaystyle n{\bar {p))\pm 3{\sqrt {n{\bar {p))(1-{\bar {p)))))}$
Plotted statistic	${\displaystyle n{\bar {p))_{i}=\sum _{j=1}^{n}{\begin{cases}1&{\mbox{if ))x_{ij}{\mbox{ defective))\\0&{\mbox{otherwise))\end{cases))}$

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]

The np-chart differs from the p-chart in only the three following aspects:

1. The control limits are ${\displaystyle n{\bar {p))\pm 3{\sqrt {n{\bar {p))(1-{\bar {p)))))}$, where n is the sample size and ${\displaystyle {\bar {p))}$ is the estimate of the long-term process mean established during control-chart setup.
2. The number nonconforming (np), rather than the fraction nonconforming (p), is plotted against the control limits.
3. The sample size, ${\displaystyle n}$, is constant.