Np-chart

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	$n{\bar {p}}={\frac {\sum _{i=1}^{m}\sum _{j=1}^{n}{\begin{cases}1&{\mbox{if }}x_{ij}{\mbox{ defective}}\\0&{\mbox{otherwise}}\end{cases}}}{m}}$ $n{\bar p}={\frac {\sum _{{i=1}}^{m}\sum _{{j=1}}^{n}{\begin{cases}1&{\mbox{if }}x_{{ij}}{\mbox{ defective}}\\0&{\mbox{otherwise}}\end{cases}}}{m}}$
Control limits	$n{\bar {p}}\pm 3{\sqrt {n{\bar {p}}(1-{\bar {p}})}}$ $n{\bar p}\pm 3{\sqrt {n{\bar p}(1-{\bar p})}}$
Plotted statistic	$n{\bar {p}}_{i}=\sum _{j=1}^{n}{\begin{cases}1&{\mbox{if }}x_{ij}{\mbox{ defective}}\\0&{\mbox{otherwise}}\end{cases}}$ $n{\bar p}_{i}=\sum _{{j=1}}^{n}{\begin{cases}1&{\mbox{if }}x_{{ij}}{\mbox{ defective}}\\0&{\mbox{otherwise}}\end{cases}}$

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.

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

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