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What is it?

An np-chart is an attributes control chart used with data collected in subgroups that are the same size. Np-charts show how the process, measured by the number of nonconforming items it produces, changes over time. The process attribute (or characteristic) is always described in a yes/no, pass/fail, go/no go form. For example, the number of incomplete accident reports in a constant daily sample of five would be plotted on an np-chart. Np-charts are used to determine if the process is stable and predictable, as well as to monitor the effects of process improvement theories. Np-charts can be created using software programs like SQCpack.

What does it look like?

The np-chart shows the number of nonconforming units in subgroups of set sizes.

np control chart

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When is it used?

Use np-charts when you can answer yes to these questions:

  1. Do you need to assess system stability?

  2. Is the data the number of nonconforming items per subgroup?

  3. Are the subgroups the same size?

  4. Are there only two outcomes to any given check?

  5. Is the time order of subgroups preserved?

Getting the most

Collect as many subgroups as possible before calculating control limits. With smaller amounts of data, the np-chart may not represent variability of the entire system. The more subgroups you use in control limit calculations, the more reliable the analysis will be. Typically, 20 to 25 subgroups will be used in control limit calculations.

Np-charts have several applications. When you begin improving a system, use them to assess the system’s stability .

After the stability has been assessed, determine if you need to stratify the data. You may find entirely different results between shifts, among workers, among different machines, among lots of materials, etc. To see if variability on the np-chart is caused by these factors, collect and enter data in a way that lets you stratify by time, location, symptom, operator, and lots.

You can also use np-charts to analyze the results of process improvements. Here you would consider how the process is running and compare it to how it ran in the past. Are there fewer nonconforming units?

Finally, use np-charts for standardization. This means you should continue collecting and analyzing data throughout the process operation. If you made changes to the system and stopped collecting data, you would have only perception and opinion to tell you whether the changes actually improved the system. Without a control chart, there is no way to know if the process has changed or to identify sources of process variability.