When to Use an Attribute Chart

Only Attributes data can be applied to an Attributes control chart.

To illustrate the differences between various attribute charts, consider an example of the errors in an accounting process, where each month we process a certain number of transactions.

The Np-Chart monitors the number of times a condition occurs, relative to a constant sample size, when each sample can either have this condition, or not have this condition. For our example using this type of attribute chart, we would sample a set number of transactions each month from all the transactions that occurred, and from this sample count the number of transactions that had one or more errors. We would then track on the attribute control chart the number of transactions with errors per month.

The p-Chart monitors the percent of samples having the condition, relative to either a fixed or varying sample size, when each sample can either have this condition, or not have this condition. For our example using this type of attribute chart, we might choose to look at all the transactions in the month (since that would vary from month to month), or a set number of samples, whichever we prefer. From this sample, we would count the number of transactions that had one or more errors. We would then track on the attribute control chart the percent of transactions with errors per month.

The c-Chart monitors the number of times a condition occurs, relative to a constant sample size. In this case, a given sample can have more than one instance of the condition, in which case we count all the times it occurs in the sample. For our example using this type of attribute chart, we would sample a set number of transactions each month from all the transactions that occurred, and from this sample count the total number of errors in all the transactions. We would then track on the attribute control chart the number of errors in all the sampled transactions per month.

The u-Chart monitors the percent of samples having the condition, relative to either a fixed or varying sample size. In this case, a given sample can have more than one instance of the condition, in which case we count all the times it occurs in the sample. For our example using this type of attribute chart, we might choose to look at all the transactions in the month (since that would vary month to month), or a set number of samples, whichever we prefer. From this sample, we count the total number of errors in all the transactions. We would then track on the attribute control chart the number of errors per transactions per month.

Interpreting an Attribute Chart

Learn more about the SPC principles and tools for process improvement in Statistical Process Control Demystified (2011, McGraw-Hill) by Paul Keller, in his online SPC Concepts short course (only $39), or his online SPC certification course ($350) or online Green Belt certification course ($499).