A P-chart is a type of control chart that outlines attributes. It can be used with datasets from subgroups that vary in size. A p-chart showcases a proportion of items that are nonconforming instead of the actual count. This is because the size of sub-samples can sometimes vary. This type of control chart highlights changes in a process over time. The attributes or characteristics of a process can be described as:
- Yes or no
- Pass or fail
- Go or no go
For example, a bank can use a P-chart to find the percentage of incomplete loan request forms that are received weekly.
R charts evaluate how processes vary based on samples that have been taken at specific times. The timeline can be shifts, hours, days, weeks, or even months. When measuring samples at these times, the researchers usually come up with sub-groups that can be used to measure the process's standard deviation. It is this standard deviation that produces a control limit for each subgroup's range. This is the initial stage and the process is often in control. However, you should identify the assignable cause if during the initial stage the points cannot be controlled. You should also remove the subgroups from the estimation.
How to interpret a control chart
As you already know, a control chart is an effective tool for monitoring the performance of a process. However, this tool will only be useful if you know how to interpret it. Through a control chart, you will get to know whether the process is under control or if there’s a problem. A process that is under statistical control will have most of the points closer to the control limit and the average. None of the points will be far from the control limits. Points that fall below the lower control limit and above the upper control limit should be permanently removed from the process.
Statistical process control
Statistical process control is a method used to have a process under control. There are several statistical process control techniques that you can use to check the behavior of a process, find problems associated with the internal system, and come up with formidable solutions to identified problems. Statistical process control can be used in the same manner as statistical quality control. One of the widely used statistical process control tools is the control chart. It is often used by analysts to monitor unusual events within a process.