# Statistical process control with p-chart | Free template

Statistical process control with p-chart is a free template to control and ensure that the processes is producing in accordance with established standards. Statistical process control is a statistical method used to measure the performance of a process.

A process is in statistical control when the only source of variation comes from natural causes, that is, when the only variation is random. Statistical process control is important for quality because it is important to know when changes have occurred in a process so as to identify and address the root causes of the changes before a large number of defective units come out of the process. Statistical process control uses the concept of hypothesis testing, when the zero-hypothesis is rejected, the process is out of control.

A p-chart for statistical process control is a chart showing points of proportions for each sample being compared against a central line, an upper control limit and a lower control limit. A p-chart is used when attributes are measured that only can take two values, such as defective or not defective. When you set up a p-graph the number of defective units in each sample is calculated and the ratio of the number of defective units in relation to the number of observed units is also calculated.

A process is out of control when a proportion of a sample exceeds the upper control limit or when a proportion of a sample is below the lower control limit. The central line is calculated as the average of all sample proportions, the upper control limit (UCL) is calculated as the mean plus the standard deviation of all proportions times the z-value and the lower control limit (LCL) is calculated as the mean minus the standard deviation of all proportions times the z-value.

You can use this template to establish a statistical process control of proportions so as to check whether a process is in statistical control or out of statistical control. If a process is out of control you have to investigate and address the root causes of the problems in the process.

**Updated: **01/01/2015 | Created by All-templates.biz

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quality variation process probability