How to Calculate Process Capability in Minitab 18

Updated on June 1, 2020
Joshua Crowder profile image

Joshua has work experience in aerospace/aluminum manufacturing & distribution. He received his BBA in accounting from Kent State University.

The graph above is the output from a process capability analysis. This type of analysis determines how well a process stays within specification limits. The analysis itself is based on a sample that is taken from a working process.
The graph above is the output from a process capability analysis. This type of analysis determines how well a process stays within specification limits. The analysis itself is based on a sample that is taken from a working process.

What Is Capability Analysis?

A capability analysis is used to tell whether a process can produce output to meet customer requirements. The analysis focuses on one single process variable. In the case of the provided example in this tutorial, we will be looking at wire gauge size.

This type of analysis can be compared to an older analysis to evaluate whether an improvement effort made the process more capable of meeting customer requirements. The data used for an analysis should come from a relatively stable process and follow a normal or approximately normal distribution. Enough data should be used to ensure precision.

Sample data for this tutorial can be found here. If you don't have Minitab 18, you can find a free trial here.

Sample data provided in the download.
Sample data provided in the download.

Completing an Analysis With Minitab 18

The sample data set provided shows the measurements of a wire 4 times every 2 hours during an 8-hour shift for 8 days straight. There are 8 samples, and the sample size is 4. The wire measurement is supposed to be 1.50 +/- .05 per the customer requirement.

To create the analysis, go to Statistics > Quality Tools > Capability Analysis > Normal Distribution. We select normal distribution assuming our data follows a normal distribution in this example.

Selecting Normal Distribution from the menu.
Selecting Normal Distribution from the menu.

Set Parameters

Place your cursor in the single column box, then highlight C1 and click select. This will add the data that we are analyzing. Next, select subgroup and enter 1. Since the upper and lower tolerance limits are known, add them as well.

Click on the options button to add a title to the graph. Name the title “Process Capability Report for Wire Diameter” and click OK in that window, and OK in the process capability window.

Adding in the data that we're analyzing.
Adding in the data that we're analyzing.
Process capability output.
Process capability output.


The sample mean is very close to the center of our specification range but shows a slight shift toward the upper limit.

  • My result for Cp is .7. Since this result is less than one, we would consider the process unstable.
  • The Cpk is a more relied-upon variable and will be lower than Cp. The Cpk for this process is .61 and more than half of what it should be. If Cpk is under 1.33, it is advised that changes may need to be made to the process.

In this situation, I only used 34 samples and was not sure if the process was reliable. My next step will be to calculate Cp and Cpk with a larger number of samples and make sure the measuring instrument used to size to inspect the wire is not giving a false reading. As the process stabilizes, Cp and Cpk will give better readings as new results are compared to older studies.


Boyer, K. & Verma, R. (2010). Operations & supply chain management for the 21st century. Mason, OH: South-Western.

This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.

© 2018 Joshua Crowder


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