• SPC Facebook icon
  • SPC Twitter icon
  • SPC LinkedIn icon
  • SPC RSS Feed icon
|

Six Sigma Control Charts

published on November 28, 2011

In keeping with my last post on Six Sigma tools and how to use them, I thought this week we would discuss control charts. In Six Sigma, control charts are a staple, but like every tool it as its limitations.

What is a control chart?

Control Charts (sometimes called Shewhart charts) are used to determine whether a process is in control, if there aren’t any uncommon variations shown then the process is under control. Now to be clear a process will always have some type of variation, these variations are common variations. What control charts create are a visual illustration of uncommon variations.  These variations are important because they can pinpoint where the problems are in your process.

What are the advantages?

The advantage of this tool is the ability to display all the variations that occur during a process; it eliminates guess work in risk identification and is very useful in process improvement. Now on the other hand, the control chart shows all variations, some variations are erratic and cover a large scope. If you find your variations resemble this, the control chart is probably not the best tool.

When do you use a control chart?

A control chart is best utilized when you have a specific process to measure and you know the parameters and constraints of that process. If you have a vague idea and aren’t really sure how the process works, then control charts are not your ideal tool. If you know how a process begins, but have no idea how it plays out then you are more suited for a better method.

What does a control chart look like?

Schewart

Now this  is a synopsis for control charts and is by no means an in-depth explanation. What I hope this post does is create a basic understanding and a starting place for the use of control charts and how to interpret the data you will receive. There are many other factors to consider when using a control chart and you will need to be familiar with statistical limits and errors. For a more detailed explanation, please consult a belt.

published on November 28, 2011

|

Leave a Reply