Today, we’ll learn how to make and use a control chart from the 7 QC Tools.
[Intro Video]
Hi, this is Mike Negami, Lean Sigma Black Belt.
Control Charts are often used in the Improvement Phase and the Control Phase in DMAIC, but
it is not used much in the service operation improvement since there is a need to collect
data on a regular basis.
However, the concept of monitoring operational data and taking preventive actions is fundamental
in Kaizen activities, so we’ll learn the Control Chart today.
I made a Control Chart template.
Please try it by clicking the link in this video's description as usual.
Before going into the template explanation, I have a little announcement: I’ve been making
templates in English and Japanese.
This time I added a Spanish version.
There is the link in this video’s description to go to the English ‘Free Download’ page,
where you can go to the Spanish and Japanese ‘Free Download’ pages.
This is the template’s sheet.
There are 7 types of Control charts, depending on what kind of data you use.
This template is the most commonly used XbarR Control Chart.
First, prepare your measured data on Excel.
In this example, this has one set of 5 operational times in a row for 30 days vertically in time
series.
After opening the file, on the template file, double-click here, then follow each message
and click ‘Yes’ or ‘No’ depending on your situation.
Here, Excel is asking where your data is.
Select your data in a maximum of 5 columns with your mouse and, click ‘OK’.
This is the result.
Two charts appeared.
This column shows each set of 5’s averages.
Those averages are plotted in yellow in the above chart.
In the chart, the upper and lower lines are control limit lines.
In short, if your plots go out of the lines, there would be an abnormality, in other words,
a ‘Special Cause’ in your process.
Here it is.
Next, this column shows the differences between each maximum value and minimum value of each
set of 5 data.
We call it ‘Range R’.
Those Range Rs are plotted in gray in the R Control Chart below.
You can see variations in your data from the chart.
Returning to the first worksheet of the template, there is the ‘Interpretation and Action
Plan’ session.
Let’s read it.
“1) Create this control chart.
When ‘Special Causes’, which will be explained next, are shown in your control chart, identify
a root cause in your process and take preventive actions.”
“2) A ‘Special Cause’ is a signal that some abnormality in the process may have occurred.
In the Control Chart, they are represented when the following symptoms appear.”
“a) When plot(s) are beyond the upper or lower control limit line.”
We’ve already learned this.
“b) Even within the control limit lines, when there are 7 or more consecutive plots
above or below the average line.”
They look like this...
“c) Even within the control limit lines, when there were 7 or more consecutive plots
trending up or down.”
They look like this…
In order to remember these 4 ‘Special Causes’ easily, we call them the ‘Rule Of Seven’.
Since there are more definitions of ‘Special Cause’ in other companies and industries,
it’s a good idea to add applicable ones to your company’s practice.
You can use this Control Chart effectively in the Check stage of the PDCA Cycle.
Even in service industries, you can use it when you collect data on a regular basis.
Even if not, it’s still a good idea to use it for a limited time.
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