Control charts are a great tool for monitoring your processes over time. This way, you can easily see variation. You can use control charts to determine if your process is under statistical control, the level of variation native to your process, and the nature of the variation (common cause or special cause).
When Do You Use Control Charts?
Generally, a control chart is used in the control phase of a DMAIC project to help lock in your gains and automate an alarm system that lets you know if the process is failing. However, if a process has existing data, you could use the same tools and techniques to prove the level (or lack) of control in the current state system. And, of course, the findings from a control chart analysis could be a launching point for improvement initiatives.
A control chart is an extension of a run chart. The control chart includes everything a run chart does but adds upper control limits and lower control limits at a distance of 3 Standard Deviations away from the process mean. This shows the process capability and helps you monitor a process to see if it is within acceptable parameters or not.
There are multiple kinds of control charts. You need to choose the right one based on the kinds of data sets you are mapping and other conditions. The kind of chart you use will affect the calculations of control limits you place in the chart.
Practical Thoughts Around Control Charts
A colleague once labeled the Upper & Lower control limits for a process he was responsible for as the “Time to update the resume lines” because if the process got out of control, he might be out of a job!
Use a control chart to tell the difference between common cause and special cause variation in a new process, or use it to determine how much common cause variation exists.
Control Chart Tips
- Specification lines should NEVER be part of a control chart.
- You should gather data for a control chart in the order of production.
- The ease of data collection is not a major concern.
- Collecting data related to a critical product or process parameter is more important.
- Never gather data from inspection records because it is too late–the cause for a point out of control, shift, or trend is lost because it happened hours earlier.
- Put at least six points in the range of a control chart to ensure adequate discrimination.
- We need six points (strata, units of measure) under the upper control limit of the range in order to have sufficient measurement discrimination. This is due to rounding. Too much rounding causes a loss of information about dispersion in a sample.
- A control chart can be used to identify the following causes
- A point outside control limits
- NOT anything to do with specification limits.
What Kind of a Control Chart to Use?
Control Chart vs. a Run Chart
A run chart can reveal shifts and trends but not points out of control. It does not have control limits; therefore, it cannot detect out-of-control conditions. You can turn a run chart into a control chart by adding upper and lower control limits.
Control limits are the voice of the process (different from specification limits, which are the voice of the customer.) They show what the process is doing and act as a guide for what it should be doing. Control limits also show that a process event or measurement is likely to fall within that limit.
Control Limits are Calculated by:
- Estimating the standard deviation, σ, of the sample data
- Multiplying that number by three
- Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL
Mathematically, the function of control limits looks like:
A Control Chart Indicates a Process is Out of Control When:
The following point to out-of-control conditions on a control chart:
- Six consecutive points, increasing or decreasing.
- Fourteen consecutive points alternating up and down.
- One or more points outside the control limits.
Control Charts: Usage & Terms
Trend: Seven points in a row in either an upward or downward direction.
Shift: Seven points in a row either above or below the center line
Extreme shift: Seven points in a row that are beyond the control limits, not a trend
Trend: Seven points in a row in either an upward or downward direction
Drift: A process is expected to drift, for no particular reason, about 1.5 standard deviations over the long run.
Control Chart Videos
How to Create Control Charts Using MiniTab
Other Notes About Control Charts
- Also, see Rational Sub Grouping.
ASQ Six Sigma Black Belt Control Chart Questions
Question: The purpose of using control charts is to
(A) Determine if the process is performing within specifications.
(B) Evaluate process performance over time.
(C) Determine how to recreate the process.
(D) Detect the causes of non-conformities.
Question: For a process, X BAR BAR = 35.0 and σ = 5.0. If the subgroup size is n=5, what is the value for the upper control limit for the process?
ASQ Six Sigma Green Belt Control Chart Questions
Which of the following control charts is used to monitor Discrete Data?
- I & mR
- X Bar
- X Bar – R