Control charts are a great tool to monitor your processes overtime. This way you can easily see variation. Control charts are a great tool that you can use to determine if your process is under statistical control, the level of variation inherent in the process, and point you in the direction of the nature of the variation (common cause or special cause).
When Do You Use Control Charts?
Generally a control part in a DMAIC project is used in the control phase to help lock in the gains that you made and automate an alarm system to let you know if the process is misbehaving. However, if a process has existing data, you could use the same tools and techniques to illustrate the level (or lack) of control in the current state system. And of course the findings from analysis on a control chart 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 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 depending upon 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 distinguish 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 included on 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 consideration.
- It is more important to collect data that relates to a critical product or process parameter.
- 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 6 points in the range of a control chart to ensure adequate discrimination.
- A control chart can be used to identify the following assignable 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 (A run chart 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 indicate 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 calculation of control limits looks like:
A Control Chart Indicates a Process is Out of Control When:
The following are indicators of out of control conditions on a control chart:
- Six consecutive points, increasing or decreasing.
- Fourteen consecutive points that alternate 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 a 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 nonconformities
Answer: (B) Control charts are used to evaluate the performance of a process overtime. It is irrelevant how the specifications are set. A control chart may tell you if non-onformaties are present, but it will not tell you what they are without root cause analysis.[/membership]
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?
Answer: (C) 41.71. UCL = mean + 3*σ / n^(1/2) = X BAR BAR + 3*5 / 5^0.5 = 35 + 15/2.2361 = 41.71[/membership]
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
I & MR charts and X Bar charts are for continuous data and When you have subgroups of size = 1. You use the ImR (XmR) chart only when logistical reasons prevent you from having larger subgroups or when there is no reasonable basis for rational subgroups.
Use X Bar R Control Charts when you have small amounts of constant, continuous data and when you can rationally collect measurements in subgroups of generally between two and 10 observations.[/membership]