A reader writes:
“I got this email from QI Macros for Excel, which I installed on my home computer a while ago. I find this story interesting as had never heard this:
users in the healthcare field are advised to wait until their process has 20 consecutive in-control points; at that point, they have a stable process and they fix the control limits at those levels. Fixing the control limits means that subsequent points don’t change the CL, UCL and LCL. If your process begins to shift, even slightly, you’ll see notification of that change.
I have not done this, though I do recalculate the CL, UCL and LCL
at the point that it shows a trend up or down that meets special cause variation rules.
I wonder what you think of the practice described here. I am ambivalent as I don’t believe in interpreting or changing limits when all points are “in control”, but I have seen what I call variation creep where the SPC chart shows gradual increasing variation that probably skews the average, particularly if the data is drifting in one particular direction (up or down). I do think that that the center line average does get pulled in a way that might obscure interpretable process change that would be visible has the CL been fixed before the new data points were added.”
My response:
It’s “better” to have 20 data points for creating limits… but Don Wheeler teaches that you can do it with as few as 4 that it’s OK statistically.
You don’t need 20 “consecutive in control points” to create limits. Wheeler advises it’s OK to include out-of-control data points in the initial calculations.
Jay is right to say you should “lock in” your average and your limits and not continually recalculate them. That said, if I were starting with just 4 data points, I would keep tweaking the calculation until I hit say 20 or 24 data points… then I’d lock it in. The limits are more valid statistically with more data points, but there are diminishing returns beyond 15 or 20.
Having 12 data points would be just fine.
Using 4 data points isn’t as great… but it’s better than not using a Process Behavior Chart.
I generally recalculate limits if there are 8+ consecutive data points on the “better” side of the average. If things have gotten worse, I think the Wheeler tip that basically says ‘focus on restoring and improving the system instead of recalculating the limits.”
Remember the purpose of the limits is to
- Predict future performance of a predictable system and
- Help us identify when the system has changed.