by Oliver Yu
Readers of this blog know well the necessity of control charting for process/campaign monitoring.
So it ought not to be surprising that we have yet another blog post about control charting. If you're really serious about reducing process variability, control charting is the highest impact, lowest cost method for establishing a baseline and understanding your status-quo process.
Everything that falls inside of the upper and lower control limits is expected variability (i.e. "common"). Since it is expected - don't do anything with it. Resist management tampering and don't waste resources investigating that which is expected.
Any point that falls outside of the upper and lower control limits is unexpected variability (i.e. "special"). Save your resources to investigate these points: chances are, you'll find something.
What hasn't been discussed here is within-control-limit patterns that can be considered special-cause. For example, 7-in-a-row on the same side of the centerline is a special cause even if no point has exceeded the control limit. Here are 4 other rules detailed later in the pocketbook:
And even farther on in the book are pages telling you how to compute control charts:
In this age with fast computers and JMP, it isn't a good use of your engineers' time to go back that far to derive the control charts limits.
- How to make IR control charts
- Control charts for Bioprocesses
- Control limits vs 3 standard deviations