I don’t believe in ghosts. Yet quality professionals chase them every day. Why? Because erroneous control limits tell them to. Control limits should be statistically based, 100-percent reliable, and reveal natural process variability. Hence, they should help to uncover unnatural events. Yet when I work with companies that are using SPC, I continue to encounter control limits that are not statistically based. In case it isn’t obvious, control charts are statistical tools and should therefore be based upon process data and statistical information. Doing so ensures that control limits can be trusted and that quality professionals aren’t wasting their energy by chasing erroneous, statistically insignificant events whereby an assignable cause is simply nonexistent.

My last column recounted a phone call wherein the caller misunderstands the role of control limits and control charts. This column highlights the first of three things that one should never allow when creating or calculating control limits. Those bimonthly callers I discussed last month usually believe that it’s bad when a plot point falls outside control limits. Therefore, they try to manipulate control limits to be something they weren’t designed to be.

 …