A control chart carries two kinds of evidence. A single point beyond a three-sigma limit is the obvious one. Something has almost certainly changed. But a process that has shifted often signals first through the pattern of points that are still within the limits. A set of supplementary rules exists to read those patterns.
The rules work by splitting each half of the chart, between the centre line and each control limit, into three bands one standard deviation wide: zone C nearest the centre, zone B beyond it, and zone A just inside the three-sigma limit. A process in control scatters points across these zones in a predictable way: most in C, few in A, and roughly even numbers either side of the centre. When the observed pattern departs from that expectation, the process has probably moved, even though no single point has escaped.
The signals fall into a few families. A run (a long stretch of consecutive points all on one side of the centre line) says the process mean has moved to a new level. A trend (several points climbing or falling in sequence) says the process is drifting, as with tool wear or a degrading reagent. A drift too slow for the rules to catch is the case for a CUSUM or EWMA chart alongside this one.
Points clustered in zone A near the limits indicate increased variability or a mixture of two processes. Points packed too tightly around zone C suggest the opposite: stratification, or control limits that no longer reflect the true spread. An oscillation (points alternating regularly above and below the centre) hints at a systematic effect such as alternating operators or shifts.
Three widely used rule sets encode these patterns, and they overlap heavily rather than compete. The WECO rules are the classic set: one point beyond zone A; two of three consecutive points in zone A or beyond, on the same side; four of five in zone B or beyond, on the same side; eight in a row on one side of the centre.
The Nelson rules extend them with explicit trend and oscillation tests. The Montgomery rules are a compact, widely taught selection. Pick one set and apply it consistently. Stacking every rule from every set together inflates false alarms without adding real sensitivity.
Every rule you add raises sensitivity and, with it, the false-alarm rate. A chart running many rules at once will signal on a stable process more often than the nominal “1 in 370” of the three-sigma limit alone suggests. A team that sees its chart alarm on a stable process soon stops trusting it. Choose the smallest set that catches the failure modes your process actually has. Treat every genuine signal as a prompt to find the assignable cause. A signal with no investigation behind it is wasted. Where signals recur, Pareto analysis ranks the causes so effort goes where most of the loss is.
Download the Xbar-R detection-rules example (.xlsx) — copper plating with Montgomery rules and annotated assignable causes, ready to open in the Analyse-it trial.
The example workbook is downloading.
It opens in Excel on its own — the data and the finished results are both in it. Analyse-it is what lets you change the analysis and re-run it, try the same study on your own data, or work through it to see how the software handles it.
Every feature from all five editions for 15 days, with no sign-up and no licence key.
Watching only for points beyond the limits. The runs and trends inside the limits are the early warning. Waiting for an escape throws that lead time away.
Applying every rule at once. More rules mean more false alarms. Choose one coherent set and hold to it.
Signalling without investigating. A flagged point is the start of a search for an assignable cause, not the end. Log what you found.
Leaving stale limits in place. After a deliberate, understood process change, recompute the limits for the new phase. Old limits will flag the new normal endlessly.
Analyse-it applies the rules to any control chart and labels what it finds, inside Excel:
Every feature from all five editions for 15 days, with no sign-up and no licence key. Detection rules come with control charts in the Quality Control & Improvement and Ultimate editions, from US$ 290 a year. Validated against published reference datasets and thousands of internal test cases. See which control chart do you need for choosing the chart itself.