A quality manager once showed me two binders. One had 14 months of control charts, all beautifully complete. The other had charts that stopped after three weeks. Same process, same operators. The difference was that the first chart had limits computed from the right subgrouping, so the chart only alarmed when something real happened. The second alarmed constantly for reasons nobody could act on, and the team quietly stopped plotting.
That is the whole game: a chart that cries wolf gets abandoned, and an abandoned chart is worse than no chart because it manufactures the impression of control.
Pick the chart by how the data arrives, not by preference
| Data | Chart | When |
|---|---|---|
| One measurement per period (batch, shift, destructive test) | I-MR | You cannot form a subgroup |
| Small subgroup, n = 2–9 | Xbar-R | Most machining, filling, assembly cells |
| Larger subgroup, n ≥ 10 | Xbar-S | Where you can afford the data |
| Defectives (pass/fail per unit) | p / np | Inspect-and-sort processes |
| Defects per unit (count) | u / c | Rework counts, surface defects |
The mistake I see most: using an I-MR chart on data where five consecutive parts come from the same setup. Individual points then include both the common cause you want to detect and the natural within-setup variation, and the limits get wide enough to hide everything. Subgroup first, chart second.
Rational subgrouping is the actual decision
A subgroup must be homogeneous: every unit in it produced under the same set of conditions (same operator, same shift, same lot of material). Variation within the subgroup should be short-term common cause only. Variation between subgroups is what the chart is designed to detect.
Consequences people miss:
- Subgrouping across a shift change makes every shift change look like a special cause.
- Subgrouping across two cavities mixes a tooling effect into the noise.
- Taking 5 parts from one tray documents the tray, not the process.
Limits need enough baseline
Twenty-five subgroups, minimum, before you trust the limits. With fewer, and especially when the process was struggling, you have computed limits from variation that includes special causes — a process that then looks "in control" because the limits are inflated.
And the corollary that causes fights: do not recalculate limits to make a signal disappear. Recalculate when there is a documented, permanent process change (new tool, new material lot policy, new machine). Otherwise you are redrawing the target around the arrow after it landed.
Run rules: use few, use deliberately
Nelson rules 1–4, or Western Electric 1–4, catch most real shifts. Running all eight rules on a small chart produces alarms at a rate that destroys trust. Pick the rules that correspond to the failures this process actually has, and write down which ones you enabled — an auditor will ask.
A practical default set:
- One point beyond 3 sigma
- Nine points on one side of the centre line
- Six points steadily increasing or decreasing
- Two of three consecutive points beyond 2 sigma
Everything else is a judgement call, and a chart full of judgement calls gets ignored.
Reaction plan or it is decoration
Every chart needs a written one-line answer to "what do we do when it alarms?" — who is called, what is checked first, what is quarantined. If the answer is "we look at it at the weekly meeting", the chart is documentation, not control.
What made the binder chart work: an out-of-control signal had a named owner and a 30-minute response window. The chart was not more sophisticated. It was actionable.
Practical setup checklist
- [ ] Chart type matches the data type and subgrouping
- [ ] 25+ baseline subgroups, all special causes resolved or documented
- [ ] Limits marked with the date computed and the baseline period
- [ ] A named owner and a reaction plan
- [ ] Rule set written on the chart
- [ ] Xbar charts paired with an R or S chart — never Xbar alone
Trying it quickly
If you want to check a chart's limits against your own numbers before rebuilding a spreadsheet, SPC control chart calculator takes the subgroup data and returns Xbar/R limits, Cp/Cpk, and the run-rule violations. Runs in the browser, nothing uploaded.
Disclosure: I maintain 6SQ Tools, free browser calculators for SPC, MSA, DOE and reliability. The chart selection and run rules above follow the AIAG SPC manual and Nelson's original 1984 rule set.
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