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Control charts (SPC)

Paste process measurements in production order to see whether the process is in statistical control, which points indicate a special cause and which sigma to use for capability.

Pre-sizing and estimating tool: results do not replace design, calculations or reports signed by a licensed professional, nor verification against the applicable codes and standards.

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With several values per line, each line is a subgroup. With a single column, values are grouped in order by the size above. For I-MR, all values are used in order.

Specification (for Cpk)

In the same unit as the measurements. Leave USL ≤ LSL to skip Cpk.

—Points signaling a special cause
—

Average, individuals or fraction defective chart

Center line, 3σ limits and 1σ and 2σ bands. Red points trigger a rule.

Tap the chart to see the values.

Dispersion chart (R, S or MR)

Range, standard deviation or moving range of each subgroup, with control limits.

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Signals found

Each flagged point and the rules triggered. Find the cause before recomputing limits without those points.

Next step

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The report gathers this page's inputs, results, equations, assumptions and references, with fields for project, engineer and revision. In the print dialog, choose Save as PDF.

Method, assumptions and references

Equations used

X̄-R: UCL/LCL = X̿ ± A₂ R̄; R: UCL = D₄ R̄, LCL = D₃ R̄; σ = R̄ ÷ d₂
X̄-S: UCL/LCL = X̿ ± A₃ S̄; S: UCL = B₄ S̄, LCL = B₃ S̄; σ = S̄ ÷ c₄
I-MR: UCL/LCL = X̄ ± 2.66 MR̄; MR: UCL = 3.267 MR̄; σ = MR̄ ÷ 1.128
p: p̄ = Σd ÷ Σn; UCL/LCL = p̄ ± 3 √[p̄ (1 − p̄) ÷ nᵢ] (LCL ≥ 0)
Rules on z = (point − center line) ÷ σ of the point; Cpk = min(USL − X̿, X̿ − LSL) ÷ 3σ

Assumptions and limits

  • Phase I limits computed from the data itself; for monitoring (phase II), freeze limits from a stable period. Rational subgroups of constant size, 2 to 25.
  • The rules assume an approximately normal distribution and independent points. Autocorrelated data (temperature, level) trigger false signals.
  • Constants A₂, A₃, B₃, B₄, D₃, D₄, d₂ and c₄ tabulated for n from 2 to 25, checked by numerical integration of the normal range distribution.

Standards and technical documents

  • ISO 7870-2:2023: Control charts — Part 2: Shewhart control charts
  • ISO 7870-1:2019: Control charts — Part 1: General guidelines
  • AIAG. Statistical Process Control (SPC) Reference Manual, 2nd ed., 2005
  • Western Electric Co. Statistical Quality Control Handbook, 1956
  • Nelson, L. S. The Shewhart control chart — tests for special causes. Journal of Quality Technology, 16(4), 237–239, 1984
  • Montgomery, D. C. Introduction to Statistical Quality Control, 8th ed. Wiley, 2019

U.S. regulations

  • NIST Handbook 133: Checking the Net Contents of Packaged Goods (statistical lot acceptance)
  • 21 CFR Part 820 (QMSR, incorporating ISO 13485:2016): statistical techniques for process monitoring of medical devices

Frequently asked questions

Which control chart should I use?

For measurements in subgroups of 2 to 10, X̄-R; above 10, X̄-S. With one reading at a time (batches, lab tests), I-MR. For items counted as good or bad, a p chart.

How are X̄-R limits computed?

UCL = X̿ + A₂ R̄ and LCL = X̿ − A₂ R̄. With subgroups of 5, A₂ = 0.577; if X̿ = 0.5000 in and R̄ = 0.0035 in, limits are 0.4980 and 0.5020 in.

Is a control limit the same as a specification?

No. Control limits come from the process and show its natural variation. Specifications come from the customer. A process can be in control and out of spec.

What do I do when a point falls outside?

Record what happened, investigate the special cause and fix it. Only then recompute limits without the explained points.