What is a P Chart?

The p-chart, sometimes called the proportion nonconforming control chart, wields potent stats for quality oversight and workflow surveillance.

P Chart Construction

Defect Data

To construct a p chart, collect defect data from inspections.

Sample Size

The p chart needs each sample size to calculate fractions.

Subgroup Size

Samples are grouped by inspection time, machine, operator, etc., consistently.

Sample Size

For p charts, the formulas are: UCL = p-bar + 3 * sqrt((p-bar * (1 – p-bar)) / n) LCL = p-bar – 3 * sqrt((p-bar * (1 – p-bar)) / n)

P Chart Analysis and Interpretation

There are some key things to look for:

P Chart Control Limits

P chart control limits detect process stability and control.

P Chart Patterns and Runs

Look for abnormal patterns within control limits, such as:

– 7 consecutive points above/below center line.

– 10 of 11 points on same side

– 14+ points alternating

P Chart Stability and Variation

Stable p charts have random points within control limits.

P Chart Interpretation Rules

General rules for interpreting a p chart:

- Point above UCL: higher-than-expected defect rate.

- Point below LCL: lower-than-expected defect rate.

- Run above/below centerline means higher/lower defect rate.

- Unstable process needs variation causes investigated and removed.

Comparing P Charts with Other Charts

P Chart vs NP Chart

NP chart: varying sample sizes; p chart: constant sample size.

P Chart vs C Chart

C chart: defects per unit; p chart: conforming/nonconforming units.

P Chart vs U Chart

U charts: multiple defects per unit; p charts: pass/fail.

P Chart vs X-bar R Charts

X-bar/R charts: variable data; p charts: proportion defective items.

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