The SPC Procedure

Constructing Charts for Proportion Nonconforming (p Charts)

You produce control charts for proportion nonconforming by using the PCHART statement.

The following notation is used in this section:

p

Expected proportion of nonconforming items that the process produces

Proportion of nonconforming items in the ith subgroup

Number of nonconforming items in the ith subgroup

Number of items in the ith subgroup

Average proportion of nonconforming items taken across subgroups:

N

Number of subgroups

Subgroup Summary Statistics

Each point on a p chart represents the observed proportion () of nonconforming items in a subgroup. For example, in Figure 20.7 the second subgroup contains 16 items, of which 2 are nonconforming. The summary statistic for the second subgroup is .

Figure 20.7: Proportions versus Counts

Proportions versus Counts


Note that an chart displays the number (count) of nonconforming items . You can use the NPCHART statement to create charts; for more information, see the section Constructing Charts for Number Nonconforming (np Charts).

Central Line

By default, the central line on a p chart indicates an estimate of p that is computed as . If you specify a known value () for p, the central line indicates the value of .

Control Limits

The control limits are computed as a specified multiple (k) of the standard error of above and below the central line. The default limits are computed using k = 3 (these are referred to as limits).

The lower and upper control limits, LCL and UCL, respectively, are computed as

You can specify parameters for the limits as follows:

  • Specify k by using the SIGMAS= option or the variable _SIGMAS_ in a LIMITS= data table.

  • Specify a constant nominal sample size for the control limits by using the LIMITN= option or the variable _LIMITN_ in a LIMITS= data table.

  • Specify by using the variable _P_ in a LIMITS= data table.

Last updated: December 21, 2018