Note: See p Chart Examples in the SAS/QC Sample Library.
You can save the control limits for a p chart in a SAS data set; this enables you to apply the control limits to future data (see Reading Preestablished Control Limits) or modify the limits with a DATA step program.
The following statements read the number of nonconforming items per subgroup from the data set Circuits
(see Creating p Charts from Count Data) and save the control limits displayed in Figure 17.60 in a data set named Cirlim
:
proc shewhart data=Circuits; pchart Fail*Batch / subgroupn = 500 outlimits = Cirlim nochart ; run;
The OUTLIMITS= option names the data set containing the control limits, and the NOCHART option suppresses the display of the
chart. The data set Cirlim
is listed in Figure 17.65.
Figure 17.65: The Data Set Cirlim
Containing Control Limit Information
Control Limits for the Proportion of Failing Circuits |
_VAR_ | _SUBGRP_ | _TYPE_ | _LIMITN_ | _ALPHA_ | _SIGMAS_ | _LCLP_ | _P_ | _UCLP_ |
---|---|---|---|---|---|---|---|---|
Fail | Batch | ESTIMATE | 500 | .005040334 | 3 | .000930786 | 0.019467 | 0.038003 |
The data set Cirlim
contains one observation with the limits for process Fail
. The variables _LCLP_
and _UCLP_
contain the lower and upper control limits, and the variable _P_
contains the central line. The value of _LIMITN_
is the nominal sample size associated with the control limits, and the value of _SIGMAS_
is the multiple of associated with the control limits. The variables _VAR_
and _SUBGRP_
are bookkeeping variables that save the process and subgroup-variable. The variable _TYPE_
is a bookkeeping variable that indicates whether the value of _P_
is an estimate or standard value.
For more information, see OUTLIMITS= Data Set.
You can create an output data set containing both control limits and summary statistics with the OUTTABLE= option, as illustrated by the following statements:
proc shewhart data=Circuits; pchart Fail*Batch / subgroupn = 500 outtable = Cirtable nochart ; run;
The data set Cirtable
is listed in Figure 17.66.
Figure 17.66: The Data Set Cirtable
Subgroup Proportions and Control Limit Information |
_VAR_ | Batch | _SIGMAS_ | _LIMITN_ | _SUBN_ | _LCLP_ | _SUBP_ | _P_ | _UCLP_ | _EXLIM_ |
---|---|---|---|---|---|---|---|---|---|
Fail | 1 | 3 | 500 | 500 | .000930786 | 0.010 | 0.019467 | 0.038003 | |
Fail | 2 | 3 | 500 | 500 | .000930786 | 0.012 | 0.019467 | 0.038003 | |
Fail | 3 | 3 | 500 | 500 | .000930786 | 0.022 | 0.019467 | 0.038003 | |
Fail | 4 | 3 | 500 | 500 | .000930786 | 0.012 | 0.019467 | 0.038003 | |
Fail | 5 | 3 | 500 | 500 | .000930786 | 0.008 | 0.019467 | 0.038003 | |
Fail | 6 | 3 | 500 | 500 | .000930786 | 0.018 | 0.019467 | 0.038003 | |
Fail | 7 | 3 | 500 | 500 | .000930786 | 0.034 | 0.019467 | 0.038003 | |
Fail | 8 | 3 | 500 | 500 | .000930786 | 0.020 | 0.019467 | 0.038003 | |
Fail | 9 | 3 | 500 | 500 | .000930786 | 0.024 | 0.019467 | 0.038003 | |
Fail | 10 | 3 | 500 | 500 | .000930786 | 0.018 | 0.019467 | 0.038003 | |
Fail | 11 | 3 | 500 | 500 | .000930786 | 0.016 | 0.019467 | 0.038003 | |
Fail | 12 | 3 | 500 | 500 | .000930786 | 0.014 | 0.019467 | 0.038003 | |
Fail | 13 | 3 | 500 | 500 | .000930786 | 0.014 | 0.019467 | 0.038003 | |
Fail | 14 | 3 | 500 | 500 | .000930786 | 0.030 | 0.019467 | 0.038003 | |
Fail | 15 | 3 | 500 | 500 | .000930786 | 0.016 | 0.019467 | 0.038003 | |
Fail | 16 | 3 | 500 | 500 | .000930786 | 0.036 | 0.019467 | 0.038003 | |
Fail | 17 | 3 | 500 | 500 | .000930786 | 0.024 | 0.019467 | 0.038003 | |
Fail | 18 | 3 | 500 | 500 | .000930786 | 0.032 | 0.019467 | 0.038003 | |
Fail | 19 | 3 | 500 | 500 | .000930786 | 0.008 | 0.019467 | 0.038003 | |
Fail | 20 | 3 | 500 | 500 | .000930786 | 0.014 | 0.019467 | 0.038003 | |
Fail | 21 | 3 | 500 | 500 | .000930786 | 0.034 | 0.019467 | 0.038003 | |
Fail | 22 | 3 | 500 | 500 | .000930786 | 0.024 | 0.019467 | 0.038003 | |
Fail | 23 | 3 | 500 | 500 | .000930786 | 0.016 | 0.019467 | 0.038003 | |
Fail | 24 | 3 | 500 | 500 | .000930786 | 0.014 | 0.019467 | 0.038003 | |
Fail | 25 | 3 | 500 | 500 | .000930786 | 0.030 | 0.019467 | 0.038003 | |
Fail | 26 | 3 | 500 | 500 | .000930786 | 0.012 | 0.019467 | 0.038003 | |
Fail | 27 | 3 | 500 | 500 | .000930786 | 0.016 | 0.019467 | 0.038003 | |
Fail | 28 | 3 | 500 | 500 | .000930786 | 0.024 | 0.019467 | 0.038003 | |
Fail | 29 | 3 | 500 | 500 | .000930786 | 0.014 | 0.019467 | 0.038003 | |
Fail | 30 | 3 | 500 | 500 | .000930786 | 0.018 | 0.019467 | 0.038003 |
This data set contains one observation for each subgroup sample. The variables _SUBP_
and _SUBN_
contain the subgroup proportions of nonconforming items and subgroup sample sizes. The variables _LCLP_
and _UCLP_
contain the lower and upper control limits, and the variable _P_
contains the central line. The variables _VAR_
and Batch
contain the process name and values of the subgroup-variable, respectively. For more information, see OUTTABLE= Data Set.
An OUTTABLE= data set can be read later as a TABLE= data set. For example, the following statements read the information
in Cirtable
and display a p chart (not shown here) identical to the chart in Figure 17.60:
title 'p Chart for the Proportion of Failing Circuits'; proc shewhart table=Cirtable; pchart Fail*Batch; run;
Because the SHEWHART procedure simply displays the information in a TABLE= data set, you can use TABLE= data sets to create specialized control charts (see Specialized Control Charts: SHEWHART Procedure). For more information, see TABLE= Data Set.