Chapter Contents
Previous
Next
|
Chapter Contents |
Previous |
Next |
| XRCHART Statement |
| See SHWXR1 in the SAS/QC Sample Library |
You can save the control limits
for 
and R charts 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 measurements from the
data set WAFERS (see
"Creating Charts for Means and Ranges from Raw Data" )
and save the control limits displayed in
Figure 43.2 in WAFERLIM:
title 'Control Limits for Wafer Diameters';
proc shewhart data=wafers;
xrchart diamtr*batch / outlimits = waferlim
nochart;
run;
The OUTLIMITS= option names the data set containing
the control limits, and the NOCHART option suppresses the display
of the charts.
The data set WAFERLIM is listed in Figure 43.6.
The data set WAFERLIM contains one observation
with the limits for process DIAMTR. The variables
_LCLX_ and _UCLX_ contain the lower
and upper control limits for the chart.
The variables _LCLR_ and _UCLR_ contain
the lower and upper control limits for the R chart.
The variable _MEAN_ contains the central line for the chart,
and the variable _R_ contains the central line for the R chart.
The value of _MEAN_ is an estimate of the process mean, and the
value of
_STDDEV_ is an estimate of the process standard deviation 
.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 values of _MEAN_ and _STDDEV_ are estimates
or standard values.
You can save process capability
indices in an OUTLIMITS= data set if you provide
specification limits with the LSL= and USL= options. This is
illustrated by the following statements:
title 'Control Limits and Capability Indices';
proc shewhart data=wafers;
xrchart diamtr*batch / outlimits = wafrlim2
usl = 35.03
lsl = 34.97
nochart;
run;
The data set WAFRLIM2 is listed in Figure 43.7.
|
The variables _CP_, _CPL_, _CPU_, and _CPK_ contain the process capability indices. It is reasonable to compute capability indices, since Figure 43.2 indicates that the wafer process is in statistical control. However, it is recommended that you also check for normality of the data. You can use the CAPABILITY procedure for this purpose.
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:
title 'Summary Statistics and Control Limit Information';
proc shewhart data=wafers;
xrchart diamtr*batch / outtable=wtable
nochart;
run;
The data set WTABLE is listed in Figure 43.8.
|
This data set contains one observation for each subgroup
sample. The variables _SUBX_, _SUBR_, and _SUBN_ contain
the subgroup means, subgroup ranges, and subgroup sample sizes.
The variables _LCLX_ and _UCLX_ contain the lower and upper control
limits for the chart. The variables _LCLR_ and _UCLR_
contain the lower and upper control limits for the R chart. The
variable _MEAN_ contains the central line of the chart, and
the variable _R_ contains the central line of the R chart.
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
WTABLE and display and R charts
identical to those in Figure 43.2:
title 'Mean and Range Charts for Diameters';
proc shewhart table=wtable;
xrchart diamtr*batch;
run;
Because the SHEWHART procedure simply displays the information read from a TABLE= data set, you can use TABLE= data sets to create specialized control charts (see Chapter 49, "Specialized Control Charts").
For more information, see "TABLE= Data Set" .
|
Chapter Contents |
Previous |
Next |
 Top |
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.