XRCHART Statement: SHEWHART Procedure

Note: See Mean and Range (X-Bar and R) Charts 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 17.105 in Waferlim:

proc shewhart data=Wafers;
   xrchart Diameter*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 17.109.

The data set Waferlim contains one observation with the limits for process Diameter. 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 names. 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:

proc shewhart data=Wafers;
   xrchart Diameter*Batch / outlimits = Waferlim2
                            usl       = 35.03
                            lsl       = 34.97
                            nochart;
run;

The data set Waferlim2 is listed in Figure 17.110.

The variables _CP_, _CPL_, _CPU_, and _CPK_ contain the process capability indices. It is reasonable to compute capability indices, since Figure 17.105 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:

proc shewhart data=Wafers;
   xrchart Diameter*Batch / outtable=Wafertab
                            nochart;
run;

The data set Wafertab is listed in Figure 17.111.

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 Wafertab and display and R charts identical to those in Figure 17.105:

title 'Mean and Range Charts for Diameters';
proc shewhart table=Wafertab;
   xrchart Diameter*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 Specialized Control Charts: SHEWHART Procedure).

For more information, see TABLE= Data Set.