The SHEWHART Procedure |
[See SHWMCHR in the SAS/QC Sample Library]You can save the control limits for a median 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 measurements from the data set Detergent (see Creating Charts for Medians from Raw Data) and save the control limits displayed in Figure 13.13.4 in a data set named Detlim:
proc shewhart data=Detergent; mchart Weight*Lot / outlimits=Detlim 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 Detlim is listed in Figure 13.13.9.
The data set Detlim contains one observation with the limits for the process Weight. The variables _LCLM_ and _UCLM_ contain the lower and upper control limits for the medians, and the variable _MEAN_ contains the central line. 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.
The variables _LCLR_, _R_, and _UCLR_ are not used to create median charts, but they are included so the data set Detlim can be used to create an chart; see MRCHART Statement and RCHART Statement If you specify the STDDEVIATIONS option in the MCHART statement, the variables _LCLS_, _S_, and _UCLS_ are included in the OUTLIMITS= data set. These variables can be used to create an chart; see SCHART Statement 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=Detergent; mchart Weight*Lot / outtable=Dtable nochart; run;
The data set Dtable is listed in Figure 13.13.10.
Summary Statistics and Control Limit Information |
_VAR_ | Lot | _SIGMAS_ | _LIMITN_ | _SUBN_ | _LCLM_ | _SUBMED_ | _MEAN_ | _UCLM_ | _STDDEV_ | _EXLIM_ |
---|---|---|---|---|---|---|---|---|---|---|
Weight | 1 | 3 | 5 | 5 | 20.7554 | 22.56 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 2 | 3 | 5 | 5 | 20.7554 | 23.54 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 3 | 3 | 5 | 5 | 20.7554 | 24.35 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 4 | 3 | 5 | 5 | 20.7554 | 25.52 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 5 | 3 | 5 | 5 | 20.7554 | 23.25 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 6 | 3 | 5 | 5 | 20.7554 | 23.01 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 7 | 3 | 5 | 5 | 20.7554 | 24.19 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 8 | 3 | 5 | 5 | 20.7554 | 26.27 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 9 | 3 | 5 | 5 | 20.7554 | 22.31 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 10 | 3 | 5 | 5 | 20.7554 | 22.66 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 11 | 3 | 5 | 5 | 20.7554 | 26.38 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 12 | 3 | 5 | 5 | 20.7554 | 23.01 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 13 | 3 | 5 | 5 | 20.7554 | 23.15 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 14 | 3 | 5 | 5 | 20.7554 | 24.73 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 15 | 3 | 5 | 5 | 20.7554 | 25.86 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 16 | 3 | 5 | 5 | 20.7554 | 23.99 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 17 | 3 | 5 | 5 | 20.7554 | 24.30 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 18 | 3 | 5 | 5 | 20.7554 | 24.88 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 19 | 3 | 5 | 5 | 20.7554 | 25.92 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 20 | 3 | 5 | 5 | 20.7554 | 25.63 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 21 | 3 | 5 | 5 | 20.7554 | 25.17 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 22 | 3 | 5 | 5 | 20.7554 | 26.72 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 23 | 3 | 5 | 5 | 20.7554 | 23.67 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 24 | 3 | 5 | 5 | 20.7554 | 24.92 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 25 | 3 | 5 | 5 | 20.7554 | 24.51 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 26 | 3 | 5 | 5 | 20.7554 | 24.75 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 27 | 3 | 5 | 5 | 20.7554 | 25.10 | 24.4996 | 28.2439 | 2.33041 | |
Weight | 28 | 3 | 5 | 5 | 20.7554 | 25.64 | 24.4996 | 28.2439 | 2.33041 |
This data set contains one observation for each subgroup sample. The variables _SUBMED_ and _SUBN_ contain the subgroup medians and subgroup sample sizes. The variables _LCLM_ and _UCLM_ contain the lower and upper control limits, and the variable _MEAN_ contains the central line. The variables _VAR_ and Lot 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 Dtable and display a median chart (not shown here) identical to the chart in Figure 13.13.4:
title 'Median Chart for Detergent Box Weight'; proc shewhart table=Dtable; mchart Weight*Lot; 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). For more information, see TABLE= Data Set.
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