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| MRCHART Statement |
| See SHWMR1 in the SAS/QC Sample Library |
A consumer products
company weighs detergent boxes (in pounds)
to determine whether the fill process is in control.
The following statements create a SAS data set
named DETERGNT, which contains the weights for five boxes
in each of 28 lots.
A lot is considered a rational subgroup.
data detergnt;
input lot @;
do i=1 to 5;
input weight @;
output;
end;
drop i;
datalines;
1 17.39 26.93 19.34 22.56 24.49
2 23.63 23.57 23.54 20.56 22.17
3 24.35 24.58 23.79 26.20 21.55
4 25.52 28.02 28.44 25.07 23.39
5 23.25 21.76 29.80 23.09 23.70
6 23.01 22.67 24.70 20.02 26.35
7 23.86 24.19 24.61 26.05 24.18
8 26.00 26.82 28.03 26.27 25.85
9 21.58 22.31 25.03 20.86 26.94
10 22.64 21.05 22.66 29.26 25.02
11 26.38 27.50 23.91 26.80 22.53
12 23.01 23.71 25.26 20.21 22.38
13 23.15 23.53 22.98 21.62 26.99
14 26.83 23.14 24.73 24.57 28.09
15 26.15 26.13 20.57 25.86 24.70
16 25.81 23.22 23.99 23.91 27.57
17 25.53 22.87 25.22 24.30 20.29
18 24.88 24.15 25.29 29.02 24.46
19 22.32 25.96 29.54 25.92 23.44
20 25.63 26.83 20.95 24.80 27.25
21 21.68 21.11 26.07 25.17 27.63
22 26.72 27.05 24.90 30.08 25.22
23 31.58 22.41 23.67 23.47 24.90
24 28.06 23.44 24.92 24.64 27.42
25 21.10 22.34 24.96 26.50 24.51
26 23.80 24.03 24.75 24.82 27.21
27 25.10 26.09 27.21 24.28 22.45
28 25.53 22.79 26.26 25.85 25.64
;
A listing of DETERGNT is shown in Figure 36.1.
The data set DETERGNT is said to be in "strung-out" form, since each observation contains the lot number and weight of a single box. The first five observations contain the weights for the first lot, the second five observations contain the weights for the second lot, and so on. Because the variable LOT classifies the observations into rational subgroups, it is referred to as the subgroup-variable. The variable WEIGHT contains the weights and is referred to as the process variable (or process for short).
You can use median and range charts to determine whether the fill process is in control. The following statements create the charts shown in Figure 36.2:
title 'Median and Range Charts for Detergent Box Weight';
symbol v=dot c=rose;
proc shewhart data=detergnt;
mrchart weight*lot / cframe = vipb
cinfill = ywh
cconnect = rose
coutfill = salmon;
run;
This example illustrates the basic form of the MRCHART statement. After the keyword MRCHART, you specify the process to analyze (in this case, WEIGHT) followed by an asterisk and the subgroup-variable (LOT).
The input data set is specified with the DATA= option in the PROC SHEWHART statement.
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Each point on the median chart represents the median of the measurements for a particular lot. For instance, the weights for the first lot are 17.39, 19.34, 22.56, 24.49, and 26.93, and consequently, the median plotted for this lot is 22.56. Each point on the range chart represents the range of the measurements for a particular batch. For instance, the range plotted for the first lot is 26.93 - 17.39 = 9.54. Since all of the points lie within the control limits, you can conclude that the process is in statistical control.
By default, the control limits shown are
limits estimated from the data; the formulas for the
limits are given in Table 36.22.
You can also read control limits
from an input data set; see "Reading Preestablished Control Limits".
For computational details, see "Constructing Charts for Medians and Ranges". For more details on reading raw data, see "DATA= Data Set".
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Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.