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Graphical Enhancements |
See SHWTREN in the SAS/QC Sample Library |
Time trends due to tool wear, environmental changes, and
other gradual process changes are sometimes observed in
charts. The presence of a systematic trend
makes it difficult to interpret the chart because the
control limits are designed to indicate expected
variation strictly due to common causes.
You can use the REG procedure (or other modeling procedure)
in conjunction with the
SHEWHART procedure to determine whether a process with
a time trend is in control. With the REG
procedure, you can model the trend and save the fitted
subgroup means and the residual
subgroup means
in
an output data set. Then, using this data as input to the
SHEWHART procedure, you can create a trend chart, which
displays a trend plot of the fitted subgroup
means together with an
chart for the residual
subgroup means, thus removing the time-dependent component
of the data from its random component. Having accounted
for the time trend, you can decide whether the process is
in control by examining the
chart.
The following example illustrates the steps used to create a trend chart for a SAS data set named TOOLWEAR that contains diameter measurements for 20 subgroup samples each consisting of eight parts:
data toolwear; input hour @; do i=1 to 8; input diameter @; output; end; label hour = 'Hour' diameter = 'Mean Diameter in mm'; datalines; 1 10.04 9.94 9.95 9.81 10.08 10.03 10.12 10.02 2 10.20 9.97 10.04 10.12 10.10 10.16 10.14 10.13 3 10.06 10.07 10.25 10.18 10.13 10.12 10.14 10.21 4 10.16 10.14 10.24 10.26 10.18 10.16 10.10 10.00 5 9.96 10.43 10.11 10.27 10.03 10.14 10.27 10.06 6 10.22 10.23 10.24 10.23 10.20 10.28 10.33 10.17 7 10.27 10.38 10.25 10.40 10.33 10.13 10.20 10.18 8 10.25 10.20 10.29 10.43 10.32 10.31 10.20 10.32 9 10.25 10.19 10.37 10.18 10.32 10.24 10.25 10.34 10 10.37 10.52 10.29 10.31 10.51 10.32 10.31 10.16 11 10.35 10.32 10.46 10.51 10.37 10.12 10.39 10.21 12 10.33 10.33 10.19 10.28 10.24 10.36 10.29 10.27 13 10.17 10.24 10.18 10.23 10.31 10.34 10.33 10.38 14 10.36 10.46 10.54 10.48 10.54 10.46 10.37 10.18 15 10.30 10.42 10.36 10.47 10.35 10.45 10.46 10.40 16 10.60 10.19 10.34 10.32 10.34 10.35 10.38 10.31 17 10.40 10.36 10.32 10.41 10.48 10.48 10.22 10.39 18 10.45 10.45 10.34 10.45 10.42 10.35 10.39 10.16 19 10.34 10.33 10.45 10.47 10.40 10.27 10.30 10.63 20 10.26 10.38 10.42 10.31 10.57 10.42 10.41 10.38 ;
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