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Creating Standard Deviation Charts from Raw Data

A petroleum company uses a turbine to heat water into steam, which is then pumped into the ground to make oil more viscous and easier to extract. This heating process occurs 20 times daily, and the amount of power (in kilowatts) used to heat the water to the desired temperature is recorded. The following statements create a SAS data set named TURBINE, which contains the power output measurements for 20 days:

   data turbine;
      informat day date7.;
      format day date5.;
      input day @;
      do i=1 to 10;
         input kwatts @;
         output;
         end;
      drop i;
      datalines;
   04JUL94 3196 3507 4050 3215 3583 3617 3789 3180 3505 3454
   04JUL94 3417 3199 3613 3384 3475 3316 3556 3607 3364 3721
   05JUL94 3390 3562 3413 3193 3635 3179 3348 3199 3413 3562
   05JUL94 3428 3320 3745 3426 3849 3256 3841 3575 3752 3347
   .
   .
   .
   23JUL94 3421 3787 3454 3699 3307 3917 3292 3310 3283 3536
   23JUL94 3756 3145 3571 3331 3725 3605 3547 3421 3257 3574
   ;

A listing of TURBINE is shown in Figure 40.1.

The data set TURBINE is said to be in "strung-out" form, since each observation contains the day and power output for a single heating. The first 20 observations contain the power outputs for the first day, the second 20 observations contain the power outputs for the second day, and so on. Because the variable DAY classifies the observations into rational subgroups, it is referred to as the subgroup-variable. The variable KWATTS contains the power output measurements and is referred to as the process variable (or process for short).

You can use an s chart to determine whether the variability in the heating process is in control. The following statements create the s chart shown in Figure 40.2:

   title 'Chart for Standard Deviations of Power Output';
   symbol v=dot c=salmon;
   proc shewhart data=turbine;
      schart kwatts*day / cframe   = vligb
                          cinfill  = ywh
                          cconnect = salmon;
   run;

This example illustrates the basic form of the SCHART statement. After the keyword SCHART, you specify the process to analyze (in this case, KWATTS), followed by an asterisk and the subgroup-variable (DAY).

The input data set is specified with the DATA= option in the PROC SHEWHART statement.

Each point on the chart represents the standard deviation of the measurements for a particular day. For instance, the standard deviation plotted for the first day is

Since all of the subgroup standard deviations lie within the control limits, you can conclude that the variability of 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 40.21. You can also read control limits from an input data set; see "Reading Preestablished Control Limits" .

For computational details, see "Constructing Charts for Standard Deviations" . For more details on reading raw data, see "DATA= Data Set" .

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