Example: Determine the Deviation of Label Positions

A manufacturing engineer carries out a study to determine the source of excessive variation in the positioning of labels on shampoo bottles (Hansen 1990). A labeling machine removes bottles from the line, attaches the labels, and returns the bottles to the line. There are six positions on the machine, and the engineer suspects that one or more of the position heads might be faulty.

A sample of 60 bottles, 10 per position, is run through the machine. For each bottle, the deviation of the label is measured in millimeters, and the machine position is recorded. In this example, you create a SAS data set named LabelDeviations, which contains the deviation measurements for the 60 bottles.

In SAS Studio, click and select New SAS Program.

Copy and paste this code into the Program tab.

data labeldeviations;
   input position @;
 
   do i=1 to 5;
      input deviation @;
      output;
   end;
   drop i;
   datalines;
1 -0.02386 -0.02853 -0.03001 -0.00428 -0.03623
1 -0.04222 -0.00144 -0.06466 0.00944 -0.00163
2 -0.02014 -0.02725 0.02268 -0.03323 0.03661
2 0.04378 0.05562 0.00977 0.05641 0.01816
3 -0.00728 0.02849 -0.04404 -0.02214 -0.01394
3 0.04855 0.03566 0.02345 0.01339 -0.00203
4 0.06694 0.10729 0.05974 0.06089 0.07551
4 0.03620 0.05614 0.08985 0.04175 0.05298
5 0.03677 0.00361 0.03736 0.01164 -0.00741
5 0.02495 -0.00803 0.03021 -0.00149 -0.04640
6 0.00493 -0.03839 -0.02037 -0.00487 -0.01202
6 0.00710 -0.03075 0.00167 -0.02845 -0.00697
run;

Click

to create the Work.LabelDeviations data set.

In the Tasks section, expand the Statistical Process Control folder, and then double-click Analysis of Means. The user interface for the Analysis of Means task opens.
On the Data tab, select the WORK.LABELDEVIATIONS data set.

Assign columns to these roles:

Role	Column Name
Response variable	deviation
Group variable	position

To run the task, click .

Here are the results:

Each point on the chart represents the average (mean) of the response measurements for a particular sample. The average for Position 1 is below the lower decision limit (LDL), and the average for Position 6 is slightly below the lower decision limit. The average for Position 4 exceeds the upper decision limit (UDL). The conclusion is that Positions 1, 4, and 6 are operating differently.