charts assess whether the process center is in control. The tests for special causes detect points beyond the control limits and specific patterns in the data plotted on the chart.

·    When a point fails a test, Minitab reports it in the Session window and marks it on the R chart. A failed point indicates that there is a nonrandom pattern in the data that may be the result of special-cause variation. These points should be investigated.

·    When no points are displayed under the test results, no points failed the tests for special causes.

The R chart must be in control before you can interpret the chart. If the R chart is out of control, then the control limits for the chart will be inaccurate and may inappropriately signal an out-of-control condition. For the camshaft data, the R chart is in control, so it is appropriate to examine the chart.

For the camshaft data, six subgroups failed the following tests:

·    Subgroup 8 failed Test 1, which looks for points more than 3 s from the center line. Test 1 provides the strongest evidence that the process is out of control and detects shifts and drifts in the process average.

·    Subgroup 17 failed Test 5, which looks for two out of the three subgroups more than two s from, and on the same side of, the center line. Test 5 provides additional sensitivity for detecting smaller shifts in process average.

·    Subgroups 12, 13, 19, and 20 failed Test 6, which looks for four out of five subgroups more than one s from and on the same side of, the center line. Test 6 provides additional sensitivity for detecting smaller shifts in process average.

These test results indicate that the process average is unstable and the process is out of control, possibly due to the presence of special causes. The factors causing the variation should be identified and corrected.