Any nonrandom pattern

This is the most complex test for stability . If the system is in control , one could imagine tilting the chart on one end and letting all the points slip down to form a normal curve . Roughly half the points would fall above and half below the centerline. Dividing the distance between the centerline and the control limits into three equal divisions up and three down, one could expect to find about two thirds of the total points in the middle two regions, and no repeatable patterns in the data.

Patterns in data are not random, and are, therefore, cause for investigation. To apply these tests, look for patterns in the plot. The following are examples of typical patterns:

>> Too close to the average
>> Too far from the average
>> Cycles
>> Trends
>> Clusters
>> Sawtooth
>> 2 of 3 points beyond 2 sigma
>> 4 of 5 points beyond 1 sigma