SPC techniques for automated manufacturing

Many people erroneously believe that statistics are not needed when automated manufacturing processes are involved. Since we have measurements from every unit produced, they reason, sampling methods are inappropriate. We will simply correct the process when the characteristic is not on target.

This attitude reflects a fundamental misunderstanding of the relationship between a process and the output of a process. It also shows a lack of appreciation for the intrinsic variability of processes and of measurements. The fact is, even if there is a data record of every feature of every part produced, there is still only a sample of the output of the process. The process is future-oriented in time, while the record of measurements is past-oriented. Unless statistical control is attained, the data from past production cannot be used to predict the variability from the process in the future (refer to the definition of statistical control above.) And without statistical tools there is no sound basis for the belief that statistical control exists.

Another reason process control should be based on an understanding and correct use of statistical methods is the effect of making changes without this understanding. Consider, for example, the following process adjustment rule:

Measure the diameter of the gear shaft. If the diameter is above the nominal size, adjust the process to reduce the diameter. If the diameter is...