Normal process: in control with chance variation

In order for a process to be normal, it should be able to be:

1. Set at the mean

2. Will continue to randomly vary about the mean

*without any operator intervention!*
A process in control is in the ideal state 100% conforming and predictable

1. must remain stable over time

2. must operate in a stable and consistent manner

3. must be set at the proper level

4. the natural process spread must not exceed the product’s specified tolerance (capability)

A great example of a normal process is cutting the grass. You set the mower deck to a particular height. As is typical for a quality profession, one would measure each blade of grass after cutting, and you would find most near the mean height (height of the deck setting) – with some a little longer and some a little shorter. Most “natural” variations, such as operations influenced by humans or nature (environmental) that are not unilateral are normally distributed.

I am sure others can give deeper academic explanation, but this is a good overview, I think...

However, not all processes are normal – and treating them as such generates incorrect decisions. Precision machining is just such an example. It is non-normal, continuous uniform distribution – which means the central limit theory does not apply. For more information on this, see:

Statistical process control for precision machining