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Process Improvement

5.3.

Choosing an experimental design

5.3.3.

How do you select an experimental design.

5.3.3.7.

Adding centerpoints

Center point, or `Control' Runs

Centerpoint

runs provide

a check for

both process

stability and

possible

curvature

As mentioned earlier in this section, we add centerpoint runs

interspersed among the experimental setting runs for two purposes:

To provide a measure of process stability and

inherent variability

To check for curvature.

Centerpoint

runs are not

randomized

Centerpoint runs should begin and end the experiment, and should be

dispersed as evenly as possible throughout the design matrix. The

centerpoint runs are not randomized! There would be no reason to

randomize them as they are there as guardians against process instability

and the best way to find instability is to sample the process on a regular

basis.

Rough rule

of thumb is

to add 3 to 5

center point

runs to your

design

With this in mind, we have to decide on how many centerpoint runs to

do. This is a tradeoff between the resources we have, the need for

enough runs to see if there is process instability, and the desire to get the

experiment over with as quickly as possible. As a rough guide, you

should generally add approximately 3 to 5 centerpoint runs to a full or

fractional factorial design.

5.3.3.7. Adding centerpoints

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