At least 3 confirmation runs should be planned
 
 
 
 
 
 

Carefully duplicate the original environment
 
 
 
 
 

Checks for when confirmation runs give surprises
 
 
 
 
 
 

Even when the experimental goals are not met, something was learned that can be used in a follow on experiment 

The interpretation and conclusions from an experiment include a "best" setting to use to meet the goals of the experiment. Even if this "best" setting was included in the design, you should run it again as confirmation runs to make sure nothing has changed, and you get what you predicted you would get.

In an industrial setting, it is very desirable to have a stable process, therefore one should run more than one test at the "best" settings. A minimum of 3 runs should be conducted (allowing an estimate of variability at that setting).

If the time between actually running the experiment and conducting the confirmation runs is more than a few hours, the experimenter must be careful to ensure that nothing else has changed since the original data collection.

The confirmation runs should be conducted in an environment as similar as possible to the original experiment. For example, if the experiment was conducted in the afternoon, and the equipment has a warm-up effect, then the confirmation runs should be conducted in the afternoon after the equipment has warmed up. Other things that may change or affect the results of the confirmation runs are: person/operator on the equipment, temperature, humidity, machine parameters, raw materials, etc.

What do you do if you don't get the results you expected? If the confirmation runs don't produce the results you expected:

1) check to see that nothing has changed since the original data collection
2) verify that you have the correct settings for the confirmation runs 
3) re-visit the model to verify the "best" settings from the analysis
4) verify you had the correct predicted value for the confirmation runs.

Every experiment is a success in that you learn something from it. However, every experiment will not necessarily meet the goals established before experimentation. That is why it makes sense to plan to  experiment sequentially in order to meet the goals.