Design of Experiments represents a family of techniques.
Experimental designs provide the ability to:
Investigate multiple process variables at the same time.
Identify which variables have significant effects on the process
Study the relationships between variables to identify interactions.
The DOE approach is selected depending on the objective of the
experimentation, the type of process, and the number of variables
that will be studied. Experimental strategies often start with
DOE techniques include:
Screening Experiments: A special extreme type of Fractional
Factorial. Often used at the start of an experimental sequence; few
experimental runs but yields important information about key
Fractional Factorials: Less runs (than Full Factorials) but less
information, too. Studies a predetermined fraction of a Full
Full Factorials: Generates lots of information but requires many
runs. Usually used to study variables at 2 or 3 levels (settings).
Response Surface Analysis (RSA): An optimizing design in which the
main independent variables are already known. Limited runs, highly
EVOP: An iterative optimizing design; experiments are run within the
existing range of process parameters. Relatively high number of
runs, selective information.