Design of Experiment (DOE)
Design of Experiments (DOE) is an optimal
method for planning scientific experimentation.
The use of DOE ensures maximum information
return for minimum investment in time and resources.
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Design of Experiments is the most efficient
approach for organizing experimental work.
DOE selects a
diverse and representative set of experiments in which all
factors are independent
of each other despite being varied simultaneously. The
result is a causal predictive model showing the importance
of all factors and their interactions.
These models can be summarized as informative contour
plots highlighting the optimum combination of factor
DOE is used for three primary objectives:
Screening Which factors are most influential and over what range?
Optimization How can we find the optimum settings taking into account
conflicting demands of different responses?
Robustness testing Once the optimum is found, can we guarantee robustness
close to that point or do we need to change specifications
to achieve robustness?