What is Design of Experiments and
why use it?
Are you running experiments involving two or more
Do you have complex pieces of equipment requiring set-up by adjusting two or more factors?
Are you using Design of Experiments (DoE) for these tasks?
If the answer to the last question is NO, then you
are almost certainly wasting precious resources, and possibly not even
obtaining valid results.
DoE is the most efficient way possible to run
multi-factor experiments or set up complex equipment, can be easily learned by
any engineer or scientist and is the essential tool for designing and
optimizing complex products and processes.
How does DoE differ?
The majority of Engineers and Scientists working
today use the one-factor-at-a-time approach to experimentation. This means that
factor A is varied while factors B, C, D, …etc are held fixed at their nominal
values. Next factor B is varied while factors
A, C, D, …etc are held fixed at their nominal values. The problem with this
approach is that it does not allow you to identify interactions
between factors. This can lead to a choice of factor settings which are far from
optimal and a complete misunderstanding of your process or product.
DoE provides you with a means to build a more
complete picture of your process or product by allowing you to identify
situations where factors interact, helping ensure that you obtain a more
accurate model of the process or product. What’s more, the additional
information will be gained at a lower cost in resources than the traditional one-factor-at-a-time approach.
The Taguchi approach to
designing experiments has become popular in certain
industrial sectors (e.g. automotive). Taguchi's
experimental designs have some associated problems with
regard to efficiency, although Matrex does include a large
range of his design arrays (Orthogonal Arrays).