Design
of Experiments, or DOE, has been in practice since the early
1900's. Developed in England, R.A. Fisher led the initial
applications in the field of agriculture. Other contributors
to Designed Experiments have included Rao, Plackett, Burman,
Box, Taguchi, Barker, Derringer and many others. Until the
early 1980's, Designed Experiments were usually set up and
run by specialists within an organization. Today, with the
advent of readily available software, such as DOE
Wisdom, the non-statistical person can successfully
set up and analyze simple but powerful experiments.
A designed
experiment is a well-controlled family of tests. Each test
is run one or more times. For each controlled test, outputs,
also known as responses, are measured. From test to test controlled
changes will be made. Once the tests are completed, the data
can then be analyzed. As you will see with further understanding
of designed experiments, simple graphs can be of great value
in furthering your understanding of the results of the experiment.
As the data is analyzed, conclusions will be reached as to
the the best setting for the inputs, or factors. The final
step in a designed experiment is to actually try these settings
and see if they produce the predicted result based on the
analysis. If the results are close to the prediction, and
better than any baseline we might have, the experiment will
be declared a success.
The challenge
facing corporations is to cut design and development time
while producing low-cost quality products that are ready to
perform. Many organizations are being challenged to cut delivery
time in half or more.
Demanding
that people work harder is not the solution. Providing proper
tools aids people in working more efficiently and effectively.
Experimental Design is a premier tool in helping meet these
challenges. By understanding and applying Experimental Design
techniques, scientists, researchers, and engineers typically
obtain a 50% reduction in the time required to conduct tests.
This translates into enhanced understanding of technologies,
reduced design and development time, and decreased costs.
If you are looking for a little more background on design
of experiments, we have an example DOE, "creating the
perfect lego" that can be followed here:
Launsby
Consulting offers a variety of tools on design of experiments.
