DOE is team oriented and a variety backgrounds such as design, manufacturing, statistics should be
involved when identifying factors and levels and
developing the matrix as this is the most skilled part. Moreover, as this tool is used to answer specific
questions, the team should have a clear understanding of the
difference between control and noise factors. In
order to draw the maximum amount of
information a full matrix is needed which contains all possible
combinations of factors and levels. If this requires too many
experimental runs to be practical, fractions of the
matrix can be taken dependent on which effects are of particular interest. The fewer the runs in the
experiment the less information is available.
By attending this workshop participants would be able to increase the performance measures and
results from the Design of Experiments processes
especially in analyzing the impact of introducing new
products and concurrently optimizing the process flow.

Design of experiments (DOE) provides a powerful means to achieve breakthrough improvements in product quality and process efficiency. This leads to increased market share, decreased costs, and big gains in profit. So why don’t more manufacturers use design of experiments (DOE)?