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DOE has a language
of its own.
-
In the world of designed experiments, the
terminology is different than most of us are
used to in business and industry.
-
It is important to know and understand the
language of DOE before delving into the
techniques.
Major DOE terms include:
- Factor
- Level
- Treatment
- Treatment Combination
- Response
- Experimental Run
- Effect
- Interaction
- Randomize
- Blocking
- Replicate
- Reflect
Factors
-
Factors are the independent variables of a
process.
-
Independent variables are the parameters or
aspects of the process that we can set or change
independently of the settings of another process
variable.
-
Factors can be related to people, equipment,
methods, materials, and the environment.
Level
Treatment
-
A treatment is a factor at a specified level.
-
Treatment Combination
-
A treatment combination is a set of factors
and their levels.
-
When conducting a DOE, processes are run with
factors set at a specified set of levels.
Response
-
The responses are the outputs of the process.
Process outputs are dependent variables.
Outputs, or responses, can be related to
quality, product performance, productivity, or
safety.
-
Responses are the results of all of the
actions of the independent variables, the
factors.
-
Most DOEs allow us to study several responses
at the same time.
Experimental Run
Effect
-
If we change the level of a factor and we see
a resulting change in the response, we can say
that this factor has had an effect on the
response.
-
The effect is a calculated value of how much
the response changes for a given change in the
factor levels.
Interaction
-
Sometimes factors do not behave the same when
they are looked at together as when they are
alone; this is called an interaction.
-
An interaction occurs when the levels of two
or more factors are changed and produce a
response that is different than the process
would produce with the factors changed to those
levels by themselves.
Randomization
-
When we run designed experiments, we will use
experimental templates to set them up and to
analyze them. We do not want to actually make
the experimental runs in the order shown by the
template; wherever possible, we want to
randomize the experimental runs.
-
Randomization of the run order is needed to
minimize the impact of those variables outside
of the experiment that we are not studying.
Blocking
-
Sometime we cannot totally randomize the
experimental runs. Typically this is because it
will be costly or will take a long time to
complete the experiment.
-
Blocking means to run all treatment
combinations at one level before running all
treatment combinations at the next level.
Experimental runs within blocks must be
randomized.
Replication
Reflection
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