DESIGN OF EXPERIMENT (DOE)
DESIGN OF EXPERIMENT
Design of experiment (DOE) is a body of knowledge, based upon statistical and other scientific disciplines, for efficient and effective planning of experiments and for making sound inferences from experimental data.
In an experiment, we deliberately change one or more process variables (or factors) in order to observe the effect the changes have on one or more response variables. The (statistical) design of experiments (DOE) is an efficient procedure for planning experiments so that the data obtained can be analyzed to yield valid and objective conclusions.
Design of experiment (DOE) defines the:
1 Population to be studied,
2 Randomization Process
3 Administration of Treatments,
4 Sample size requirement
5 Method of statistical analysis
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Step 1: BASIC PRINCIPLES OF DESIGN OF EXPERIMENT
Following the Basic Principles of Design of Experiment (DOE) which include:
- Randomization
- Replication and
- Local Control
One can easily comprehend the Idea of DOE and easily implement it in product and process research.
Full tutorial available here: Introduction-to-design-of-experiment
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Step 2: Process Models of Design of Experiment (DOE)
Experimental data can be used to derive an empirical (approximation) model linking the outputs and inputs.
These empirical models contain first and second-order terms.
The most common empirical models fit- Linear form
Linear form:
Y= β0 + β1 X1 + β2 X2 + β12 X1 X2 + experimental error
Free access to complete tutorial: Introduction-to-design-of-experiment
