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DOE Approach Basics |
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DOE Approach Basics |
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»Click here to display Table of Contents«
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DOE Approach Basics |
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DOE Approach Basics |
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Design of Experiments (DOE) can be defined as a test or a series of tests in which purposeful changes are made to the input variables of a process or system so that the reasons for changes in the output response can be identified and observed.
DOE Study Objectives
| • | To determine which factors are most influential on the output response. |
| • | To determine where to set the influential controlled input variables so that: |
| - | the output response is close to the desired nominal value. |
| - | variability in output response is small. |
| - | the effects of the uncontrolled variables are minimized. |
| • | To construct an approximate model that can be used as a surrogate model for the actual computationally intensive solver. |
If there is a fitting function (approximation, response surface) defined prior to a DOE, the DOE can be performed using the analysis solver directly or by using a fitting function (approximation, response surface).
A DOE approach can be copied into another (new) DOE approach. All settings are copied, but any files created (solver runs, results) are not copied.
A DOE approach can also be removed; upon removal of an approach, all files can be deleted from the study folder (prompts are provided).
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DOE study using the analysis solver directly |
DOE study using an approximation from the Fit Approach |
The steps to set up a DOE approach in HyperStudy are:
