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Box-Behnken

Box-Behnken

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Box-Behnken

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Box-Behnken designs are used to generate higher order response surfaces using fewer required runs than a normal factorial.  Box-Behnken designs place points on the midpoints of the edges of the cubical design region, as well as points at the center.

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Box-Behnken designs and CCF central composite designs can be visualized as near compliments of each other. They both essentially suppress selected runs from a full factorial matrix in an attempt to maintain the higher order surface definition. For example, for three three-level variables, the full factorial run size is 27. The central composite design drops all of the middle edge nodes, resulting in only 15 runs. The Box-Behnken design is nearly the opposite in that it uses the twelve middle edge nodes and the center node to fit a 2nd order equation. A central composite design plus a Box-Behnken design becomes a full factorial with extra samples taken at the center.

 

Usability Characteristics

Box-Behnken is generally used for fitting a second-order response surface.
A Box-Behnken DOE is only defined when all of the variables have three levels.
A Box-Behnken DOE should not be used when accurate predictions at the extremes are important.
Any data in the inclusion matrix is combined with the run data for post-processing. Any run matrix point which is already part of the inclusion data will not be rerun.

 

Settings

In the Specifications step, you can change the following settings of Box-Behnken from the Settings tab.

Parameter

Default

Range

Description

Design

AutoSelect

AutoSelect, bbdgn13, bbdgn25, bbdgn41, bbdgn49, bbdgn57, None

AutoSelect will pick the lowest number of runs sufficient to study effects.

bbdgn stands for Box Behnken design.

Number of runs

(npt)

Dependant upon design selected.

13-57

Number of designs to be evaluated.

Use Inclusion Matrix

false

true or false

Concatenation without duplication between the inclusion and the generated run matrix.