Experiments in Adams Insight
In Adams Insight, a designed experiment helps you gain understanding and improve a system or subsystem model. The components of the experiment include:
■System model - such as a multi-dynamic simulation
■Factors - inputs to the system
■Responses - outputs or performance metrics of the system under investigation
In the experimental design process, you systematically modify factors in your model and monitor responses after each Trial.
The design matrix does not directly specify factor values. Instead, it specifies indexes to the Levels for each factor. The indexes center on zero. This means that for a two-level factor, the only possible values are -1 and +1; for three-levels, -1, 0 and +1; for four-levels, -2, -1, +1, +2; and so on.
This convention implies that the levels (allowed values or range of values) are ordered from smallest to largest, and cover a range above and below a baseline value. For example, if a factor has three levels, you can think of the -1 index as the low value, the 0 index as the middle or baseline value, and the +1 index as the high value. In Adams Insight, we recommend that you list factor values from smallest to largest.