eldo_user

Setting Up An Analysis
Design of Experiments Analysis
0**** SENSPARAM INFORMATION TEMPERATURE = 27.000 DEG C
0************************************************************************
YVAL(I(R2),5N) NOM: 5.2297E-05
*| Absolute Relative Parameter Parameter Parameter
*| Sensitivity Sensitivity (%/%) Nominal Value Variation Name
*| -9.4162E-07 -1.0803E-01 6.00000e+00 3.000e+00% X2.C
*| -1.2688E-06 -7.2781E-02 3.00000e+00 1.000e-01% X2.D
*| -3.3851E-06 -6.4729E-02 1.00000e+00 1.000e-01% X3.X1.D
*| -3.3851E-06 -6.4729E-02 1.00000e+00 1.000e-01% X3.X2.D
*| -3.5221E-07 -4.0408E-02 6.00000e+00 1.000e-01% X1.D
Related Topics
Statistical and Sensitivity Related Analyses
Design of Experiments Analysis
Design of Experiments is concerned with the standard techniques of factor screening, location
and dispersion analysis, and response surface methodologies in circuit design. In this context, a
general situation is considered where an observable output (extracted measure in Eldo) depends
on a set of parameters and the effects (main effects and interactions) of parameters (factors) on
the output are explored using the techniques of Design of Experiments.
Eldo contains the basic tools to perform a factor screening experiment with the .DEX command.
Because the main issue in studying statistical design problems lies in a large number of circuit
parameters involved, the primary purpose of a variable screening experiment is to select or
screen out the few important main effects from the many less important ones. Once a small
number of important factors is identified, subsequent statistical design problems can be solved
more efficiently and require fewer runs.
In this context, a factor is a circuit parameter that is studied in the experiment. To study the
effect of a factor on one or several user-defined responses, two or more values of the factor are
used. These values are referred to as levels or settings. A combination of factor levels is called a
run and will be associated to a specific simulation run in Eldo.
In an experiment, one or more variables (or factors) are deliberately changed to observe the
effect the changes have on one or more response variables. The DEX techniques are efficient
procedures so that the data obtained can be analyzed to yield valid and objective conclusions.
This efficiency is founded on some key properties of orthogonal arrays, which offer a
systematic way of testing. The benefits include: a uniform distributed coverage of the test
domain, all pair-wise combinations of test set created, and arrive at complex combinations of all
the variables.
Tip
See “.DEX” in the Eldo Reference Manual.
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Eldo® User's Manual, 15.3