Configuring the Factors

You can select and configure the input parameters that you want to use as factors to study. The attributes that you can configure are determined by the DOE technique you selected.

  1. Double-click the DOE component icon .
    The DOE Component Editor appears.
  2. From the DOE Component Editor, click the Factors tab.
  3. Right-click in the table to access various options for working with factors.

    For more information, see Setting Table Options.

  4. Determine which parameters you want to define as factors to study by selecting the corresponding check boxes in the first column.

    Alternatively, you can click the button at the bottom of the tab to add all parameters. To clear all the parameters, click the button.

    If you select an array as a factor, a single quantity represents the array in the model and it will be expanded during execution to define a factor for each element in the array. You can override the attributes for each individual element by selecting them separately.

    To select aggregates, click and select the scalar members.

    Tip: You can also right-click on the aggregate, and select Expand all.

  5. Change any of the default values, which are provided for all attributes for a selected factor.

    Depending on the technique, a change in one of the columns might automatically update any other columns that are related.

    Although each technique defines the appropriate set of attributes for a factor, the following attributes are common among many of the techniques:

    • # Levels. The number of levels at which you want to study the factors. A change to this attribute automatically readjusts the levels for this factor.

    • Levels. A space-separated list of the levels at which to study the factor. The related attributes are updated once you click in a different cell.

    • Lower/Upper. The lower/upper levels for the factor. A change to one of these attributes automatically calculates new levels evenly distributed between the lower and upper values.

    • Relation. Specifies whether the levels are interpreted as values or as %/difference (diff) from a specified baseline.

    • Baseline. The value used for converting levels into values when the relation is % or diff.

    • Values. A space-separated list of the actual values at which to study the factor. The Values are calculated using the Levels (or Lower/Upper values) as a percentage or difference (specified by the Relation attribute) from the Baseline (for techniques that support those attributes).

      For example, for Levels = “-10 10”, Baseline = 20, Relation = “%”, the Values are calculated as “18.0 22.0”.

      Because the values are calculated from other attributes, you cannot edit the contents of this column.

    The following attributes are not common to all the techniques:

    • Alpha (Central Composite technique only). The lower and upper levels specify the two levels at which a 2-level full-factorial study is performed. The center point is also studied. The Alpha option is a ratio defining two other points (also known as “star points”) at which to study the given factor. For example, Alpha set to 0.25 indicates the factor is to be studied at points 1/4 of the way from the baseline to the lower and upper levels. Alpha set to 1.5 indicates the factor is to be studied 50% beyond the lower and upper levels. For example, Lower = 5, Upper = 20, Baseline = 10, and Alpha = 0.25 results in Levels = {5, 8.75, 10, 12.5, 20}.

    • Cluster (Adaptive DOE technique only). The intent of clustering is to define subsets of factors that will be simultaneously varied while keeping other factors constant. This allows user to define which factors are coupled and which are uncoupled by placing them in clusters defined by integer numbers. If all clusters have a unique number, all factors are considered independent, if they all have the same number they are all considered coupled. The benefit of clustering is more efficient searching of the space. This is an optional extra input. Default for DOE is all factors in same Cluster. Cluster definition can be defined based on:

      • Prior physical insight or based on the results of an orthogonal DOE study (e.g. Box Behnken) to identify coupled or uncoupled terms.
      • The main effects plot can be used to identify the contribution of the Cluster variables. If the contribution is low, the Cluster can be dropped by setting the Cluster to zero (0). At any time in future iterations, the Cluster can be activated again.

    • Column (Data File only). If you specified to not use a header row to find factors in the file, you must provide the column number for each factor.

  6. Click Update factor baselines to current values when executing if you want the baseline values updated to the current parameter values before executing.

    If Isight previously modified a parameter, this option allows for automatic updating of the baseline of all factors to the current parameter values in Isight, prior to executing the DOE technique, which will readjust the values to be studied appropriately. By default, this option is not selected and the user-defined settings are retained. This option is useful if the DOE technique is executed after another element of the simulation process flow that might change the parameter values (e.g., after an Optimization component), so that the DOE study can be performed around the new design point.

  7. If desired, click Edit at the bottom of the editor to set factor options for one or more factors.

    For more information, see Editing Attributes for Multiple Parameters.

  8. If desired, map an option to a parameter.

    For more information, see Mapping Options and Attributes to Parameters.

  9. If desired, click Constraint... (Sobol Sequence DOE technique only) to impose a constraint on factors.

    For more information, see Configuring the Sobol Sequence Technique.

  10. Click OK to save your changes and to close the DOE Component Editor.