For the option: | Do the following: |
|---|---|
Investigation Strategy | Select one of the following: ■Study - Perimeter ■Study - Sweep ■DOE Screening (2 Level) ■DOE Response Surface ■Variation - Monte Carlo ■Variation - Latin Hypercube Learn more about Investigation Strategies. |
Select one of the following: ■Linear ■Interactions ■Quadratic ■Cubic ■None. See None Option. | |
DOE Design Type | Select one of the following: ■Plackett-Burman ■Fractional Factorial ■Full Factorial ■Box Behnken ■CCF (Central Composite Faced) ■D-Optimal ■Latin Hypercube Learn more about DOE Design Types. |
Candidate Runs | This option is only applicable to D-Optimal designs. It specifies the size of the candidate pool from which the D-Optimal algorithm chooses rows for a design matrix. ■All - Uses all of the candidate runs that are in a full factorial design for a given collection of factors (potentially a very large number). ■Random - Limits the number of Candidates, thus reducing the run time of the D-Optimal algorithm. If you choose Random, enter a value for Number of Candidate Runs. |
Number of Runs | Indicates a numeric value of unique Trials (rows) in the Design Space and Work Space. ■Value - Adams Insight specifies a value for all designs types except Plackett-Burman. ■Range - For Plackett-Burman and D-Optimal designs, this option provides a range of values for the possible number of trials. Generally, you can increase the fidelity of your final results as you increase the number of trials in the experiment. |
Number of Center Points | Specifies the number of center points to include in the Number of Runs specified above. This option applies to the following: ■D-Optimal DOE design types - Be sure to set an adequate number of runs so that you have enough trials to create the response surface. ■Variation investigation strategies - The first trials are held at the nominal condition of the system. The scatter plots will also reflect this with the trial identifier in the plot being displayed in red. For example, if you specify Variation - Latin Hypercube, Number of Runs=100, and Number of Center Points=1, then Adams Insight generates 100 trials with Trial 1 being set to the nominal condition. |
Number of Candidate Runs | Specifies the number of Candidate Runs for the D-Optimal design. |
Run Order | Select one of the following: ■Standard - You can use this option if you are running an analytical Design of Experiment (DOE), and do not expect the order of the runs to have a significant effect on the results. ■Random - This is generally the run order to use for physical DOEs. For example, if your response varies depending on when you measure it during the course of a day, you should randomize the run order in order to capture the overall behavior of the system. ■Ease of Adjustment - This option is also more applicable for physical DOEs. It affects the Work Space and Design Space matrix when you set a Factor attribute to Ease of Adjustment. |