Use the Simulation Experiment option in the Simulator red triangle menu to run a designed experiment to simulate responses across factor combinations. When you select Simulation Experiment, you need to specify the number of design points, the portion of the factor space to be used in the experiment, and which factors to include in the experiment. For factors that are not included in the experiment, the current value set in the Profiler is used in the experiment.
The experimental design is a Latin Hypercube. The number of runs at each design point is determined by the N Runs value specified in the Simulator report. See N Runs. At each design point, N Runs random draws are generated with the design point serving as the center of the random draws. The shape and variability come from the specified distributions. The output table has one row for each design point and columns for the design factors and simulated responses.
For responses with spec limits, the simulated responses include the defect rate and an overall defect rate. You can use a Gaussian Process model to model the overall defect rate from the simulation experiment. For more information about Gaussian Process models, see “Gaussian Process” in Predictive and Specialized Modeling.
Note: The Simulation Experiment respects linear constraints that are incorporated into the Prediction Profiler.