Response variables for a given set of input variables.Īn Optimization is a mathematical procedure used to determine the best design for a set of given constraints, by changing Package reports for data generated during the approach.Ī Fit is a mathematical model that is trained by data and is capable of predicting output View the computational results from the DOE. This data typically comes from other approaches, such as DOEs or previously run Optimizations. Screens the maximum number of main effects with the least number of experimental runs in case of two-level factors.Įxplores how controllable variables can be used to mitigate the effects from the uncontrolled variables.Įdit the summary of run data stored in the run matrix by editing existing runs or adding new run data.Īn Inclusion matrix contains existing data that will be appended into the newly created approach as known data points. Modified Extensible Lattice Sequence (Mels)Ī lattice sequence is a quasi-random sequence, or low discrepancy sequence, designed toĮqually spread out points in a space by minimizing clumps and empty spaces.A Latin HyperCube DOE, categorized as a space filling DOE, is the generalization of this concept to an arbitrary number of dimensions. Number generator, based on the Hammersley points, to uniformly sample a unit hypercube.Ī square grid containing sample positions is a Latin square if, and only if, there is only one sample in each rowĪnd each column. Hammersley sampling belongs to the category of quasi-Monte Carlo methods. This will resolve all the effects and interactions. Information matrix that is inverted during the Fit’s regression analysis, which in turn improves the numerical efficiency of the DOE.Ī factorial experiment in which only a chosen fraction of the combinations required for the Full Factorial DOE is run.Įvaluates all possible combinations of input variable levels. By identifying the type of regression that will be used, samples are selected to maximize the determinant of the Primarily intended to be used as the input matrix for a Least Squares Regression Fit. Generates higher order response surfaces using fewer required runs than a normal factorial. Learn how to create, open, import and save models.īefore you can create approaches you must first setup your Study by defining input variables and output responses.ĭefine the models, input variables, and output responses to be used in the study. Learn the basics and discover the workspace.ĭiscover HyperStudy functionality with interactive tutorials. Numerical methods available for a DOE approach.Ĭentral Composite Design contains an imbedded factorial or fractional factorial design with center points that areĪugmented with a group of `star points' that allow the estimation of curvature. Select a numerical method to use when evaluating the DOE. By running a DOE, you can determine which factors are most influential on an output response. To investigate their effect upon the output responses and to get an understanding of the global behavior Is a specific set of steps taken to study the mathematical model of a design.Ī DOE is a series of tests in which purposeful changes are made to the input variables Once the study Setup is complete, an unlimited combination of approaches can be added to a study. A study is a self-contained project in which models, variables, output responses, and approaches are defined.
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