DOE
overview  

Stat > DOE

These advanced Design of Experiments (DOE) capabilities help you improve your processes. You can screen the factors to determine which are important for explaining process variation. After you screen the factors, Minitab helps you understand how factors interact and drive your process. You can then find the factor settings that produce optimal process performance.

Select one of the following commands:

> Factorial

Create Factorial Design - generates two-level full, fractional, and split-plot factorial designs, and Plackett-Burman designs

Define Custom Factorial Design - creates a factorial design from data that you already have in the worksheet

Select Optimal Design - selects a subset of design points, augments a design, or evaluates a design

Pre-process Responses for Analyze Variability - calculates statistics in a single response column from experimental repeats or replicates

Analyze Factorial Design - fits two-level full, fractional, and split-plot factorial designs, and Plackett-Burman designs

Analyze Variability - detects and models dispersion effects in two-level factorial experiments

Factorial Plots - displays main effects, interactions, and cube plots for two-level full and fractional factorial designs, and Plackett-Burman designs

Contour and Surface Plots - draws a contour plot and a three-dimensional response surface plot

Response Optimizer - calculates a numerical optimal solution and draws an interactive plot to help identify the combination of factor settings that jointly optimize a set of responses

Overlaid Contour Plot - draws a contour plot for multiple responses

> Response Surface

Create Response Surface Design - generates Box-Behnken and central composite designs

Define Custom Response Surface Design - creates a response surface design from data that you already have in the worksheet

Select Optimal Design - selects a subset of design points, augments a design, or evaluates a design

Analyze Response Surface Design - fits a response surface model including Box-Behnken and central composite designs

Contour and Surface Plots - draws a contour plot and a three-dimensional response surface plot

Response Optimizer - calculates a numerical optimal solution and draws an interactive plot to help identify the combination of factor settings that jointly optimize a set of responses

Overlaid Contour Plot - draws a contour plot for multiple responses

> Mixture

Create Mixture Design - generates settings for simplex centroid and simplex lattice designs

Define Custom Mixture Design - creates a mixture design from data that you already have in the worksheet

Select Optimal Design - selects a subset of design points, augments a design, or evaluates a design

Simplex Design Plot - draws a simplex design plot

Analyze Mixture Design - fits data from any Scheffe mixture design

Contour/Surface Plots - draws a contour plot and a three-dimensional response surface plot

Response Trace Plot - draws a response trace plot

Response Optimizer - calculates a numerical optimal solution and draws an interactive plot to help identify the combination of factor settings that jointly optimize a set of responses

Overlaid Contour Plot - draws a contour plot for multiple responses

> Taguchi

Create Taguchi Design - generates Taguchi orthogonal array designs

Define Custom Taguchi Design - creates a Taguchi design from data that you already have in the worksheet

Analyze Taguchi Design - fits a model to a Taguchi design

Predict Taguchi Results - predicts results for Taguchi designs

> DOE

Modify Design - changes factor names and levels

Display Design - changes the design order and coding of factors in the worksheet