Design-Expert 7.1
Introduction
Design-Expert offers an impressive array of design options. Version 7.1 includes dozens of new features that increase the ease-of-use, functionality, power and appeal of an already great product.
After you build your design in Design-Expert, generate worksheets with your experiments laid out for you in randomised run-order. Add, delete or duplicate runs in any design with the handy design editor. With annotated statistical analysis and an extensive context-sensitive help system, you can easily interpret the outputs. Interactive 2-D graphics support use of your mouse to drag contours or set flags that display coordinates and predicted responses. Rotatable 3-D plots make response visualisation easy.
With the powerful optimisation features in Design-Expert, you can maximise desirability for dozens of responses simultaneously. There are also unique tools for generating and graphing propagation of error (POE), thus allowing you to achieve six-sigma objectives for reducing variation. Maximise, minimise or hit targets with factor levels set to give you robust results.
A Tremendous Variety of Designs Meet All Your Experimental Needs
- Standard two-level full and fractional factorials (up to 512 runs) for testing up to 21 factors simultaneously, now also with minimum-aberration blocking choices.
- General (multilevel) factorial designs (up to 32,000 runs) using factors with mixed levels.
- Taguchi orthogonal arrays.
- High-resolution irregular fractions, such as 4 factors in 12 runs.
- Placket-Burman designs for 11, 19, 23, 27 or 31 factors in 12, 20, 24, 28 or 32 runs respectively.
- Response Surface Method (RSM) designs, including central composite (small, face-centered, etc.), Box- Behnken (3-level), hybrid and D-Optimal.
- Mixture designs, such as simplex-lattice, simplex-centroid screening (for up to 24 components) and D-optimal.
- Combined mixture and process designs (mix your cake and bake it, too!).
- Ability to graph any two columns of data on the XY graph (this is a great way to view a blocked effect).
- Easy-to-use automatic or manual model reduction.
- Ability to easily analyse designs with botched or missing data.
Enjoy Incredible Flexibility in Design Modification
- Define your own generators for fractional factorial designs.
- Impose linear multivariable constraints on RSM or mixture design.
- Add categorical factors to RSM, mixture or combined designs.
- Create a factorial candidate set for RSM designs when only specific factor levels are available.
- Ignore a row of data while preserving the numbers.
Build Confidence with Statistical Analysis of Data
- If your model is aliased, a warning will pop up prior to viewing the ANOVA for two-level fractional factorials, allowing you to make substitutions for aliased effects.
- Select optional annotated views for assistance interpreting the ANOVA.
- Inspect F-test values on individual model terms and confidence intervals on coefficients.
- Automatically select effects using Lenth's criteria or probability values.
- Take advantage of new user preferences, for example, make a global change in the significance threshold (0.05 by default vs. 0.01 and 0.1).
Take Advantage of Powerful Tools for Response Modeling
- Change models from RSM to factorial and back and from Scheffe (mixture) to slack (during design building and at model selection).
- Add integer power terms to the model, for example, quartic.
- Select terms for model, error, or to be ignored (allows analysis of split-plot and nested designs).
Simplify Interpretation with Terrific Graphics
- A quick summary of the design type as well as factor, response and model information is available by clicking on the design status node.
- Discover significant effects at a glance with half-normal or normal probability plots, made easier by including points representing estimates of pure error (if available from your design).
- See the Box-Cox plot for advice on the best response transformation.
- View a complete array of diagnostic graphs to check statistical assumptions and detect possible outliers (bonus feature: predicted-versus-actual graphs with a 45º line).
- Graph alternative aliased interactions.
- See the effects plot in the original scale after transforming the response.
- Observe variation in predictions by viewing the least significant difference (LSD) bars on the model graphs.
- Poorly predicted regions on contour maps are shaded to give you confidence in your predictions.
- Slice your contour plots using a simple slide bar (and see actual design points when they're on a slice!)
- Set flags to reveal the predicted response at any location.
- Drag 2-D contours using your mouse.
- Rotate 3-D graphics and see projected 2-D contours.
- Edit colors, text and more to produce professional reports.
- See all effects on one graph with trace and perturbation plots.
- Plot the standard error of your design on any graph type (contour, 3-D, etc.)
Locate Your Sweet Spot with Multiple Response Optimisation
- Maximise, minimise or target specific levels for both responses and factors.
- Set weight and importance levels to prioritise responses for desirability.
- Choose 2-D contour, 3-D surface, histogram or ramp desirability graphs.
- Include categorical factors.
- Set factors at constant levels.
- Add equation-only responses, such as cost, to the optimisation process.
- Look at the overlay plot to view constraints on your process or formulation.
- Predict responses at any set of conditions (including confidence levels).
- Discover optimal process conditions or formulations.