Design-Expert software description

Design-Expert software offers features, better than any other package, presented in an incredibly easy-to-use format. Design-Expert is a must for anyone wanting to improve a process or a product. With Design-Expert you can screen for vital factors, locate ideal process settings to achieve peak performance and discover your optimal product formulations.

 

 

 

 

 

Reach the peak of performance with your process or formulation. Design-Expert includes all of the features of Design-Ease, plus provides in-depth analysis of process factors or mixture components. Combine mixture and process variables in your designs. Design-Expert offers rotatable 3D plots to help you visualize your response surface. Explore the 2D contours with your mouse, setting flags along the way to identify coordinates and predict responses. The sweet spot where all your requirements are met can be found via the program's numerical optimization function, which finds the most desirable factor settings for up to 12 responses simultaneously!

Design-Expert new features

General

- Pareto chart of t-values of effects: Quickly see the vital few effects relative to the trivial many from two-level factorial experiments.
- New Color Byoption: Color-code points on graphs according to the level of another factor—a great way to incorporate another piece of information into a graph.
- Right-click on any response cell and ignoreit: This feature allows you to ignore a response data point without having to ignore the entire row.
- Screen tips: Press the new tips button for enlightenment on the current screen—this is especially helpful for novice users.
- 3D surface plots for categorical factors: See colored bars towering above others where effects are greatest.
- Min Run Res IV(two-level factorial) designs for 5 to 50 factors: Screen main effects with maximum efficiency in terms of experimental runs.
- Min-Run Res Vdesigns for 6 to 31 factors: Resolve two-factor interactions (2FIs) in the least runs possible while maintaining a balance in low versus high levels.
- Two-level fractional factorials for up to 512 runs and 21 factors: Build bigger designs than ever-before possible.
- On plots of effects simply draw a box around the ones you want selected for your model: This is much easier than clicking each one with your mouse.
- Central composite designs (CCD’s) are now available for up to 30 factors and 8 blocks: This represents a significant expansion in RSM capability.
- CCD’s are available that are based on the Min-Run Res V fractional-factorial core: Take advantage of a much more efficient design for larger numbers of factors.
- Box-Behnken designs are expanded up to 21 factors: This popular RSM design previously was limited to certain numbers of factors, but that is no longer the case.
- Crosshairs window: Predict your response at any place in the response surface plot.
- Full-color contour and 3D surface plots: Graduated or banded colorization adds life to reports and presentations.
- Magnification feature: An incredible tool for expanding a mixture graph that is originally a small sliver and difficult to interpret.
- Mixture-in-mixture designs: Develop sophisticated experiments for immiscible liquids or multilayer films involving separate formulations that may interact.
- Add blocks D-optimally: This feature will be especially useful for mixture designs, which previously could not be blocked automatically.
- Points on 3D graphs: See lollipops protruding from surfaces where actual responses were collected.
- Row(s) in the design layout are highlighted when point(s) are selected on the diagnostics: The highlighting feature makes identification of problematic data much easier.
- Numerical optimization solutions are now carried over to graphical optimization and point prediction: Explore the results of the numerical optimization on other screens.

New design creation

- Design-builder updates resolution of two-level fractional factorials when the number of blocks is changed: Immediately see how segmenting a design might reduce its ability to resolve effects.
- Block names are now entered during the design build: Identify how you will break up your experiment, for example by specific shift, material lot or the like.
- Min-run Res IV plus twooption: Ask for two extra runs to make your experiment more robust to missing data.
. - User-defined base factors for design generators: You have more flexibility to customize fractional factorial designs.
- Expanded D-optimal capabilities—impose balance penalty, force categoric balance: This feature helps users equalize the number of treatments.
- CCD’s offer new alpha choices of Practical,Orthogonal Quadraticand Spherical: Develop more control over where you put your ‘star’ points.
- Coordinate Exchange capability for D-optimal designs: Avoid the arbitrary nature of designs constructed from candidate point sets.
- In General or Factorial D-optimal designs, categorical factors can be specified as either nominal or ordinal (orthogonal polynomial contrasts): This affects the layout of analysis of variance (ANOVA).
- Mixture design builder recognizes inverted simplexes and constrained regions that benefit by being inverted: This provides dramatic advantages in the power for estimating model terms.

New analysis capability

- From Alias List, Pareto Chart or Effects Plots views, right-click on effects to show aliases: Never lose sight of what really is being measured in fractional-factorial designs.
- Select alternative aliased effects: Choose what you think makes most sense based on your subject-matter knowledge.
- Backward stepwise regression is now applicable to factorial designs: This is useful for quickly analyzing general (categorical) factorials.
- Means and standard deviations for all experimental inputs (factors) and outputs (responses) are added to the Design Summary screen: This provides a handy assessment of your system.
- The user can define their preference for sums of squares calculations for both numeric and categoric factors to be sequential, classical, or partial: These distinctions are important for statisticians who want to do ANOVA in specific ways.
- Cox model option for mixtures: May be more informative for formulators with a standard (reference) blend to which they’d like to compare more-optimal recipes.

New design augmentation tools

- Semifold: In only half the runs needed by a normal foldover, augment Res IV designs to resolve specified 2FIs aliased in the original block of runs.
- Add center points, blocks and replicates without rebuilding the design: This will be a real time-saver.

New diagnostics capability

- DFFITS: Spot influential runs via this deletion diagnostic that measures difference in fits when any given response is removed from the dataset.
- DFBETAS: See from this deletion diagnostic how model terms change due to an influential run.

Updated graphics

- Grid lines on contour plots: See more readily what the coordinates are at any given point.
- Select the details printed on flags planted on contour plots: As a user you now can control this feature.
- Confidence bands on one-factor plots: Get a good feel for the uncertainty in a predicted response as a function of the factor level.
- Color-codes for positive versus negative effects: Assess plus or minus impacts on half-normal and Pareto plots.
- Smart tic marks: Get more-reasonably rounded settings straight off.

Improved user interface

- Export the graph to a file: Save the graph as an enhanced metafile (.emf) that can be inserted as a picture from file to Microsoft Word and the like.
- Set row status to normal, ignore or highlight: This allows users control over their design matrix.

More options for Design-Expert design evaluation

- Annotation option on reports: This will be a boon to those who may be unfamiliar with all the esoteric statistics needed for design evaluation.
- Customizable design evaluation content and power levels: Use the OPTIONS button to select which statistics to display, specific power levels to report, and whether to display the standard error or variance on the graph (with the option to scale by N—the number of runs in the design).
- Specify model terms to ignore so they don’t display in the alias list: For example, don’t bother showing interactions of four or more factors.
- Evaluation can be done on either design or a particular response: Shows the effect when data is missing from a specific response, but not all responses.

Expanded help

- Tutorial movies: See Flash demo’s of features via Screen Tips—a very effective way to show how to navigate through the software.
- Internet links: These are helpful connections to further information.

New import/export tools

- XML (eXtensible Markup Language) capability: Export design files or reports in viewable format that can be manipulated for further processing (The XML tool also allows import of designs created externally).
- Scripting capability: Run Design-Expert software in batch mode so it can be tied into more comprehensive lab-ware or used to cycle through massive quantities of data, for example from computer-based simulations.

Design-Expert courses design of experiments

Science Plus Group is closely cooperating with CQ Consultancy in Leuven (Belgium) in the field of Design of Experiments (DoE). CQ offers excellent courses that can bring your knowledge to a higher level. Participants in a course can have significant discounts on DoE software and vice versa. What can we tell about the courses?

Introduction

Research and Development: searching for new products and improving existing processes. This can be accomplished efficiently and optimally only in one way: the way of Experimental Design. Experimental Design, alias Design of Experiments (DOE) or Statistical Design of Experiments (SDE), not only guarantees reaching the preset goal, but on top costs a minimum number of experiments ... on condition that one takes into account the characteristics of the field of application. The optimal strategy of experimenting will be different in chemical industries as compared to for example the automotive industry. This explains the specific context of this course.

Course Information

Three courses on DOE are offered: an introductory course (DOE-I: 4 days), an intermediate course (DOE-II: 2 days), and an advanced course (DOE-III: 1 day). Participants are assumed to have a thorough understanding of some basic statistical techniques (confidence intervals, hypothesis tests, ANOVA). The course Applied Statistics is ideally suited as a preparation to DOE-I. The required foreknowledge can however also be obtained by private study. Participants who opt for private study will receive the necessary course material (a selection of the course material of the Applied Statistics course), twenty days before the start of DOE-I. The same material is also treated in an (optional) preparatory course day.

Ordering

For price information and ordering, please visit the Prices and Ordering Page 

Manufacturer page

Science Plus Group is a distributor for this product. You can also visit the StatEase website, the manufacturer of this product.