Purpose
This DOE app helps you determine the relationship between factors affecting a process and the output of that process.
You can use it to design an experiment, analyze experimental data and optimize output.
Features
- Various types of designed experiments to help you create a design.
- Customization of design table by replication, randomization, blocking, etc.
- Fit of mathematical model to data from test runs.
- Diagnostic statistics and graphs to help you interpret the results.
- Optimization of response after defining factor constraints.
Updates since OriginPro 2024:
- Support available design for 2-level factorial and central composite design (with default parameters).
- Save and load design parameters for Power and Sample Size and Create Design.
Please read this blog to learn the updates.
Updates since OriginPro 2025:
- Definitive screening design.
- Quick and easy to add terms or remove terms from model via recalculation.
- Simultaneously optimize multiple responses, each with a different model.
Installation
The App requires R software (recommended version 4.4.1) and packages (rsm, FrF2, daewr, car, mixexp).
- Open the download page for R version 4.4.1
- Download the file named R-4.4.1-win.exe and install it
- Once you have successfully installed R, you can then install the App
- The App will download and install required R packages when you run it the first time.
Note that if you installed the App prior to instalilng R, the App icon will show in the Apps bar.
Simply click on that icon to continue after you have installed R.
Note: If downloading packages fails, a pop-up dialog will ask you to copy 2 lines of commands from Results Log and run them in R to complete downloading packages.
Related FAQ: FAQ-1214 What can I do when Origin has trouble launching R?
This App requires orgutils app.
Operation
Click the app icon to open the dialog with 4 buttons. Click one of them to open a dialog.
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Power and Sample Size
Determine sample sizes before creating a design. Calculate power for a given sample size or sample sizes for given power values.
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Define Custom Design
Create a design from data in the worksheet. The following types of design are supported.
- Definitive Screening Design
- Factorial Design
- Response Surface Design
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Create Design
Identify factors and levels for each factor. Use techniques of the design to create a design table that makes the experiment cost-effective. Conduct a series of experiments and collect response data for each run in the table. The following types of design are supported.
- Definitive Screening Design
- Factorial Design
- 2-Level Factorial
- Plackett-Burman
- General Full Factorial
- Response Surface Design
- Central Composite
- Box-Behnken
- Mixture Design
- Simplex Centroid
- Simplex Lattice
- Extreme Vertices
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Analyze Design
Fit a model to data collected using the design. Evaluate which factors have a significant impact on the response. You can interpret the relationship between factors and response through a variety of analytical tools and graph tools.
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Optimize Response
Determine what levels of factors should be to achieve a desired response. You can choose goals like minimize, maximize and target to optimize. Put constraints on factor levels before optimization.
Help File
This app provides a help file that introduces design of experiments and explains dialog settings. Click ? button in dialog or press F1 to open it.
Sample OPJU File
This app provides a sample OPJU file and a data file. Right click on the app icon in the Apps Gallery window, and choose Show Samples Folder from the short-cut menu. A folder will open. Drag-and-drop the project file DOE Sample.opju from the folder onto Origin. The Notes window in the project shows detailed steps.
Note: If you wish to save the OPJU after changing, it is recommended that you save to a different folder location (e.g. User Files Folder).