Design Folio
In order to develop the best possible products and processes in the most cost-effective way, it is necessary to plan the testing process carefully so that all relevant factors and potential interactions of factors are considered without wasting time, effort or money. Design of Experiments (DOE) is widely used across the natural and social sciences to develop experimentation strategies that maximize learning using a minimum of resources.
Weibull++ includes three kinds of folios for design of experiments:
- Standard design folios are used for identifying important factors (i.e., "screening") and determining the best settings for these factors (i.e., "optimization"). They can also be used for simple one factor designs that allow you to compare the response at different factor levels.
- Robust design folios are used to minimize the system's sensitivity to noise factors (i.e., "robustness testing"). Robust design folios include all the functionality of the standard design folio, with the addition of some features specific to the robust design methodology.
- Mixture design folios are used when the factors in an experiment are components in a mixture, and when you wish to determine the best proportions to use for each component.
To create a DOE folio, right-click the DOE folder in the current project explorer and choose the folio type.
Standard Design
Robust Design
Mixture Design
When the folio first appears, only the Design tab will be displayed, which allows you to configure an experiment design. After you have specified all of the settings on the Design tab, choose Design > General > Build Design or click the icon on the control panel.
This will create a second tab called Data that a) shows a "plan" for how the experiment needs to be performed and b) allows you to enter and analyze response data from an experiment that follows that plan. (If you want to change the experiment design settings after the Data tab has already been created, see Changing Design Settings.) After you analyze the data, a summary of results (including the factors that were found to be significant) will appear on the control panel.
Tip: This documentation assumes that you will first design an experiment, then perform it, and then enter and analyze the resulting data. However, if you already have data available from a prior experiment, you can also use the Design tab to build a design that reflects the prior experiment and then build the design so you can enter and analyze the results on the Data tab.
After you have entered the response information in the Data tab, you can choose Data > Analysis > Plot or click the icon on the control panel.
This will create a third tab called Analysis Plot that allows you to view all of the graphical plots that are relevant to the current analysis of the response data.
The information presented in the topics that follow describes interfaces and procedures that are common to all design types. To learn more about a specific design type, see one of the following topics:
