| Entrance | What is it used for? |
| How do I choose? | Selection Assistant: Describe your needs, and it will identify the appropriate plans and rule out the others, explaining why. |
| Fact 2 Taguchi | 2-level factorial and fractional designs, L4 through L64 tables, with explicit handling of interactions and aliases. |
| XN | Mixed-level designs: Each factor can have its own number of levels, ranging from 2 to 6. |
| Sweeping plan | Screening: Quickly identify influential factors. Two-level tables or three-level DSDs. |
| Response surface methodology (RSM) | Full quadratic modeling and optimization: centered composite, Box-Behnken, Hoke, hybrid, and DSD. |
| Smart DOE | A catalog of certified 2- and 3-level designs that guarantees the absence of correlation between the main factors and the second-order terms, selected based on a trade-off between quality and the number of experiments. |
| Filling | Uniform coverage of the experimental space—the layout of machine learning models. |
| Grid | The project data table: this is where we enter the measured responses. |
| Analysis | The Machine Learning module, for analyzing the plan once the measurements have been taken. |
💡 The order of use is always the same: Choose a plan, build it, transfer it to the grid, conduct the tests and enter the Y values, then analyze. The first seven options cover the first two steps; «Grid» and «Analysis» are there so you don’t have to leave the menu.