Overview for Create General Full Factorial Design

Use Create General Full Factorial Design to create a designed experiment to study factors that can have any number of levels. You can use a general full factorial design to create full resolution, 2-level designs for 8 or more factors. Minitab stores the design information in the worksheet. The worksheet shows the order for the data collection.

For example, engineers conduct an experiment to investigate the effects of humidity, temperature, and copper content on the amount of warping that occurs in a copper plate. Humidity has 2 levels, temperature has 3 levels, and copper has 5 levels. They create a general full factorial design because two factors have more than 2 levels. The design includes 30 experimental runs, which represent all combinations of the factor levels.

This Minitab worksheet shows a portion of the design. The engineers perform the experiment by collecting data using the order shown in the RunOrder column, which contains the randomized order of the runs.

C1 C2 C3 C4 C5 C6 C7 C8
StdOrder RunOrder PtType Blocks Humidity Temperature Copper Content  
3 1 1 1 1 1 1  
4 2 1 1 1 3 2  
11 3 1 1 1 1 4  
10 4 1 1 2 1 4  
1 5 1 1 2 2 1  
6 6 1 1 2 3 5  
12 7 1 1 1 3 5  

After collecting the data, an engineer enters the response data in an empty column in the worksheet, and then analyzes the design.

Many of the choices you make when you create a design depend on your overall experimental plan. For more information, go to Phases of a designed experiment.

Where to find this analysis

Stat > DOE > Factorial > Create Factorial Design

When to use an alternate analysis

  • If you already have the factor columns in a worksheet, use Define Custom Factorial Design. Custom designs let you specify which columns are the factors and any other design columns that you already have.
  • To identify the most important factors early in the experimentation process, use Create Definitive Screening Design.