Overview for Create Plackett-Burman Design

Use Create Plackett-Burman Design to create a designed experiment to identify the most important factors early in the experimentation process. Plackett-Burman designs can fit 2 – 47 factors that each have 2 levels. Usually, you use a Plackett-Burman design when you are starting with 8 or more factors and want to identify the most critical factors to study in subsequent experiments. For more information, go to Plackett-Burman designs .

When you create a design, Minitab stores the design information in the worksheet, which shows the order in which data should be collected. Once you have collected your data, use Analyze Factorial Design to analyze the data.

For example, process engineers at a company that sells dairy products design an experiment to study various factors that affect ice cream texture. The experiment includes 9 factors including fat content, pasteurization, temperature, homogenization process, mixing speed, draw temperature, emulsifier, stabilizer, and cooling speed. The engineers create a Plackett-Burman design so that they can determine which factors are most important. Then, the engineers plan to use other factorial designs and response surface designs to study these factors in greater detail.

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

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
  • Stat > DOE > Screening > Create Screening 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 include a factor that is difficult to randomize due to time or cost constraints, use Create 2-Level Split-Plot Design .
  • To identify the most important factors early in the experimentation process, use Create Definitive Screening Design .
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