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Select optimal runs, augment, or improve a general full factorial design

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Stat > DOE > Factorial > Select Optimal Design

Select the task, then enter the number of design points for the optimal design.

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Select optimal design

Complete the following steps to select a D-optimal design from candidate runs in a general full factorial design.

  1. Under Task, choose Select optimal design.
  2. In Number of points in optimal design, enter the number of experimental runs to select from the candidate set.
  3. Click Terms. D-optimality depends on the terms. After you specify the terms, Minitab selects the experimental runs.

In this worksheet, the columns contain a general full factorial design. Minitab analyzes all of the factors as categorical factors. The full design forms the candidate set for the optimal design.

C1 C2 C3 C4 C5 C6 C7 C8
StdOrder RunOrder PtType Blocks Temperature Copper Endcap Method
53 1 1 1 125 60 0.25 Friction
8 2 1 1 50 60 0.50 Soldering
40 3 1 1 100 60 0.50 Soldering
54 4 1 1 125 60 0.25 Soldering
21 5 1 1 75 60 0.25 Friction

Augment/improve design

Complete the following steps to add experimental runs or change experimental runs in a D-optimal way.
Note

The experimental runs can be the only runs in the worksheet, or you can use a column in the worksheet to identify which runs are part of the design.

  1. From Task, select Augment/improve design (you may optionally provide an indicator column that you created).
  2. In Number of points in optimal design, enter the number of experimental runs for the improved design. To keep the same number of runs, enter 0 for the number of points.
  3. (Optional) Enter a column that identifies the initial experimental runs to augment and identifies any experimental runs that must be in the optimal design.
    • The number in the column is the number of replicates of that experimental run in the initial design. A 0 identifies a point that is not in the initial design, but is part of the candidate set of experimental runs.
    • The sign in the column specifies whether the experimental run must be in the optimal design.
      • A positive value identifies a point that can leave the design.
      • A negative value identifies a point that must remain in the optimal design.
  4. Click Terms. D-optimality depends on the terms. After you specify the terms, Minitab augments or improves the optimal design.
In this worksheet, the columns C1 to C8 contain a general full factorial design. The Initial Design column shows which points are in the initial design to augment or improve:
  • −2 indicates that the optimal design will have at least 2 replicates of the experimental run.
  • 0 indicates that the initial design does not include the experimental run. The improved design can include or not include this experimental run.
  • −1 indicates that the optimal design will have at least 1 replicate of the experimental run.
  • 1 indicates that the initial design has 1 replicate of the experimental run. The improved design can include or not include this experimental run.
  • 3 indicates that the initial design has 3 replicates of the experimental run. The improved design can include or not include this experimental run.
C1 C2 C3 C4 C5 C6 C7 C8 C9
StdOrder RunOrder PtType Blocks Temperature Copper Endcap Method Initial Design
53 1 1 1 125 60 0.25 Friction −2
8 2 1 1 50 60 0.50 Soldering 0
40 3 1 1 100 60 0.50 Soldering −1
54 4 1 1 125 60 0.25 Soldering 1
21 5 1 1 75 60 0.25 Friction 3

Evaluate design

Complete the following steps to calculate optimality measures for a design. You can use this information to compare designs.
Note

The experimental runs can be the only runs in the worksheet, or you can use a column in the worksheet to identify which runs are part of the design.

  1. From Task, select Evaluate design (you may optionally provide an evaluate column that you created).
  2. (Optional) Enter a column that identifies which experimental runs to evaluate. Positive integers specify the number of replicates of that experimental run in the design to evaluate. A 0 value identifies a point that is not in the design. If you do not enter a column, then Minitab evaluates all of the experimental runs in the worksheet.
  3. Click Terms. D-optimality depends on the terms. After you specify the terms, Minitab evaluates the experimental runs.
In this worksheet, the columns C1 to C8 contain a general full factorial design. The Initial Design column shows which points are in the design to evaluate:
  • 0 indicates that the design does not include the experimental run.
  • 1 indicates that the optimal design has 1 replicate of the experimental run.
  • 3 indicates that the optimal design has 3 replicates of the experimental run.
C1 C2 C3 C4 C5 C6 C7 C8 C9
StdOrder RunOrder PtType Blocks Temperature Copper Endcap Method Initial Design
53 1 1 1 125 60 0.25 Friction 0
8 2 1 1 50 60 0.50 Soldering 0
40 3 1 1 100 60 0.50 Soldering 0
54 4 1 1 125 60 0.25 Soldering 1
21 5 1 1 75 60 0.25 Friction 3
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