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

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

- Under Task, choose Select optimal design.
- In Number of points in optimal design, enter the number of experimental runs to select from the candidate set.
- 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 |

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.

- From Task, select Augment/improve design (you may optionally provide an indicator column that you created).
- 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.
- (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.

- 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 |

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.

- From Task, select Evaluate design (you may optionally provide an evaluate column that you created).
- (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.
- 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 |