文档介绍：Page 1 Friday, December 17, 1999 1:08 PM
CONTENTS INDEX MEET MTB UGUIDE 1 UGUIDE 2 SC QREF HOW TO USE
19
Factorial Designs
■ Factorial Designs Overview, 19-2
■ Choosing a Design, 19-5
■ Creating Two-Level Factorial Designs, 19-6
■ Creating Plackett-Burman Designs, 19-24
■ Summary of Two-Level Designs, 19-28
■ Creating General Full Factorial Designs, 19-33
■ Defining Custom Designs, 19-35
■ Modifying Designs, 19-38
■ Displaying Designs, 19-42
■ Collecting and Entering Data, 19-43
■ Analyzing Factorial Designs, 19-44
■ Displaying Factorial Plots, 19-53
■ Displaying Response Surface Plots, 19-60
See also,
■ Chapter 23, Response Optimization
■ Session Five: Designing an Experiment in Meet MINITAB
MINITAB User’s Guide 2 19-1
CONTENTS INDEX MEET MTB UGUIDE 1 UGUIDE 2 SC QREF HOW TO USE
Page 2 Friday, December 17, 1999 1:08 PM
CONTENTS INDEX MEET MTB UGUIDE 1 UGUIDE 2 SC QREF HOW TO USE
Chapter 19 Factorial Designs Overview
Factorial Designs Overview
Factorial designs allow for the simultaneous study of the effects that several factors may
have on a process. When performing an experiment, varying the levels of the factors
simultaneously rather than one at a time is efficient in terms of time and cost, and also
allows for the study of interactions between the factors. Interactions are the driving
force in many processes. Without the use of factorial experiments, important
interactions may remain undetected.
Screening designs
In many process development and manufacturing applications, the number of potential
input variables (factors) is large. Screening (process characterization) is used to reduce
the number of input variables by identifying the key input variables or process
conditions that affect product quality. This reduction allows you to focus process
improvement efforts on the few really important variables, or the “vital few.” Screening
may also suggest the