Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of MINITAB are detailed enough to provide effective guidance to a new MINITAB user, the book is still general enough to be very helpful to users of other DOE software packages.
The book assumes that readers have good basic algebra skills. Since many students/readers have rusty statistical skills, Mathews provides an extensive review of basic statistical methods (graphical data presentation, descriptive statistics, and inferential statistics) and MINITAB usage in Chapters 1-3. Chapter 4 - DOE Language and Concepts - presents a friendly introduction to DOE free of the quantitative methods that are presented in later chapters. This chapter also includes a detailed explanation of Mathews' 11-step DOE process, guidelines for reporting the results of designed experiments, and an insightful list of ways that experiments can go wrong. Chapters 5-7 describe the design of experiments involving qualitative design variables and their analysis by ANOVA. Chapter 8 presents linear regression and all of the associated methods used for the analysis of quantitative design variables. Chapters 9-11 present two-level factorial, fractional factorial, and response surface design methods, respectively. Every chapter contains many examples with detailed solutions including extensive output from MINITAB.
Preface
Acknowledgments
Chapter 1 : Graphical Presentation of Data
Chapter 2 : Descriptive Statistics
Chapter 3 : Inferential Statistics
Chapter 4 : DOE Language and Concepts
Chapter 5 : Experiments for One-Way Classifications
Chapter 6 : Experiments for Multi-Way Classifications
Chapter 7 : Advanced ANOVA Topics
Chapter 8 : Linear Regression
Chapter 9 : Two-Level Factorial Experiments
Chapter 10 : Fractional Factorial Experiments
Chapter 11 : Response Surface Experiments
Appendix A
Bibliography
Index
CD Contents
Example Problem Data
Chapter Problems
Classroom Exercises and Labs
Excel Experiment Design Files
MINITAB v14 Macros
