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The sixth edition of this introductory text features increased focus on computers as well as the
relationship between experiments and their resulting models. It allows the reader to obtain information
for characterization and optimization of systems; improve manufacturing processes; design and
develop new processes and products; evaluate material alternatives in product design; improve the field
performance and reliability of products; and more. Access to an affiilated website is included.
Design and Analysis of Experiments discusses nested and split-plot designs, regression fitting, and
response surface methods, along with other process optimization methods. There is extensive
coverage of factorial and fractional designs, and a presentation of new analysis techniques, including the
generalized linear model. There is also expanded coverage of experiments with random factors,
response surface methods, experiments with mixtures, and methods for process robustness.
From the Preface: “...There are numerous examples illustrating all of the design and analysis
techniques. These examples are based on real-world applications of experimental design and are
drawn from many different fields of engineering and the sciences. This adds a strong applications flavor to
an academic course for engineers and scientists and makes the book useful as a reference tool for
experimenters in a variety of disciplines...”
Target Audience: Students; process engineers, quality improvement specialists, research and
development personnel, and others in the process industries requiring a firm footing in experimental design.
Table of Contents:
Introduction
Simple Comparative Experiments
Experiments with a Single Factor: The Analysis of Variance
Randomized Blocks, Latin Squares, and Related Designs
Introduction to Factorial Designs
The 2k Factorial Design
Blocking and Confounding in the 2k Factorial Design
Two-Level Fractional Factorial Designs
Three-Level and Mixed-Level Factorial and Fractional Factorial Designs
Fitting Regression Models
Response Surface Methods and Other Approaches to Process Optimization
Experiments with Random Factors
Nested and Split-Plot Designs
Other Design and Analysis Targets
Bibliography
Appendices
Index
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