Quality by Experimental Design, Fourth Edition

Achieve Technological Advancements in Applied Science and Engineering Using Efficient Experiments That Consume the Least Amount of Resources

Written by longtime experimental design guru Thomas B. Barker and experimental development/Six Sigma expert Andrew Milivojevich,Quality by Experimental Design, Fourth Edition shows how to design and analyze experiments statistically, drive process and product innovation, and improve productivity. The book presents an approach to experimentation that assesses many factors, builds predictive models, and verifies the models.

New to the Fourth Edition

• Updated computer programs used to perform simulations, including the latest version of Minitab®
• Four new chapters on mixture experiments: Introduction to Mixture Experiments, The Simplex Lattice Design, The Simplex Centroid Design, and Constrained Mixtures
• Additional exercises and Minitab updates

A Proven, Practical Guide for Newcomers and Seasoned Practitioners in Engineering, Applied Science, Quality, and Six Sigma

This bestselling, applied text continues to cover a broad range of experimental designs for practical use in applied research, quality and process engineering, and product development. With its easy-to-read, conversational style, the book is suitable for any course in applied statistical experimental design or in a Six Sigma program.

Foreword
Preface to the Fourth Edition
Preface to the Third Edition
Preface to the Second Edition
Preface to the First Edition
How to Use This Book

Part I : The Philosophy of Experimentation
Chapter 1 : Why Design Experiments?
Chapter 2 : Organizing the Experiment
Chapter 3 : The Neglected Response Variable

Part II : Statistical Experimental Design
Chapter 4 : The Factorial Two-Level Design: General Factorial Designs
Chapter 5 : Fractional Factorials at Two Levels
Chapter 6 : Multilevel Designs
Chapter 7 : Three-Level Designs
Chapter 8 : Blocking in Factorial Designs
Chapter 9 : Randomized Block and Latin Square
Chapter 10 : Nested Designs
Chapter 11 : Evolutionary Operation

Part III : Sorting the Signal from the Noise
Chapter 12 : Simple Analysis
Chapter 13 : Analysis of Means by Using the Variance
Chapter 14 : Yates Analysis: Analysis of 2k and 2k-p Designs
Chapter 15 : Matrix Algebra
Chapter 16 : Least Squares Analysis
Chapter 17 : Putting ANOVA and Least Squares to Work
Chapter 18 : ANOVA for Blocked and Nested Designs

Part IV : The Derivation of Empirical Equations from Statistically Designed Experiments
Chapter 19 : Case History of an Experimental Investigation

Part V : Utilization of Empirical Equations
Chapter 20 : Robust Design
Chapter 21 : Monte Carlo Simulation and Tolerance Design
Chapter 22 : Case History Completed: The Utilization of the Equation

Part VI : Special Topics in Experimental Design Mixture Experiments
Chapter 23 : Introduction to Mixture Experiments
Chapter 24 : Simplex Lattice Design
Chapter 25 : The Simplex Centroid Design
Chapter 26 : Constrained Mixtures
Chapter 27 : Statistical Tables and Graphs

References
Index

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