I In this volume, the author demystifies the Design of Experiments (DOE). He begins with a clear explanation of the traditional experimentation process. He then covers the concept of variation and the importance of experimentation and follows through with applications. Stamatis also discusses full and fractional factorials. The strength of this volume lies in the fact that not only does it introduce the concept of robustness, it also addresses "Robust Designs" with discussions on the Taguchi methodology of experimentation. And throughout the author ties these concepts into the Six Sigma philosophy and shows readers how they use those concepts in their organizations.

Extensions of Howell Tong's threshold approach to other fields of statistics abound. This volume is dedicated to his 65th birthday and consists of in-depth contributions from leading experts in a variety of fields of statistics, ecology, economics and finance as well as some of Tong's reprints.

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Many examples drawn from the author’s experience of engineering applications are used to illustrate the theoretical results, which are presented in a cookbook fashion...it provides an excellent practical guide to the analysis of product-life data." –T.M.M. Farley Special Programme of Research in Human Reproduction World Health Organization Geneva, Switzerland Review in Biometrics, September 1983 Now a classic, Applied Life Data Analysis has been widely used by thousands of engineers and industrial statisticians to obtain information from life data on consumer, industrial, and military products. Organized to serve practitioners, this book starts with basic models and simple informative probability plots of life data. Then it progresses through advanced analytical methods, including maximum likelihood fitting of advanced models to life data. All data analysis methods are illustrated with numerous clients' applications from the author's consulting experience.

Describes the life of a beaver and the methods he uses to dam streams and build himself a lodge.

This volume presents an exposition of topics in industrial statistics. It serves as a reference for researchers in industrial statistics/industrial engineering and a source of information for practicing statisticians/industrial engineers. A variety of topics in the areas of industrial process monitoring, industrial experimentation, industrial modelling and data analysis are covered and are authored by leading researchers or practitioners in the particular specialized topic. Targeting the audiences of researchers in academia as well as practitioners and consultants in industry, the book provides comprehensive accounts of the relevant topics. In addition, whenever applicable ample data analytic illustrations are provided with the help of real world data.

This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.

Revised, and updated Design and Optimization in Organic Synthesis presents strategies to explore experimental conditions and methodologies for systematic studies of entire reaction systems (substrates, reagent(s), catalyst(s), and solvents). Chemical phenomena are not usually the result of a single factor and this book describes how statistically designed methods can be used to analyse and evaluate synthetic procedures. The methodology is based on multivariate statistical techniques. The accompanying CD contains data tables and programmes. This book is essential reading for anyone working in process design and development in fine chemicals or the pharmaceutical industry, and is suitable for those with no experience in the field.* Contains recalculated models and redrawn figures, as well as new chapters on for example, the design of combinatorial libraries * Presents strategies to explore experimental conditions and methodologies* Enables the analysis and prediction of the best synthetic procedures

The authority on building empirical models and the fitting of such surfaces to data—completely updated and revised Revising and updating a volume that represents the essential source on building empirical models, George Box and Norman Draper—renowned authorities in this field—continue to set the standard with the Second Edition of Response Surfaces, Mixtures, and Ridge Analyses, providing timely new techniques, new exercises, and expanded material. A comprehensive introduction to building empirical models, this book presents the general philosophy and computational details of a number of important topics, including factorial designs at two levels; fitting first and second-order models; adequacy of estimation and the use of transformation; and occurrence and elucidation of ridge systems. Substantially rewritten, the Second Edition reflects the emergence of ridge analysis of second-order response surfaces as a very practical tool that can be easily applied in a variety of circumstances. This unique, fully developed coverage of ridge analysis—a technique for exploring quadratic response surfaces including surfaces in the space of mixture ingredients and/or subject to linear restrictions—includes MINITAB® routines for performing the calculations for any number of dimensions. Many additional figures are included in the new edition, and new exercises (many based on data from published papers) offer insight into the methods used. The exercises and their solutions provide a variety of supplementary examples of response surface use, forming an extremely important component of the text. Response Surfaces, Mixtures, and Ridge Analyses, Second Edition presents material in a logical and understandable arrangement and includes six new chapters covering an up-to-date presentation of standard ridge analysis (without restrictions); design and analysis of mixtures experiments; ridge analysis methods when there are linear restrictions in the experimental space including the mixtures experiments case, with or without further linear restrictions; and canonical reduction of second-order response surfaces in the foregoing general case. Additional features in the new edition include: New exercises with worked answers added throughout An extensive revision of Chapter 5: Blocking and Fractionating 2k Designs Additional discussion on the projection of two-level designs into lower dimensional spaces This is an ideal reference for researchers as well as a primary text for Response Surface Methodology graduate-level courses and a supplementary text for Design of Experiments courses at the upper-undergraduate and beginning-graduate levels.

Based on deep theoretical as well as practical experience in Reliability and Quality Sciences, Robust Design Methodology for Reliability constructively addresses practical reliability problems. It offers a comprehensive design theory for reliability, utilizing robust design methodology and six sigma frameworks. In particular, the relation between un-reliability and variation and uncertainty is explored and reliability improvement measures in early product development stages are suggested. Many companies today utilise design for Six Sigma (DfSS) for strategic improvement of the design process, but often without explicitly describing the reliability perspective; this book explains how reliability design can relate to and work with DfSS and illustrates this with real–world problems. The contributors advocate designing for robustness, i.e. insensitivity to variation in the early stages of product design development. Methods for rational treatment of uncertainties in model assumptions are also presented. This book promotes a new approach to reliability thinking that addresses the design process and proneness to failure in the design phase via sensitivity to variation and uncertainty; includes contributions from both academics and industry practitioners with a broad scope of expertise, including quality science, mathematical statistics and reliability engineering; takes the innovative approach of promoting the study of variation and uncertainty as a basis for reliability work; includes case studies and illustrative examples that translate the theory into practice. Robust Design Methodology for Reliability provides a starting point for new thinking in practical reliability improvement work that will appeal to advanced designers and reliability specialists in academia and industry including fatigue engineers, product development and process/ quality professionals, especially those interested in and/ or using the DfSS framework.