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The latest experimental design techniques for quality improvement "The methods taught in this book are a major contribution to statistical methods as an aid to engineers, as well as to those in industry, education, or government who are trying to understand the meaning of fi gures derived from comparisons or experiments." -- W. EDWARDS DEMING Co-written by three recipients of the Deming Medal awarded by the American Society for Quality (ASQ), Quality Improvement through Planned Experimentation, Third Edition discusses the principles and methodologies for planning and conducting experiments to improve products, processes, or systems. Fully revised with up-to-date case studies and incorporating new software, this authoritative guide fosters the sequential building of knowledge essential for implementing effective improvements. End-of-chapter exercises reinforce what you've learned, and forms for designing planned experiments help you to integrate the methods in the book into your daily work. The methods of planned experimentation provide an opportunity to better meet the needs of customers, reduce costs, and increase productivity by effecting verifiably beneficial changes. COVERAGE INCLUDES: * Improvement of quality * Principles for design and analysis of planned experiments * Experiments with one factor * Experiments with more than one factor * Reducing the size of experiments * Evaluating sources of variation * Sequential experimentation * Using a time series response variable * Designs with factors at more than two levels * Applications in health care * New product design NEW: Study-it software available for download!
This resource offers a comprehensive framework for the sequential building of knowledge -- a model for improvement -- that is key to making improvements. Step by step, you discover the tools and properties of sound experiments, the methods of planned experiments, and their application to the design of new and improved products and services.
Updated to include the latest in experiment design; this breakthrough resource offers a comprehensive framework for the sequential building of knowledge a model for improvement that is key to making improvements. --
Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation.Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes.The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration.This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments.Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.
This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic. Written in nonstatistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem-solving methodology New edition includes two new chapters on DoE for services as well as case studies illustrating its wider application in the service industry
The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma. Key features: * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods – reducing time taken to design and develop prototypes, reducing time to reach the market * Case studies place DOE techniques in the context of different industry sectors * An excellent resource for the Six Sigma training program This book will be useful to engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs. * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and conduct tests * Case studies place DOE techniques in the context of different industry sectors
This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings