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- ISBN: 9780071759663 | 0071759662
- Cover: Hardcover
- Copyright: 7/17/2012
A fully revised guide to experimental design for analytic studies, updated with new case studies and coverage of the latest software Quality Improvement Through Planned Experimentation, Third Edition offers in-depth coverage of implementing planned experimentation to make improvements. The Third Edition is thoroughly revised and updated to incorporate new information and case studies on the service and biomedical industries. In addition, a major improvement is the upgrade of the "Study It" now offered on an affiliated website. The methods of analysis for data from analytic studies that are used in this book are unique and are not available in any other software. The statistical methods covered in this book are powerful aids to engineers, technicians, designers, and quality managers who are charged with improving their businesses. The late W. Edwards Deming, who led the sweeping quality revolution in the U.S. in the 20th century, said that this book "breaks new ground in prediction based on data from comparisons of two or more methods, treatments, tests, and experiments." The work of Deming, Box, Taguchi, and other pioneers in quality served as a foundation for everything in this book. Quality Improvement Through Planned Experimentation, Third Edition Discusses the PDSA (Plan, Do, Study, Act) cycle, and how to repeat it sequentially for continuous improvement of processes and products Includes case studies from a manufacturing plant, service, and healthcare operation, as these are areas where quality and planned experimentation are being used most Contains exercises at the end of each chapter so you can implement what you've learned Featuers a companion website with software to help you design and analyze experiments, planning forms, graphical plots, and all data files by page number for examples used throughout the book Co-written by three winners of the Deming Medal, awarded by the American Society for Quality Provides a system for experimental design that is accessible to managers, designers, engineers, scientists, and technicians in all industries Focuses on analytic studies, the appropriate framework for quality improvement projects Uses almost exclusively graphical methods for analysis of data from studies Complete coverage: Improvement of Quality; Building Knowledge, the Scientific Method; Model for Improvement; Using the PDSA Cycle to Test a Change; Principles for Design and Analysis of Planned Experiments; Types of Planned Experiments; Principles for Designing Analytic Studies; Tools for Experimentation; Form for Documentation; Analysis of Data from Analytic Studies; Experiments with One Factor; General Approach to 1 Factor Experiments; Using Control Chart for a 1 Factor Experiment; Example of a One Factor Design; Paired Comparison Experiments; Randomized Block Designs; Incomplete Block Designs; Experiments w/ More Than 1 Factor; Introduction to Factorial Designs; Design of Factorial Experiments; Analysis of Factorial Experiments; Reducing Size of Experiments; Introduction to Fractional Factorial Designs; Fractional Factorial Designs Moderate; Fractional Factorial Designs Low; Blocking in Factorial Designs; Evaluating Sources of Variation; Rational Subgrouping with Control Charts; Nested Design to Study Variation; A Three Factor Nested Experiment; Planning/Analyzing with Nested Factors; More than Three Factors in a Nested Design; A Study with Nested and Crossed Factors; Calculating Variance Components; Calculating Summary Statistics; Case Study: Sequential Experiment; Improving a Mill Process; Time Series Designs; Designs for Studying Changes over time; Use of Shewhart Control Charts; Case Study Sequential Experimentation Using Time Series; Experiments with More than 2 Levels and Special Applications; Factorial Designs with More Than 2 Levels; Augmenting Factorial Designs with Center Points; Three level Factorial Designs; Special applications (Interchangeable Parts, Mixtures, Evolutionary Operation); Experimental Design for Complex Systems; Applications in the Biomedical Field Case Study; New Product Design; Phase 0: Generate Ideas; Phase 1: Develop Concepts, Define Product; Phase 2: Test; Phase 3: Implement; Case Study