Quality improvement through planned experimentation

書誌事項

Quality improvement through planned experimentation

Ronald D. Moen, Thomas W. Nolan, Lloyd P. Provost

McGraw-Hill, c2012

3rd ed

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. 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 conductingexperiments 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 themethods 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!

目次

Chapter 1. Improvement of Quality Building Knowledge and the Scientific Method Defining Quality Model for Improvement Sequential Experimentation Using the PDSA CycleChapter 2. Principles for Design and Analysis of Planned Experiments Types of Planned Experiments Principles for Designing Analytic Studies Tools for Experimentation Form for Documentation of a Planned Experiment Analysis of Data from Analytic Studies Chapter 3. Experiments with One Factor General Approach to One-Factor Experiments Using Run Charts for a One-Factor Design Using Shewhart Charts for One-Factor Experiments Paired-Comparison Experiments Randomized Block Designs Incomplete Block Designs Chapter 4. Experiments with More Than one Factor Introduction to Factorial Designs Design of Factorial Experiments Advanced Topics in the Analysis of Factorial Experiments Chapter 5. Reducing the Size of Experiments Introduction to Fractional Factorial Designs Fractional Factorial Designs--Moderate Current Knowledge Fractional Factorial Designs--Low Current Knowledge Using Blocking to Design a Sequence of Experiments Chapter 6. Evaluating Sources of Variation Applications of Nested Designs Planning and Analyzing an Experiment with Nested Factors More Complex Nested Designs Appendix 6a: Calculation of Variance Components Appendix 6b: Calculating and Combining Statistics Chapter 7. Sequential Experimentation--A Case Study Improving a Milling Process--Getting Started The First Improvement Cycle: Current Performance of the Mlls The Second PDSA Cycle: Sources of Variation The Third PDSA Cycle: Evaluating Mill Cutter Vendors The Fourth PDSA Cycle: Screening Process Variables The Fifth PDSA Cycle: Evaluate Effect of Improvements on the Mill Process The Sixth PDSA Cycle: Evaluating Important Factors The Seventh PDSA Cycle: Determining Optimum Levels The Eighth PDSA Cycle: Confirmation of Improvements Final Actions of the Mill Improvement Team Chapter 8. Sequential Experimentation Using a Time Series Response Variable Incorporating Experimental Patterns in a Time Series Shewhart Charts Designs for Sequential Experimentation Using Time Series Response Variables Chapter 9. Experiments with Factors at More than Two Levels Factorial Designs with More Than Two Levels Augmenting 2^k Factorial Designs with Center Points Three Level Designs for Quantitative Factors Experiments for Formulations or Mixtures Experimental Design for Complex Systems Chapter 10. Applications in Healthcare Chapter 11. New Product Design Phase 0: Generate Ideas Phase 1: Develop Concepts and Define Product Phase 2: Test Phase 3: Produce Product Appendix A: Evaluating Measurement Systems

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