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    Quality Improvement Through Planned Experimentation

    ISBN-10: 0071759662
    ISBN-13: 9780071759663
    Edition: 3rd 2012
    List price: $134.00
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    List Price: $134.00
    Edition: 3rd
    Copyright Year: 2012
    Publisher: McGraw-Hill Education
    Publication Date: 7/17/2012
    Binding: Hardcover
    Pages: 544
    Size: 6.00" wide x 9.00" long x 1.25" tall
    Weight: 1.760
    Language: English

    #60;b#62;Gerald J. Langley#60;/b#62; is a statistician, author, and consultant, and co-founder of Associates in Process Improvement (API), a consulting firm that specializes in the improvement of quality and productivity.#60;p#62;#60;b#62;Ronald D. Moen#60;/b#62; is a statistician, consultant, and teacher to industry, government, and education. He is co-founder of API.#60;p#62;#60;b#62;Kevin M. Nolan#60;/b#62; is a statistician, author, and consultant at API, where he focuses on developing methods and assisting organizations to accelerate their rate of improvement in quality and productivity.#60;p#62;#60;b#62;Dr. Thomas W. Nolan#60;/b#62; is a statistician, author, and consultant, and)co-founder of API.#60;p#62;#60;b#62;Clifford L. Norman#60;/b#62; is a consultant with API whose work has emphasized the psychology of change.#60;p#62;#60;b#62;Lloyd P. Provost#60;/b#62; is a statistician who advises to organizations as an API associate.

    Foreword
    Preface
    Acknowledgments
    Improvement of Quality
    Introduction
    Building Knowledge and the Scientific Method
    Defining Quality
    Model for Improvement
    Sequential Experimentation Using the PDSA Cycle
    Summary
    References
    Exercises
    Principles for Design and Analysis of Planned Experiments
    Introduction and Definitions
    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
    Summary
    References
    Exercises
    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
    Summary
    References
    Exercises
    Experiments with More Than One Factor
    Introduction to Factorial Designs
    Design of Factorial Experiments
    Advanced Topics in the Analysis of Factorial Experiments
    Summary
    References
    Exercises
    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
    Summary
    Appendix: Development of Other Blocking Arrangements
    References
    Exercises
    Evaluating Sources of Variation
    Applications of Nested Designs
    Planning and Analyzing an Experiment with Nested Factors
    More Complex Nested Designs
    Summary
    Calculation of Variance Components
    Calculating and Combining Statistics (X, S, or R)
    References
    Exercises
    Sequential Experimentation-A Case Study
    Improving a Milling Process-Getting Started
    The First Improvement Cycle: Current Performance of the Mills
    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
    Exercises
    Using a Time Series Response Variable
    Incorporating Experimental Patterns in a Time Series
    Shewhart Charts
    Designs for Sequential Experimentation Using Time Series Response Variables
    Summary
    References
    Exercises
    Experiments with Factors at More Than Two Levels
    Factorial Designs with More Than Two Levels
    Augmenting 2k Factorial Designs with Center Points
    Three-Level Designs for Quantitative Factors
    Experiments for Formulations or Mixtures
    Experimental Designs for Complex Systems
    Summary
    References
    Exercises
    Applications in Health Care
    Introduction
    Applications
    Summary
    References
    Exercises
    New Product Design
    Introduction
    Phase 0: Generate Ideas
    Phase 1: Develop Concepts and Define Product
    Phase 2: Test
    Phase 3: Produce Product
    Summary
    References
    Exercises
    Evaluating Measurement Systems
    Glossary
    Index

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