Quality Improvement Through Planned Experimentation

About the Book

The methodology engineers need to plan andconduct experiments to quantify cause-and-effect mechanisms in complex systems

Updated to include the latest in experiment design, thisbreakthrough 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.

Case studies of experiments in action, and forms and checklists facilitate the adoption of the methods into your daily work. The Second Edition includes new and expanded coverage of how to:

* Test changes to products, processes, and systems
*Evaluate the measurement process
* Extend planned experiments to large systems
*Apply experiments to new product design

Table of Contents:
Foreword Preface Chapter 1-Improvement of Quality 1.1 Introduction 1.2 Improvement of Quality 1.3 Model for Improvement 1.4 Summary References Exercises Chapter 2-Testing a Change 2.1 Introduction 2.2 Prediction and Degree of Belief 2.3 Using the PDSA Cycle to Test a Change 2.4 Designing Tests of Change 2.5 Principles for Testing a Change 2.6 Analysis of data from Tests of Change 2.7 Summary References Exercises Chapter 3-Principles for Design and Analysis of Planned Experiments 3.1 Definitions 3.2 Types of Planned Experiments 3.3 Principles for Designing Analytic Studies 3.4 Tools for Experimentation 3.5 Form for Documentation of a Planned Experiment 3.6 Analysis of Data from Analytic Studies 3.7 Summary References Exercises Chapter 4-Experiments with One Factor 4.1 General Approach to One-Factor Experiments 4.2 Using the Control Chart for a One-Factor Experiment 4.3 Example of a One-Factor Design 4.4 Paired-Comparison Experiments 4.5 Randomized Block Designs 4.6 Incomplete Block Designs 4.7 Summary References Exercises Chapter 5-Experiments with More Than One Factor 5.1 Introduction to Factorial Designs 5.2 Design of Factorial Experiments 5.3 Analysis of Factorial Experiments 5.4 Summary References Exercises Chapter 6-Reducing the Size of Experiments 6.1 Introduction to Fractional Factorial Designs 6.2 Fractional Factorial Designs--Moderate Current Knowledge 6.3 Fractional Factorial Designs--Low Current Knowledge 6.4 Blocking in Factorial Designs 6.5 Summary References Exercises Chapter 7-Evaluating Sources of Variation 7.1 The Control Chart as a Nested Design 7.2 Nested Design to Study Measurement Variation 7.3 A Three-Factor Nested Experiments 7.4 Planning and Analyzing an Experiment with Nested Factors 7.5 More than Three Factors in a Nested Design 7.6 A Study with Nested and Crossed Factors 7.7 Summary Appendix 7A: Calculation of Variance Components Appendix 7B: Calculating and Combining Statistics References Exercises Chapter 8-Experiments for Special Situations 8.1 Factorial Designs with More Than Two Levels 8.2 Augmenting 2k Factorial Designs with Center Points 8.3 Three-Level Factorial Designs 8.4 Experimental Design for Interchangeable Parts 8.5 Experiments for Formulations or Mixtures 8.6 Evolutionary Operation 8.7 Experimental Designs for Complex Systems 8.8 Summary References Exercises Chapter 9-New Product Design 9.1 Introduction 9.2 Phase 0: Generate Ideas 9.3 Phase 1: Develop Concepts and Define Product 9.4 Phase 2: Test 9.5 Phase 3: Produce Product 9.6 Summary References Exercises Chapter 10-Case Studies 10.1 Case Study 1: Improving a Milling Process 10.2 Case Study 2: Redesign a Wallpaper Product Exercises Appendix A-Improvement Using Control Charts A.1 Introduction A.2 Control Charts for Individual Measurements A.3 Subgrouping A.4 Interpretation of a Control Chart A.5 Types of Control Charts A.6 Capability of a Process A.7 Planning a Control Chart A.8 Summary References Exercises Appendix B-Evaluating Measurement Systems B.1 Introduciton B.2 Studying Measurement Processes B.3 Data from a Measurement Process B.4 Monitoring and Improving a Measurement Process B.5 Using Planning Experimentation to Improve a Measurement Process B.6 Case Study: Evaluating a Measurement Process B.7 Summary References Appendix C-Form C.1 Worksheet for Documenting a PDSA Cycle C.2 Form for Documentation of a Planned Experiment C.3 Tables of Random Numbers C.4 Design Matrices for Low Current Knowledge C.5 Design Matrices for Moderate Current Knowledge C.6 Design Matrices for High Current Knowledge Gossary Index

About the Author :
1991 No primary address Improving Quality Through Planned Experimentaion Associates in Process Development