Quality Improvement Through Planned Experimentation

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9780079137814: Quality Improvement Through Planned Experimentation

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

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. 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

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

L'autore:

1991 No primary address Improving Quality Through Planned Experimentaion

Associates in Process Development

Contenuti:

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

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Lloyd Provost; Ronald Moen; Thomas Nolan
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