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Quality Improvement Through Planned Experimentation

Quality Improvement Through Planned Experimentation (Hardcover, CD-ROM, 2nd)

Thomas W. Nolan, Lloyd P. Provost, Ronald D. Moen (지은이)
McGraw-Hill Professional Pub
140,060원

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Quality Improvement Through Planned Experimentation
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책 정보

· 제목 : Quality Improvement Through Planned Experimentation (Hardcover, CD-ROM, 2nd) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 산업공학
· ISBN : 9780079137814
· 쪽수 : 474쪽
· 출판일 : 1998-08-01

목차

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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