- Richard E. DeVor |
- John W. Sutherland |
- Tsong-how Chang |
Title overview
Emphasizing proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement, this text blends statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement.
Importance is placed on both the philosophical/conceptual underpinnings and the techniques and methods of SPC and DOE. The concepts and methods of Taguchi for quality design are combined with more traditional experimental design methods to promote the importance of viewing quality from an engineering design perspective.
- Features a blend of statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement.
- Places particularly strong emphasis on proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement.
- Provides careful explanations, using actual cases, of the relationship between quality intent through engineering design and its realization through manufacture.
- Computer workshops and the associated software provided with the book allow readers to simulate processes and apply the methods presented to solve problems.
Several new chapters:
– Design and Analysis of Engineering Tolerances
– Design and Analysis of Simple Comparative Experiments
– Response Surface Methodology.
• An updated perspective on the state of quality since 1990.
• New case studies
• Three new DOE computer workshops on factorial design, fractional factorial design, and response surface methodology.
• 40% new or revised homework problems.
Table of contents
PART I: FUNDAMENTAL CONEPTS AND METHODS
Chapter 1 Evolution of Quality Design and Control
Chapter 2 Conceptual Framework for Quality: Design and Control
Chapter 3 Statistical Methods and Probability Concepts
for Data Characterization
Chapter 4 Sampling Distributions and Statistical Hypothesis Testing
Chapter 5 Conceptual Framework for Statistical Process Control
PART II: PROCESS CONTROL AND IMPROVEMENT
Chapter 6 Shewhart Control Charts for Variable Data
Chapter 7 Importance of Rational Sampling
Chapter 8 Interpretation of X and R Control Charts:
Use of Sampling Experiments
Chapter 9 Some Control Chart Methods for Individual Measurements
Chapter 10 Process Capability Assessment
Chapter 11 The Design and Analysis of Tolerances
Chapter 12 Statistical Thinking for Process Study: A Case Study
Chapter 13 Shewhart Control Charts for Attribute Data
Chapter 14 Attribute Control Chart Implementation
for Process Improvement: Two Case Studies
PART III: PRODUCT/PROCESS DESIGN AND IMPROVEMENT
Chapter 15 Conceptual Framework for Planned Experimentation
Chapter 16 Design and Analysis of Simple Comparative Experiments
Chapter 17 Design and Interpretation of 2k Factorial Experiments
Chapter 18 Analysis of Two-Level Factorial Designs
Chapter 19 Model Building for Design and Improvement
Using Two-Level Factorial Designs
Chapter 20 Two-Level Fractional Factorial Designs
Chapter 21 Sequential and Iterative Nature of Experimentation
Chapter 22 Robust Design Case Studies
Chapter 23 Modeling of Response Surfaces and Response Optimization
References and Further Readings
Appendix Tables