Many engineers and scientists have receive little or no training in designed experiments, and any courses that are available tend to be either abstract and divorced from practical considerations or strictly practical-lacking the rigor and depth necessary for true, long-term understanding.
Practical Guide to Designed Experiments: A Unified Modular Approach bridges that gap, presenting the essential material in a manner that permits rapid application to practical problems but also provides the structure and understanding necessary for long-term growth. It covers two-level and three-level full and fractional factorial design and also includes the L12 and L18 designs popularized by Taguchi. The author describes the role and selection of the system response for measurement and optimization and discusses both conventional and Taguchi approaches, noting their similarities and differences.
Clearly written and well organized, this text shows how the components of experimental design fit and work together. Offering an abundance of examples, case studies, and practice problems, it is highly suited to anyone with a basic science or engineering background but little or no previous exposure to matrix experiments or other elements of planned experimentation.
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Paul D. Funkenbusch is Professor of Mechanical Engineering and Materials Science, University of Rochester, New York.
HOW A DESIGNED EXPERIMENT WORKS
Polishing Fluid Delivery System
Control Factors, Levels, and Coding
Array Selection and Setup
Noise Factors and Conditions
Responses and Characteristic Responses
Analysis of Means
Analysis of Variance
Conclusion
FUNDAMENTAL CONCEPTS
Food for Thought
Over-the-Wall Engineering
Contributions of Taguchi
Stages of Design
Defining Quality (Traditional Approach)
Quadratic Loss Function
The P-Diagram
Conclusion
Homework/Discussion Problems
STATISTICAL CONCEPTS
Review of Basic Concepts
ANOM and ANOVA
Homework/Discussion Problems
ARRAY DESIGN (Two-Level Factors)
Basic Concepts
Interactions
Design Trade-Offs and Strategies
Homework/Discussion Problems
SELECTION OF THE CHARACTERISTIC RESPONSE
Response and Characteristic Response
The "Natural Choice"
Good Experimental Practice
Linked to Long-Term Improvement
Ease of Optimization and Implementation
Taguchi's S/N Ratios
Homework/Discussion Problems
INCLUSION OF REAL-WORLD VARIABILITY
Noise Conditions
A Menu of Strategies
Homework/Discussion Problems
ADDITIONAL ARRAY DESIGNS (Three-Level Factors and Modifications)
Standard Designs for Factors with Three Levels
Design Strategies with Three-Level Factors
Modification of Columns
Homework/Discussion Problems
ADDITIONAL ANALYSIS TECHNIQUES
Choosing an Analysis Technique
Pooling of Unused ("Empty") Columns
Pooling of Smallest Effects
Replication
Normal Probability Plots
Homework/Discussion Problems
APPENDICES
Two-Level Factorial Arrays
Three-Level Factorial Arrays
Screening Arrays
Critical Values of F
References
Index
Each chapter also includes and Overview and a section of Homework/Discussion problems.
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