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(The following description was used when this course was taught during the Spring 2007 Semester. There will likely be differences in the instructor, textbook, and/or outline the next time the course is taught.)
Instructor: Dr. Yu Ding
Textbook: Wu, C. F. J. and Hamada, M., 2000, Experiments: Planning, Analysis, and Parameter Design Optimization, Wiley.
Description: The main objective of this course is to develop and discuss the fundamental theory, concepts and procedures required in the efficient design and analysis of industrial experiments. Emphasis is placed on engineering formulations and applications.
Course Topics
Chapter 1. Basic principle and experiments with a single factor : Concept of six-sigma, relation of this course to six-sigma program, design principals, hypothesis test, least square estimation, one-way layout model, ANOVA, multiple comparison, residual analysis.
Chapter 2 . Experiments with more than one factor : two-way layout model, multi-way layout model, paired comparison design, randomized block design, Latin square design, balanced incomplete block design.
- Chapter 3. Full factorial experiments : Factorial experiments versus one-factor-at-a-time; main effects and interaction effects, ANOVA for factorial experiments; unreplicated design and half normal plot; regression for computing factorial effects.
Chapter 4. Fractional factorial experiments : Design principles for fractional factorial design, maximum resolution and minimum aberration criteria; construction of fractional factorial design; use of design tables.
Chapter 5. Response surface methodology : Concept of response surface methodology; check for curvature; central composite design; steepest descent/ascent method; canonical analysis.
Chapter 6. Robust parameter design : Concept of robust design; noise factor; cross array strategy; comparison of cross array and single array strategies; Taguchi's signal-to-noise ratio and its limitations.
